Gift-giving is an art, and when it comes to online shopping, the canvas can sometimes feel cluttered. For DTC brands, the opportunity to make this experience memorable is now more within reach than ever, especially as the global personalized gifts market—valued at USD 51.98 billion in 2024—is expected to grow to [USD 138.17 billion by 2030](https://www.marketresearchfuture.com/reports/personalized-gifts-market-10348). 

This demand for customization and gifting underscores the importance of adding thoughtful touches like personalized messages, gift wrapping, and unique packaging to create an exceptional and seamless gifting experience.

Many DTC brands with smaller catalogs rely on external platforms to offer ready-to-use gifting solutions, like sending e-cards instead of physical products or allowing recipients to provide their shipping information—creating a convenient, customizable experience similar to gift cards. 

However, this reliance on third-party platforms can result in a fragmented user experience, akin to a ping-pong match between the store and the gifting service, which can introduce friction into the process.

Even with custom gift options available, most stores fail to deliver an engaging gifting experience. It's easy to treat gifting as an afterthought, but in reality, a shopper's gift-giving journey begins long before they add an item to their cart—often even before landing on a product page.

## DTC Brands and the Power of Unique Gifting Experiences

Unlike B2C e-commerce or marketplaces, DTC brands often offer unique, special products that attract gift-givers seeking a personalized touch. A well-crafted gifting experience not only sets these brands apart from their competitors but also enhances brand sentiment and serves as a powerful customer acquisition tool, similar to referral programs.

By addressing specific aspects such as tailored filters, cart and checkout optimizations, and personalized experiences for email subscribers, businesses can elevate their gifting offerings and engage both gift-givers and recipients more effectively.

Let's explore these key points to uncover valuable insights, tips, and best practices that can enhance the overall gifting experience.

### Streamlining the Gift Discovery Process

Shopping for someone else can be challenging, especially if users aren’t familiar with the recipient's preferences. This is particularly true in categories like toys, fashion, or beauty products, where age and trends heavily influence choices.

To make the gift-giving process smoother and more enjoyable, e-commerce sites should offer "Recipient" filters, such as Age or Gender. Mori, a brand specializing in kids' and babies' apparel and accessories, provides common gifting categories like "Newborn Baby Gift" along with recipient filters, demonstrating how these features can help customers refine their search based on the recipient's demographics and interests.

E-Commerce stores selling products frequently bought as gifts can significantly improve the gift selection process by following these insights:

* **Age and gender filters:** Allow users to narrow their search by offering filters based on the recipient's age, gender, or relationship (e.g., "For Her" or "For Kids").
* **Interest-based filters**: Let customers filter products based on hobbies, interests, or lifestyle categories, such as "For Pet Lovers" or "For Fitness Enthusiasts."
* **Occasion filters:** Offer filters for specific occasions like "Birthday," "Anniversary," or "Holiday Gifts" to help users choose based on the event.
* **Personalized recommendations:** Use customer data or popular trends to highlight products that suit common gifting scenarios, offering a personalized touch.
* **Filter placement:** Ensure filters are prominently placed, ideally in the main navigation menu or homepage, for easy access and a streamlined browsing experience.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/7a2437b926981d7723352af400450ea947a6a5e1-1600x1052.jpg?fit=clip" alt="Mori Baby Mori recipient filters">
  <figcaption>Mori Baby Mori offers a thoughtful and personalized gifting experience on their site, allowing customers to add gift wrapping, personal messages, and curated bundles that cater to new parents and babies.</figcaption>
</figure>

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/20910d0dd249e64b3fc92d7124dfe61a8065c6ce-1600x1052.jpg?fit=clip" alt="Maisonette recipient filters">
  <figcaption>Maisonette provides a curated gifting experience with options to select beautifully packaged gifts, customizable messages, and handpicked collections for children and parents, making it easy to find thoughtful presents.</figcaption>
</figure>

### Optimizing the Product Page for Gifting
Once users have found a potential gift, providing clear and accessible gifting options on the product page is crucial for a seamless purchasing experience. As the personalized gifts market is projected to grow at a compound annual growth rate [(CAGR) of 12.97%](https://www.marketresearchfuture.com/reports/personalized-gifts-market-10348), the demand for custom options like gift wrapping, messages, and unique packaging is increasing. By clearly displaying these options and offering transparency around costs, DTC brands can capture this growing segment and ensure a positive, memorable gifting experience for their customers.

Many e-commerce sites overlook this step, which can lead to frustration for gifter-givers who need to know early on what gift options are available without digging through the checkout process. Lake, for example, effectively advertises its branded gift box on the product page, offering an easy way to add it to the cart and providing detailed options, streamlining the gifting decision for users.

To optimize the product page for gifting, consider these strategies:

* **Display gifting options clearly**: Show available gifting options—such as gift wrapping, custom messages, or special packaging—on the product page to help users make informed decisions early.
* **Make gifting costs transparent**: Clearly state any additional costs associated with gift services like wrapping fees or packaging upgrades, preventing unpleasant surprises later in the process.
* **Link to more gifting information**: For complex gift services include a link to a dedicated gifting info page where users can explore options in detail, keeping the product page clean and focused.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/b114d6b08da9784a3ad53ef70a4235da221078ec-1600x1052.jpg?fit=clip" alt="Lake Pajamas offers Gift boxes in the buy section">
  <figcaption>Lake Pajamas offers a simple yet elegant gifting experience, allowing customers to add gift boxes, personalized messages, and luxurious packaging to their orders, perfect for presenting their high-quality sleepwear as thoughtful gifts.</figcaption>
</figure>

### Enabling Customers to Enter a Gift Message
A key feature for sites offering gifts is the ability to include a personalized message. While this seems straightforward, here are a few best practices:

* **Display Custom Message Option in the Cart:** Ensure the option to add a custom gift message is available and visible in the cart, so users can easily include it before completing their purchase.
* **Avoid prefilled gift messages:** Using preset messages like “I hope you enjoy this gift!” can confuse users, who might think the field is already filled in. Instead, only show a placeholder after users opt to include a message.
* **Use a "Save" button**: Rather than relying on autosave, provide a "Save" button so users feel confident their personalized message is securely stored.
* **Preview gift message in order summary:** Include a preview of the gift message in the order summary to reassure users that their message has been saved and will be sent with the order.


### Integrating Special Wrapping and Branded Gift Boxes into the Cart

Special wrapping or branded gift boxes can add a final, thoughtful touch to the gifting experience. Gifting features can vary widely across e-commerce sites, making it essential to provide clear information about these options. When incorporating special wrapping and branded gift boxes into the cart, consider the following insights:

* **Brief Descriptions:** Include short descriptions or icons representing gift wrapping and branded box options to help customers quickly understand the choices available.
* **Mark Free Options Clearly:** If gift wrapping or custom packaging is offered at no additional cost, clearly indicate that these options are free to prevent confusion.
* **Opt-Out Option:** Provide an easy way for customers to opt out of special gift wrapping or boxes if they prefer to skip these options.
* **Discounted Bundles:** Offer discounted bundles that include the product and gift wrapping or a branded box to increase the overall value of the purchase.
* **Delivery Times:** Especially during the holiday season, it's important to provide a delivery-date estimate or delivery-date range. Many stores that don't provide this information risk failing to deliver gift orders on time. By offering accurate delivery estimates, customers can plan their gift-giving effectively.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/75d41dc78e3e19448d4c7e313f9a31f966064129-1600x1052.jpg?fit=clip" alt="Lake Pajamas offers Gift boxes in the cart">
  <figcaption>The easy-to-spot "Select Gift Options" button ensures that customers can quickly personalize their gift, making the process of sending thoughtful, beautifully packaged sleepwear even smoother and more user-friendly.</figcaption>
</figure>


### Leveraging Personalization for Existing Customers
Offering personalized experiences for existing customers can elevate the gifting process and create a sense of connection between customers and your brand. Here are a few ways to achieve this:

* **Custom Profiles for Gift Recipients:** Allow customers to create profiles for their loved ones, where they can save important details such as birthdays, genders, sizes, and interests. This information can be used to prefill filters during the search process, making it easier and faster for customers to find the perfect gift.
* **Saved Items and Wishlists:** Enable customers to save their favorite items or create wishlists for each recipient profile. This not only simplifies the gift selection process but also encourages repeat visits and purchases.
* **Personalized Reminders and Recommendations:** Send your customers timely notifications before recipients' birthdays or special occasions, along with personalized gift recommendations based on the recipient's profile. This thoughtful gesture can increase customer satisfaction and foster brand loyalty.

![](https://cdn.sanity.io/images/kqgmf0g2/production/99b9208357c496fca7a3e2675aadfe4720de6174-1600x1052.jpg?fit=clip)

Maisonette offers a great example of effective personalization features. Users with an account can save multiple profiles with details like name, date of birth, and gender. Maisonette then provides selections based on these data, and users receive a notification one month before the recipient's birthday with a special promotional code. Such personalization can lead to higher conversion rates, increased customer retention, and greater overall success in the competitive DTC market.

## Wrapping Up the Perfect Gifting Flow

The gifting experience is a crucial aspect of e-commerce, particularly for DTC brands specializing in unique, high-quality products. As shoppers increasingly seek personalized and memorable gifts, e-commerce sites must meet these expectations by offering thoughtful and transparent gifting options.

Remember that a well-executed gifting experience can be a powerful differentiator in the competitive e-commerce landscape, providing both immediate benefits and long-term gains for your brand. As you refine your gifting strategy, keep in mind the importance of creating a seamless and enjoyable shopping journey that fosters customer engagement and loyalty.

Ready to enhance your gifting experience? Get in touch with the team at Nebulab to create a seamless, personalized, and memorable gifting process that delights your customers and drives results. Whether it's optimizing product pages, integrating custom messages, or adding unique packaging, we can help you turn your DTC e-commerce into a go-to destination for thoughtful gifts. 

Together, we can make your gifting strategy truly stand out! [Reach out today.](https://nebulab.com/contact-us)

How DTC Brands Can Elevate Their Gifting Experience

With the Ecodesign for Sustainable Products Regulation (ESPR) becoming effective on July 18, 2024, Digital Product Passports (DPPs) are now set to become a reality in the European Union within the next 2-3 years.

While it is still unclear which brands the regulation will affect exactly and what requirements it will entail, if you’re a merchant that manufactures or imports their products in the EU, you should keep up to speed with the state of the legislation so that you’re not unprepared by the time DPPs become mandatory (which is expected in 2026-2027).

[Luke Hodgson at Commerce Thinking](https://www.commercethinking.com/) has published a couple of deeply researched and incredibly thoughtful articles on the subject. You can find them here:

* [How New Luxury Brands Prepare for DPP](https://www.commercethinking.com/p/how-new-luxury-brands-prepare-for)
* [Should I care about Digital Product Passports?](https://www.commercethinking.com/p/should-i-care-about-digital-product)

Because Luke has already done an outstanding job of talking about DPPs from a regulatory standpoint, we think it’s worth approaching the topic from a slightly different angle. 

More specifically, we’ll outline three ways in which brands can ride the regulatory wave the EU put in motion with the ESPR, augmenting the customer experience around their Digital Product Passports to drive growth and engagement among their audience.


## 1. Promoting Product Transparency and Circularity

We’d be remiss if we did not mention the very goal the ESPR set out to achieve, which is to promote transparency and circularity in the manufacturing and retail industry. Far from simply being a bureaucratic concern, we think the regulation both reflects and accelerates a broader shift in consumer sentiment.

The signs are strong that [consumers are getting tired](https://www.voguebusiness.com/story/consumers/why-consumers-are-questioning-luxurys-markups) of the luxury industry’s empty promises and insane markups. As a result, the consumer landscape is getting polarized: on one end, consumers look for value; on the other, they look for artisanality and sustainability. For the latter segment, DPPs are invaluable: pre-purchase, consumers can use them to evaluate a brand’s supply chain and ESG posture; post-purchase, they can learn more on the product and access end-of-life options.

Brands can lead the way here by going above and beyond what the ESPR mandates by investing in a delightful, on-brand consumption experience; by enriching the mandatory data with editorial elements that more deeply connect the consumer to the brand; and by offering easy access to resell, repair, and recycle options.

**Example:** Many Scandinavian brands [do this incredibly well.](https://www.commercethinking.com/p/scandinavia-is-years-ahead-on-sustainability) Among them, [Nudie Jeans](https://www.nudiejeans.com/) stands out for the excruciating level of detail available about the supply chain behind each one of their products and their commitment to offering clear, easily accessible end-of-life options to customers.


## 2. Collecting (and Activating) Zero-Party and First-Party Data

For all the woes suffered by the direct-to-consumer (DTC) channel in recent years, it’s still undeniable that DTC offers brands an unparalleled amount of qualitative and quantitative data. In fact, as brands move to an omnichannel-by-default strategy, they are getting more comfortable with seeing DTC as a channel dedicated almost exclusively to data acquisition , while wholesale and marketplaces are being used to pursue sustainable growth.

In the long term, we believe there’s an opportunity for DPPs to close this gap. By effectively bypassing the sales channel and giving brands a standardized way to re-connect with their end customer, no matter how the product has been purchased, brands will be able to acquire invaluable zero-party and first-party data.

As always, how brands activate this data will ultimately make or break the experience. The most obvious use cases are customer profiling and marketing (e.g., by acquiring their email address and demographics, the brand can create a direct relationship with a previously anonymous customer).

Further down the road, there’s a tangible opportunity to graduate beyond one-way data acquisition, allowing customers to also leverage their DPPs as “proof of ownership” in a centralized or decentralized digital identity system (NFTs are the usual suspect here, but by no means the only possible technology). This would enable even richer marketing activations, more accurate insights into secondary market transactions for a brand’s products, and even peer-to-peer between the brand’s customers.

**Example:** Armani partners with [Certilogo](https://certilogo.com/) to power their DPPs. When scanning a Certilogo QR code, the consumer is prompted for their email, which is shared with the brand for marketing purposes.

## 3. Creating Phygital Brand Activations

Finally, DPPs are the perfect conduit for brands looking to create phygital experiences, blending the best of the physical and digital world and allowing customers to experience the brand’s products in novel and engaging ways.

These experiences can show up in a myriad of different shapes and forms: brands can link a customer’s information to the DPP and use it for expedited in-store access; they can grant owners of certain products exclusive perks at select venues and events; or they can allow customers to redeem digital product twins and transfer them to compatible gaming or metaverse platforms.

Phygital activations makes the most sense when the brand’s products can be seamlessly integrated into the customer’s existing day-to-day, which means that collabs are key. The ESPR and broader adoption of DPPs are likely to play an important role here, normalizing the concept of phygital experiences and pushing more brands into the space.

**Example:** During the latest Hahnenkamm Races in Austria, Hugo Boss partnered with MasterCard [to bring their BOSS x Perfect Moment ski jackets to life.](https://group.hugoboss.com/en/newsroom/news/news-detail/boss-returns-to-hahnenkamm-races-as-official-presenting-partner-and-unveils-magic-moment-wearable-technology-experience) An NFC tag embedded in the jacket’s sleeve allowed the wearer to access the races, ski lifts, and an exclusive pop-up store, as well as to execute contactless credit card payments.


## Approach Digital Product Passport Investments as R&D Projects

In this article, we have only scratched the surface of the kind of activations that DPPs might enable for consumer brands. The sky’s the limit, and the nature of DPPs means that brands will be able to evolve their implementations long after a product has been sold, continuing to release new interactions that keep the customer engaged with the brand and its products.

With that said, it’s also important to be realistic about the time horizon of the ESPR’s implementation.

DPPs will not become mandatory in the EU until 2026 or 2027–even then, it’s likely that they will only be required for publicly traded organizations initially. Rolling out DPPs in compliance with the EU’s specifications will require significant investments in supply chain transparency and digital capabilities, which are not feasible to expect of smaller operators.

As such, most brands should approach DPP investments as R&D projects at this stage. Now is the time to map out your roadmap to compliance, evaluate vendors, and think about activations that go beyond the regulatory requirements and enrich your brand’s customer experience.

Above all, we urge brands to find the right balance between being ahead of their game and containing their investment. The good news about DPPs is that they are, well, digital–there will always be time to experiment and add more functionality later on. Tests can be run in small, incremental batches on select SKUs before a broader rollout is needed.

As the ESPR is rolled out and consumers start waking up to the new opportunities afforded by DPPs, we expect their usage to become more widespread among the general population. At that point, brands that had already been experimenting will have the data, capabilities, and confidence they need to finalize their implementations and translate their experiments into a tangible competitive advantage.

Digital Product Passports and Retail’s New Growth Opportunity

In the last few years, customer acquisition has become more challenging and expensive for direct-to-consumer (DTC) brands due to App Tracking Transparency, increased competition, and inflationary pressure. With Chrome deprecating third-party cookies in late 2024/early 2025 and the resulting “signal loss,” marketers expect campaign performance to take another hit, driving Customer Acquisition Cost (CAC) further up.

As a result, e-commerce executives have been paying increased attention to customer retention strategies. Existing customers are cheaper to re-engage, have a higher average order value, and can drive organic acquisition through referrals, UGC and word of mouth.

In our conversations with clients, Customer Relationship Management (CRM) strategies have been top-of-mind, and new or revamped loyalty programs are among the main projects that brands are putting on the roadmap for the next year–often coupled with more intentional zero-party/first-party data strategy and better personalization capabilities.

However, not all loyalty programs are created equal: different growth stages, categories, and business models call for different program designs. The loyalty ecosystem has become increasingly complex to navigate, with a deluge of tools and tactics that brands can tap into. While this leads to more flexibility and healthier competition, even expert practitioners are often at a loss when they want to launch a new program or when they need to understand the performance and pitfalls of their existing one.

In this article, we’d like to cover the e-commerce loyalty programs through a first-principles approach. We’ll look at how to pick a program structure, how to design the “earn” side and the “burn” side of your program to maximize ROI–based on factors such as your geography, target demographic, product category, and business model–and how to measure the effectiveness of your program.

Let’s dive right in!

## How to Structure Your Loyalty Program

The number one mistake we see brands making when rolling out their loyalty program is not being intentional enough when it comes to program structure. Instead, they just do the first thing that comes to mind, copy popular competitors or other brands they admire, or mindlessly adopt the functionality of whatever loyalty app they have decided to install (which, in turn, is often dictated by the app’s popularity).

Unfortunately, loyalty programs are extremely nuanced. The ideal program depends on factors such as geography, target demographic, product category, business model, internal capabilities, and several other elements that, taken together, make certain structures and rewards more effective than others.

If you don’t account for all these elements, you will end up with a program that’s underperforming at best and detrimental at worst. Think about a luxury fashion brand that releases a discount-based loyalty program: customers wouldn’t simply be uninterested, but some might actively resent the brand for putting forward a cheap, transactional program that is not consistent with your brand’s image.

In fact, we find that _consistency_, rather than _uniqueness_, is the primary trait of successful loyalty programs. **Good programs are consistent with the needs of both the brand and its consumers–at all times and across all touchpoints.** You don’t need to be cleverer than everyone else; you just need to consistently make your customers happy in ways that will ultimately benefit the brand. If you can align these two needs, you’re halfway there.

As you can imagine, that’s easier said than done. In reality, most brands are pulled in a million different directions, and a compromise is often needed to find the ideal structure.

In the following paragraphs, we’ll outline a streamlined, repeatable process that you can follow to design the foundational aspects of your loyalty program.

### 1. Pick a Loyalty Program Type

The very first step is to pick the structure of your loyalty program.

You’ll find a lot of conflicting and confusing information on the web about the different possible types of loyalty programs–most resources are trying to one-up each other by adding one more variation to a never-ending list of program structures.

Let’s simplify this. In our experience, all loyalty programs fall into one of two categories:

* **Balance-based programs.** In a balance-based program, customers are awarded points when they perform specific actions (e.g., spending with the brand) or at key moments (e.g., on their birthday). They can then spend those points to redeem rewards such as discounts or free products. This is similar to having a bank account where you accumulate money and then spend it.
* **Tier-based programs.** Tier-based programs are similar to transactional programs in that you design a way to “quantify” how loyal customers are. However, rather than the customer “spending” their loyalty, the customer is assigned a loyalty tier (which can be permanent or not). Based on the customer’s tier, they are then granted different perks, such as free shipping or early product access.

Everything else (gamified programs, [paid memberships](https://nebulab.com/blog/ecommerce-memberships), value-based programs, etc.) is a variation of the above. For instance, a paid membership is just a tiered loyalty program where your tier is determined by a digital subscription plan: you pay the brand every month just to have access to the perks of that specific tier.

Neither type of program is superior to the other. Whether to go with a balance-based program or a tier-based program is primarily a function of your brand’s positioning, price point, and consumer demographic:

* **Balance-based programs are better for brands selling to a price-sensitive audience** that worries about value for money and responds better to more tangible rewards. These customers are likely already subscribed to similar programs, e.g., at their grocery store, making the model more familiar.
* **Tier-based programs, on the other hand, are a better fit for a more affluent type of consumer** who worries about status more than about convenience. The aura of exclusivity associated with being on the upper tiers of a brand’s loyalty program is a perfect match for such a demographic.

Another factor to take into account has to do with the nature of the rewards you expect to give your customers: some rewards (such as freebies) are supposed to be one-offs, which makes them a better fit for a balance-based program, while others (such as free shipping) are better modeled as “permanent” rewards, which makes them a better fit for a tier-based program.

If you can’t decide, you should know that it’s not uncommon to see hybrid programs: Most airlines, for instance, have loyalty programs where consumers accumulate rewards as they travel with the airline. Certain perks (e.g., priority boarding) are unlocked through a tier-based mechanism, while others (e.g., free trips) are unlocked through a balanced-based mechanism.

**However, as we’ll see later, simplicity and ease of use are key elements that determine the success of a loyalty program**, so you should only take this approach as a last resort, _especially_ if you’re launching a brand-new program.

### 2. Model the “Earn” Side of Your Program

Once you’ve chosen the foundational structure of your loyalty program, it’s time to determine how your customers will earn their rewards. At Nebulab, we typically refer to these as _triggers_ because they trigger your customers to carry out certain behaviors.

When designing a trigger, there are only two elements you need to think about:

* What is the action you want customers to take?
* How are you going to reward customers for that action?

They might seem like trivial questions, but they’re really not. Think about it this way: a loyalty program is an investment. You’re giving away value (in the form of discounts, freebies, services, etc.) in exchange for a specific return. If you get your triggers wrong, you might fail to drive action or drive the wrong action, which means you’re giving away your loyalty program perks in exchange for nothing.

While most brands start by rewarding customers for spending more, you don’t have to stop there. Here are a few additional ideas that might be relevant:

* **Acquire zero-party data.** If you need more information about your customers, how about _asking_ them? You can use your loyalty program to collect data about a customer’s preferences, habits, and attitudes and then activate it as part of your personalization strategy or product manufacturing process.
* **Encourage event attendance.** If you host virtual or IRL events, you can encourage attendance by rewarding attendees through your loyalty program. (Note: Exclusive event access also makes for a very appealing loyalty perk, so this goes both ways!)
* **Collect user-generated content (UGC).** Are you struggling to collect UGC for your brand, or do you need some organic content for a new product launch? You can reward customers for posting content on social media and allowing you to reuse it across your digital properties.
* **Promote referrals.** For obvious reasons, referrals and loyalty go hand-in-hand. If you want to drive more referrals, you can use your loyalty program to encourage customers to tell their friends about your brand. Bonus: Make it an even better deal by also rewarding the _referee_, not just the referrer!

These are very generic examples that will apply to most brands. However, as we’ve already said, the sky’s the limit: find ways to activate your loyalty program that make sense for your brand, and keep in mind that the “right” triggers will change over time.

When working with brands, we encourage them to treat their loyalty program as a blank canvas that they’re constantly drawing on. At any given time, you should be able to draw a straight line from your current goals and challenges to your loyalty program’s structure: How does your program drive behavior that helps your business reach the next level?

### 3. Model the “Burn” Side of Your Program

Once you’ve established how customers will advance in your loyalty program, you need to determine what perks you’ll offer.

A common mistake at this stage is copying what everyone else does and offering discounts without thinking about what your customers really want.

Typically, we bucket loyalty program perks into four categories:

* **Exclusivity.** These perks include exclusive/early access to products, content, or events. They are typically a good fit for premium brands with an established “brand universe” (i.e., digital and physical IP) that they can expand, remix, and leverage as part of their loyalty program.
* **Cash.** These are more tangible monetary perks such as discounts, cashback, freebies, free shipping, and other forms of value add. They are typically a good fit for value-driven brands, where consumers are more price-sensitive and want to know they’re getting the most bang for their buck.
* **Services.** Think personal shoppers, pet grooming, and other services you can bundle with your product to create a holistic brand experience. They are a good fit for product categories that are service-adjacent (such as pets), require constant education (such as apparel/beauty), or both.
* **Community.** Exclusive communities are becoming increasingly popular, allowing customers to retreat from the open web into a “safe space.” These communities can double down as invaluable sources of UGC and customer feedback, creating a powerful loop.

It’s worth spending a few words on discounts, which are extremely common in loyalty programs. While discounts are easy to implement and seem like a safe bet, they are not necessarily the right choice for all brands. Discounting has several problems:

* **It’s expensive.** While this ultimately depends on your profit and operating model, discounting products year-round can severely impact your bottom line.
* **It scales poorly.** With most of the perks we have described, you can access economies of scale. That’s not the case with discounting: no matter your size, a 10% discount will always mean giving away 10% of revenue.
* **It hurts your brand.** Discounting lowers the perceived value of your product and can easily backfire, especially if your brand has a premium positioning.

So, how do you decide which perks to offer? It’s pretty simple, actually: you just ask!

Talk to 10-20 of your most loyal customers, i.e., those who will realistically reach the upper echelons of your loyalty program. You’ll want to ask them about their lifestyle, how your brand fits into their day-to-day, what other brands they shop with, and what they would value in your loyalty program. This should give you a comprehensive overview of what perks will resonate the most.

A final note: if your brand sells in different channels (e.g., online and in your physical stores), design your perks to appeal to customers no matter their shopping channel. For instance, a free shipping perk doesn’t make sense to someone who typically shops in-store, but having access to a personal stylist once a year is much more enticing.

## Optimizing Your Loyalty Program CX

When we talk about Customer Experience (CX), we refer to _how_ customers will interact with your loyalty program. Making your program as simple as possible to understand and consume is one of the main factors determining its success.

On that note, here are a few suggestions for creating an amazing loyalty program CX:

* **Unify the experience.** By funneling as many of your CRM operations as possible through your loyalty program, you will streamline the customer experience, maximize enrollment rates, and reduce operational overhead for your team. This can go as far as enrolling any customer with a registered account into your loyalty program.
* **Keep it simple.** At the same time, you want to avoid overcomplicating things: if customers get confused, they might stop engaging with the program. Provide clear instructions for earning and consuming rewards, and keep reminding customers of the existence and structure of your program across different touchpoints (e.g., via email, SMS, at checkout, etc.).
* **Leverage personalization.** Loyalty program personalization is a somewhat sophisticated but compelling technique. Some perks resonate more than others: if you can identify which customers are most likely to appreciate them, you can effectively maximize customer engagement.

Remember that if you’re using a third-party app to power your loyalty program, your ability to customize the CX might be somewhat limited. This isn’t a bad thing per se, but it is something you’ll want to account for when picking your ideal partner. You also shouldn’t be scared of deploying a little bit of custom technology, if it helps you stand out from the crowd and create a loyalty program that your customers will love you for.


## Measuring Loyalty Program Effectiveness

Launching your program is only half the battle. As we’ve mentioned, a good loyalty program is like a blank canvas: you should constantly adjust it to drive the behavior you want at that moment in time. To do that effectively, you need to measure the success of your program.

What KPIs to measure ultimately depends on your program's structure, perks, and rewards. At a minimum, you’ll want to look at the following:

* **Enrollment Rate:** % of unique customers who enrolled in your program
* **Engagement Rate:** % of unique customers that engaged with your program in any capacity (e.g., looking at their balance)
* **Redemption Rate:** % of unique customers that used a perk from your program
* **AOV, LTV, and Time-Bound Retention:** you’re already measuring these for your regular customers. For your loyalty members, you want to measure the program’s incrementality with respect to these KPIs–more on that below.
* **Program Costs:** you should have a clear picture of both variable costs (discounts, freebies, events, etc.) and fixed costs (IT, training, etc.).

Finally, don’t forget about customer feedback! Ideally, you should constantly seek qualitative and quantitative feedback from your customers in the form of NPS surveys and moderated/unmoderated interviews to improve the program.

### A Note on Self-Selection and Program Incrementality

Unfortunately, the literature on measuring loyalty program effectiveness can be extremely poor, when not misleading. Most resources will point you to metrics such as Customer Lifetime Value (CLTV) and leave it at that. Some will tell you to compare metrics between members and non-members, which is awfully incorrect.

**When it comes to loyalty programs, what you want to measure is their _incrementality,_ i.e., to what extent the loyalty program _actually_ affects your KPIs.** If you do that, you’ll find that the incrementality of any loyalty program is much lower than what you’d see if you just computed the performance delta between members and non-members.

For example, let’s assume you want to measure how much your loyalty program contributes to increasing Average Order Value (AOV). You look at the AOV of customers enrolled in your program and find that it is, on average, $25 higher than for non-members. You might be tempted to conclude that your loyalty program leads to a $25 increase in AOV, but you would be wrong–_very much_ wrong.

Think about it this way: many of your loyalty program’s members would have spent the exact same amount (or perhaps just a little less) with your brand, _even if the loyalty program was not there to begin with._ These customers are _not_ spending more because they’re subscribed to your loyalty program; instead, they have subscribed to your loyalty program _because_ they were spending more in the first place. This statistical mistake is called self-selection bias, and it’s unfortunately very common among inexperienced practitioners.

To properly compute program incrementality, you need to rely on techniques such as difference-in-differences analysis, where you measure a metric before and after customers join your program, and Propensity Score Matching (PSM), where you “cluster” customers by affinity and compare their behavior. Unfortunately, it would take an entire article to unpack these techniques, so we encourage you to do additional research.

## Loyalty Programs Are Powerful, but They Require Attention

As you’ve seen, launching a loyalty program for your brand is not an initiative you can treat as an afterthought. It requires careful planning, spotless execution, and continuous, data-informed iteration to maximize your ROI. Otherwise, you might end up with a loyalty program that’s more expensive than the incremental revenue it generates.

In this article, we’ve only scratched the surface, but there’s so much more: depending on the structure of your program, you’ll need to think about tier pricing or point expiration; interviewing customers is an art in and of itself, as is measuring program incrementality. All of these topics would warrant separate articles.

If you need help launching your program or overhauling your existing one, feel free to reach out! Together, we can create a program that will grow your business while delighting your customers.


The Ultimate Guide to E-Commerce Loyalty Programs

Have you ever found yourself pondering over a complex problem for hours or days? You explore all possible paths yet end up with more doubts than certainty. Then, a casual conversation with a colleague suddenly illuminates your thoughts. Just articulating your challenge out loud, especially in a trusted circle, opens your mind and allows your ideas to blossom.

Imagine having a format to refer to every time you are stuck on a problem–a structured approach that unblocks the flow of ideas and brings order to chaos. A workshop is precisely that: a repeatable process to create an environment where conversation flows, ideas flourish, and solutions are nailed down.

At Nebulab, we use workshops to help our teams and clients navigate complex business domains, design efficient middleware integrations, and tackle multi-faceted productivity and collaboration challenges. Over the years, the humble workshop has proven, time and again, one of the most effective ways of taming complexity.

In this post, we’ll explore the practices we adopt for running workshops that bring value to both organizers and attendees.

## The Key Ingredients of a Good Workshop

If you’ve watched movies like A Beautiful Mind or the recently released Oppenheimer, you might be familiar with the process mathematicians use to dig into a problem. They gather in front of a whiteboard, and for the most part, they sketch formulas and diagrams rather than relying on verbal communication. They alternate themselves in the writing, pause, take a step back to glimpse what they produced, and question their thoughts with “what if” questions. 

It might not be evident at first glance, but these whiteboard conversations have a lot in common with workshops:

* The participants are exploring a complex domain
* The rules of engagement are well-understood
* The physical environment has the proper setup
* The participants visualize their concepts

All these elements are integral to a successful workshop, all concurring to create a space where ideas can be developed and examined collaboratively.

Let’s take a look at each of them, one at a time.

### Complexity and Collective Intelligence

The heart of a workshop lies in the rich interaction between participants.

This interactive environment is particularly effective when tackling complex problems characterized by uncertainty or requiring diverse expertise. Participants from different areas of the business (e.g., industry experts, e-commerce managers, and tech leaders) bring a range of diverse insights that rarely have a chance to converge.

In a workshop, we leverage the group's collective intelligence, which often leads to superior decision-making, problem-solving, and innovation than an individual could achieve by themselves. This is particularly true in scenarios where the complexity of the subject matter benefits from a multitude of perspectives.

Each aspect of a workshop–from its physical setup to the methods of visualization and facilitation– is designed to harness this collective wisdom to navigate and illuminate complex issues.

### Rules of Engagement

A simple, clearly understood set of rules is essential to facilitate efficient interaction and meaningful conversation in a workshop.

We can’t just put people in a room and expect valuable outcomes to emerge. Every workshop has a format and rules; for mathematicians, the format is mathematical symbolism, and the rule is to alternate in front of the whiteboard until a satisfactory outcome is achieved.

It’s critical to keep things simple: the participants need to be focused on exploring the problem domain, not on remembering or feeling constrained by the rules.

For instance, in a workshop I recently facilitated, we started with two rules: blue sticky notes to indicate a system and yellow sticky notes for activity in a system or data exchanged by two systems. In the second half of the workshop, I introduced a third rule: red sticky notes to highlight the critical/challenging aspects of a system’s behavior. With such a simple set of rules, all participants had an easy time contributing, the workshop ran all day with little effort, and the outcomes were excellent.

Pro tip: progressively revealing the rules is a trick that helps attendees focus on the matter at hand and ensures they aren’t overwhelmed.

### Physical Environment

An often overlooked but crucial aspect of workshops is the room setup.

Adequate space is necessary for participants to move freely, interact with each other, and engage with tools like boards or flipcharts. Think of the mathematician with unobstructed access to their whiteboard–this accessibility is critical.

In my experience, it's beneficial to rearrange the furniture to suit the workshop's needs. Typically, I align chairs along the room's perimeter, creating a central, open area in front of the board or designated workspace. This layout encourages movement, collaboration, and a focus on the current task.

Remember: the ideal setup can vary depending on the nature and size of the workshop. The goal is to create an environment that fosters active participation and easy access to your collaboration tools.

### The Power of Visualization

Relying exclusively on verbal communication often limits us to our existing mental models, creating a clash where new, breakthrough ideas struggle to emerge. This is because it's easier to interpret what we hear within our existing frameworks than to challenge and change them. 

Visualization offers a powerful solution to this limitation.

Going back to our example, mathematical symbols serve as the visualization tool. For a diverse workshop audience, simpler tools are often more effective: these can be post-its, diagrams, or even Lego bricks. Visualizing concepts on a wall is particularly impactful: it not only allows workshop participants to step back and see the 'big picture,' but also ensures that all participants can engage and contribute equally.

This method ties in with our earlier discussion on room setup (an open space in front of a wall facilitates this kind of visualization) and with the idea of a simple ruleset (guiding participants on how to contribute visually is vital).

## The Role of the Facilitator

In our example, a group of mathematicians might naturally fall into a collaborative rhythm without a facilitator. However, in a larger group setting, especially with individuals who have strong perspectives and diverse backgrounds, having a facilitator becomes essential.

A facilitator isn’t required to be a domain expert. Instead, their skills lie in observing group dynamics, actively engaging participants, offering suggestions discreetly, and summarizing discussions. The facilitator must be able to identify and guide the group’s focus to emerging concepts, even when they don’t have an in-depth understanding of the workshop’s subject.

Facilitators are crucial in navigating the complexities of group interactions, which can be unpredictable and challenging.

A note of caution to facilitators: not every workshop goes as planned, hence flexibility is key. Much like a jazz musician improvising in a jam session, a facilitator must read the room and adjust the workshop's flow as needed.

A good facilitator can transform a potentially chaotic discussion into a harmonious and productive session.

## How We Use Workshops at Nebulab

Across various industries, workshops are versatile tools that can be tailored to various needs. From Retrospectives and User Story Mapping in Agile teams to Event Storming for Domain-Driven Design architectures, their applications are manifold.

As an e-commerce agency, we find workshops particularly effective in two main areas. Hopefully, you can use these examples as inspiration for your own workshops.

### E-Commerce Middleware Design

Firstly, as detailed in [my previous blog post,](https://nebulab.com/blog/ecommerce-middleware) we use workshops to explore connections and dependencies between systems when architecting middleware software.

This workshop format is inspired by [Event Storming](https://www.eventstorming.com/), and it’s best described as a form of generative business process mapping: treating the wall as a timeline, we use sticky notes to represent the systems we are discussing (e.g., the e-commerce platform or the ERP software), the activities performed by the user or system, and events those activities generate.

Aligning the sticky notes on a timeline gives us a general overview of the business process and the system’s relationships. It also allows us to rearrange the responsibilities and dependencies between systems and the middleware.

On the brand side, we typically invite any stakeholders with an active role in the systems we’re analyzing. On the Nebulab side, we have a workshop facilitator, one or more strategists to provide insights into the business domain, and technologists to provide insights into the system’s architecture.

### E-Commerce Domain Mapping

Workshops are also invaluable when implementing complex business rules or requirements deeply rooted in a brand's unique domain.

In this case, we start by representing the different types of actors involved in the domain, then the names of the business rules, and then the logic behind each rule. Finally, we arrange everything as a tree. Focusing on the users and visually representing the conditions and constraints applied to the system helps us untangle complex business domains and spot corner cases that were not previously covered.

The value of these workshops lies in their ability to bring together people with diverse expertise–from those with deep business or process knowledge to technology experts who may not be as familiar with the brand's specific domain. This diversity is crucial for surfacing and clarifying assumptions, removing ambiguity, and fostering mutual understanding.

An additional benefit is the reorientation towards the “bigger picture.” It's common for individuals immersed in day-to-day tasks to lose sight of the organization’s broader objectives. These workshops serve as a vital tool to realign everyone’s focus on the overarching goals, ensuring a cohesive and comprehensive approach to problem-solving.

## Don’t Be Afraid To Experiment!

If you are tackling a gnarly issue or trying to untangle a business problem, a workshop might be the answer you’re looking for. While they seem intimidating at first, the benefits of an effective workshop far outweigh the complexities–just follow the rules we’ve outlined, and you’ll be halfway through!

Of course, if you’re an e-commerce brand and would like some help from experienced facilitators who can challenge your assumptions and contribute with their own insights, [feel free to reach out!](https://nebulab.com/contact-us) We’re always down for a good workshop.


Using Workshops to Navigate Complexity and Build Alignment

In our [previous article about cross-cultural design](https://nebulab.com/blog/cross-cultural-ecommerce-design), we delved into the intricacies of crafting online shopping experiences that resonate with diverse cultural backgrounds. We explored how Cross-Cultural Design can be the beacon that guides brands through the complexities of global expansion, emphasizing that a one-size-fits-all approach is rarely practical.

This time, we'd like to focus on a particular design trend that originated in the East and is gaining traction worldwide in specific market segments.

Characterized by busy interfaces and seemingly chaotic information taxonomies, this model stands in stark contrast to the more streamlined, search-centric user experiences we’re used to. Browsing for products is an adventure in and of itself: the shopping journey is akin to a digital bazaar, buzzing with energy, and each click leads to unexpected finds.

This trend has a name—it’s called *shoppertainment*—and it’s being popularized in the West by Chinese e-commerce marketplaces such as Shein and Temu.

Today, we’ll look at what shoppertainment is exactly, why it works so well, and what lessons we can learn from its most prominent adopters.

## How Shein and Temu Drive Customer Engagement through Shoppertainment
Temu, pronounced “tee-moo,” is an online superstore for virtually everything—from home goods to apparel to electronics—that made its Super Bowl debut in 2023.

Temu encourages consumers to “shop like a billionaire” and offers products at surprisingly low prices. It has quickly become [the most downloaded app](https://www.statista.com/statistics/1417955/most-downloaded-marketplace-apps-worldwide/), surpassing rivals Amazon and Walmart, not just in the United States but in the entire world.

With low prices and cluttered design, the personalized and gamified shopping experience Temu offers has drawn comparisons to Shein, [the Chinese fast fashion upstart](http://www.cnn.com/2021/08/14/business/shein-china-fast-fashion-intl-hnk/index.html) that also offers a wide selection of inexpensive clothing and home goods and has made significant inroads into several markets, including Europe and the United States.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/05fe639fe020903aa95fffd22a520ba6aaa28a06-1600x1052.jpg?fit=clip" alt="Shein Influencer on Youtube">
</figure>

Shein and Temu have both burst onto the scene in an online-first, fast-moving world. Through social media, influencer partnerships, live-streaming events, and a hefty reliance on performance marketing, they've created a strong brand presence that resonates with their target audience, often overshadowing the more sober, utilitarian approach of marketplaces like Amazon and Walmart.

When exploring the user experience design of platforms like Shein and Temu, it becomes evident that they foster an overwhelming sensory experience.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/77d823a005f01064ebcf0d5aadc49f0a4ea92f62-1600x1052.jpg?fit=clip" alt="Temu user experience">
</figure>

The interfaces of these platforms are a collage of vibrant colors, animated elements, and interactive features that aim to captivate and retain user attention. It's a digital landscape that's always in motion, with pop-ups, limited-time offers, and an endless stream of personalized recommendations designed to evoke the same excitement and urgency one might feel in a bustling street market.

Compare this with Amazon's more conservative approach, where functionality and efficiency are the cornerstones. Amazon's clean and practical design focuses on the ease of finding products through a logical and orderly user interface.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/3130810a416d7ba2c3239d26b5bdf116d0b43d4c-1600x1052.jpg?fit=clip" alt="Amazon browsing experience">
</figure>

These differences mirror broader cultural preferences that Temu and Shein lean heavily into and have managed to “export” outside their original cultural context.

## High-Context vs. Low-Context Cultures and their Impact on Design
In [high-context](https://en.wikipedia.org/wiki/High-context_and_low-context_cultures) Eastern cultures, where communication is often layered and nuanced, the sensory-rich UX design of Shein and Temu does not overwhelm but rather speaks a familiar language.

Furthermore, the digital journey took a mobile-first trajectory in the East, with the majority of the population experiencing the internet for the first time through the screens of their phones rather than desktop computers. This has profoundly influenced how online services, including e-commerce, have evolved in these regions.

Let’s think about Alipay and WeChat, platforms offering a comprehensive range of services from bill payments and banking management to taxi bookings and shopping. For super app users, the process of purchasing a luxury handbag within the same platform used for everyday tasks like paying utility bills is seamlessly integrated, reducing cognitive dissonance.

Conversely, in the more conservative and [low-context](https://en.wikipedia.org/wiki/High-context_and_low-context_cultures) West, Amazon's streamlined approach aligns more closely with communication preferences. The marketplace's structure and navigation are built for efficiency, offering a controlled space that prioritizes the straightforward discovery and purchase of products. Amazon's interface is a testament to the low-context communication prevalent in Western culture, where explicit messages win the day.

And yet, despite the cultural nuances, shoppertainment-centric platforms like Temu and Shein continue to gain traction in the West. What gives?

## The Appeal of Shoppertainment Across Cultures and Generations
As mentioned earlier, Temu and Shein embrace the delight of discovering treasures in a bustling marketplace. The success of these platforms lies in their mastery of discovery-based commerce. They blend AI with an understanding of user behavior to create a personalized and gamified shopping environment. Influencers, social proof, and live-streaming events further enrich this landscape, transforming the act of purchasing into an engaging and social event that feeds on the innate human love for exploration and deals.

Interestingly, this “shoppertainment" model resonates particularly well with Western Gen Z consumers, who are more adaptable to innovative, if less polished, user interfaces. Their shopping habits are motivated by value and the excitement of discovery rather than the aesthetics of the shopping platform. The loud and lively [Y2K stylings](https://www.pcmag.com/encyclopedia/term/y2k-fashion#:~:text=The%20technology%2C%20styles%2C%20dress%20and,Y2K%20problem%20and%20Y2K%20anxiety), playful interactions, and immersive content that dominate these sites speak the language of a generation that craves authenticity and spontaneity over polish and predictability.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/e1c699b758b05bdb646829f956b0ea868f307157-1600x1052.jpg?fit=clip" alt="Shoppertainment and Gen Z">
</figure>

Temu and Shein continue to rise in popularity, and not just with Gen Z. There’s another significant factor contributing to this phenomenon.

While Gen Z may be at the forefront of embracing energetic and interactive digital storefronts, the economic draw of these platforms speaks to the universal appeal of consumerism. Older generations, too, find the cost savings compelling enough to venture into these more animated shopping environments, suggesting that the desire for value can sometimes supersede preferences for a more traditional and subdued browsing experience.

As such, Shein and Temu have tapped into a powerful vein within the consumer market, demonstrating that while the 'shoppertainment' model might be vital to capturing the hearts of younger users, the fundamental drive to consume at the best possible price is a widespread motivator that crosses generational and cultural boundaries.

## Is Global E-Commerce Moving Toward Shoppertainment?
Temu and Shein have not just pioneered the 'shoppertainment' model; they've excelled in it, capturing the hearts of a broad audience with their gamified, discovery-driven approach to commerce. Their success lies beyond competitive pricing or extensive inventories, and it’s rooted in a shopping experience that equally prioritizes entertainment and acquisition. 

Looking ahead, the trajectory of e-commerce design might be steering towards a hybrid model. Incorporating personalized and interactive elements typical of Eastern consumer experiences without compromising the organized simplicity that users appreciate in the West will be critical to the continued success of our domestic marketplaces.

As such, the next challenge in e-commerce design will be to create experiences that resonate not just with a medley of cultural preferences but also with the varied tastes of an international, multi-generational audience.

If you have any questions about shoppertainment or want to understand which principles you can apply to your brand, [feel free to reach out](https://nebulab.com/contact-us)–we’d love to chat!

East, Meet West: The Rise of Shoppertainment in E-Commerce

Picture this: You run an eCommerce store, and business is booming in your home country. Feeling confident, you decide to expand into new markets. You translate your website into a few languages, but something's amiss. Your sales aren't hitting the expected numbers, and customers seem less engaged. What went wrong?

This is where Cross-Cultural Design comes to the rescue. Cross-Cultural Design (CCD) recognizes that every culture is unique and influenced by its values, traditions, and preferences. Ignoring these cultural nuances can lead to missteps, missed opportunities, and the alienation of potential customers.

In this article, we'll take you on a laid-back journey through the exciting world of CCD, explaining why it's a game-changer and how to navigate it effortlessly.

## The Principles of Cross-Cultural Design

Thinking about how cultural differences can influence users' needs and expectations isn’t an easy task, and we at Nebulab know it very well: we’re not only fully distributed, but we also work with brands from all over the world. Local preferences, navigation, and information hierarchy are just some of the aspects that can be influenced by cultural, behavioral, and economic elements.

In theory, User Research should help designers understand what their audience expects from digital interactions. Unfortunately, most behavioral research studies–which User Research practitioners take a lot of inspiration from–[are based on Western subjects](https://www.youtube.com/watch?v=Ho6OlPrD7sA)). This leads to the majority of design and user experience benchmarks being Western-centric, which creates obvious problems for teams that are designing for a non-Western audience.

In light of these challenges, broadening our perspectives becomes even more difficult: without reliable data and benchmarks, how can designers operate effectively without sacrificing speed?

That’s where Cross-Cultural Design comes to the rescue: rather than providing a set of steps to follow, it offers a set of principles that designers should keep in mind when operating outside their zone of “cultural comfort.” These principles will guide you to approach your work differently, which, in turn, will help you make better choices for your design, content, and technical strategy:

* **Embrace Cultural Immersion**: Dive into the culture you're designing for, immerse yourself in its nuances, and understand its values, traditions, and aesthetics. This deep understanding will help you create designs that resonate with the local audience.
* **Research Creative Communities**: Explore the creative communities within the culture. This involves understanding how artists, designers, and local creators express cultural identity. Drawing inspiration from these communities can enrich your design.
* **Work with Experts**: Collaborate with experts or individuals with in-depth knowledge of the culture. Their insights can provide invaluable guidance and ensure your design is culturally sensitive and authentic.
* **Question Assumptions**: Challenge assumptions and preconceptions about the culture. Be open to reevaluating your design choices based on real-world insights and user feedback rather than relying on stereotypes or biases.
* **Prioritize Flexibility**: Design with flexibility in mind. Recognize that cultures evolve, and your design should adapt to changing norms and preferences. A flexible design can better withstand the test of time and evolving cultural trends.

Now that we've explored these guiding principles, let's dive into two crucial concepts closely related to cross-cultural design: internationalization and localization.

## Internationalization and Localization: You Need Both!

The most fundamental challenge teams face when working on a cross-cultural project is ensuring the content, branding, and design are flexible enough to accommodate multiple languages, nationalities, and cultures. This process is called _internationalization_ (often abbreviated as _i18n_). **Internationalization involves creating digital experiences that work across cultures.**

On the other hand, **localization (_l10n_) involves tailoring a product to a specific culture.** Localization encompasses modifying UIs, adjusting layouts and styles, revising content and language, and tailoring and enhancing the user experience to suit the needs of the particular audience you’re designing for.

In other words, while internationalization is more about having a framework in place to adapt your product to a global audience, localization is about doing the actual work of adapting your product for each audience you want to serve.

Because internationalization mainly falls on the shoulders of your engineering team, we won’t focus on it in this article. Different eCommerce platforms and software libraries have different internationalization capabilities–make sure your engineering team is aware of any cross-cultural requirements and uses that information to inform their technical choices.

Instead, let’s explore the most common aspects that you need to consider when _localizing_ your design systems and digital experiences, particularly when it comes to eCommerce.

### Names and Addresses

It's essential to understand that cultural differences extend to the most basic elements of your user experience, such as how names or addresses should be collected and formatted.

For example, when we designed the checkout form for a Pakistani marketplace, we learned that Pakistani individuals will often have a first name, a middle name (which is typically their father's name), and a last name (family name or surname). With that requirement in mind, we decided to scrap the “First name” and “Last name” fields, typical of Western cultures, in favor of a single “Your name” field instead.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/3cc7341fef23a9a7996314c04bb0f694078be97b-1600x1052.jpg?fit=clip" alt="Unified field for first, middle and last names">
</figure> 

The same applies to addresses: in the form below, you might have noticed that there is no ZIP Code field–that’s because there are no ZIP codes in Pakistan. For our client [Framework](https://frame.work/), on the other hand, we’ve had to adapt the ZIP code field to allow both 3+2 and 3+3 codes in Taiwan.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/9ba2719bc3b73d7a9af55685588fbde123c4fbf8-1600x1052.jpg?fit=clip" alt="Framework's shipping address form for Taiwan">
  <figcaption>Taiwan’s introduced 3+3 ZIP codes in 2020 to improve mail sorting efficiency.</figcaption>
</figure>


### Text Direction

One of the most significant layout challenges encountered while localizing a South Eastern client’s eCommerce experience was supporting right-to-left (RTL) text in Lebanon.

That kind of change doesn’t just involve the actual text but also requires shifting the overall content and “mirroring” certain UI elements:

* **Headers, labels, and text should be oriented from right to left**. In eCommerce, that means displaying the brand’s logo on the right and the cart icon on the left.
* **Navigation buttons** must be mirrored, but icons that do not convey direction should remain unchanged.
* **Checkboxes** should be positioned to the right of their corresponding label.
* **Progress bars** should fill in a right-to-left direction.

Later in this article, we will explore tools to assist designers in this process.

### Linguistic Nuances

Very often, translating your UI and content is just the first step. It’s crucial to remember that each language has its quirks and nuances.

A common problem is that UI elements that look good in English might not be suitable for other languages. As an example, the German language allows stringing together multiple nouns to express complex concepts, which leads to some very long words that cannot be readily displayed in a mobile button.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/0e17cec623f050d16c9a7d4dc23019effd576e6c-1600x1052.jpg?fit=clip" alt="German vs. English UI in Framework">
</figure>

Another consideration is that the formatting of numbers, phone numbers, and currencies varies in each language. Using the same phone number or currency format across different languages is bound to cause confusion and friction for the user.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/b949ccdab489f172ff0e28a913d61c54d49da452-1600x1052.jpg?fit=clip" alt="Framework's checkout flow">
</figure>

### Payment Methods

Credit card usage is widespread in Western countries, while digital wallets and cash-on-delivery are preferred in many Asian markets. Adapting payment options to local preferences can dramatically enhance the customer experience and your conversion rates!

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/b8e24cd97481e4b71bb924ac1b5019328afb9c57-1600x1052.jpg?fit=clip" alt="OLX Mall's payment method selector">
  <figcaption>In some countries, cultural, historical, and socio-economic factors led to a deep-rooted preference for cash payments, even in online transactions.</figcaption>
</figure>

### Sign-In Preferences

Even something as familiar as the sign-in process can vary across cultures. In Western markets, users typically register for websites or online services using their email addresses. However, in Eastern countries, most users prefer to use their phone number.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/2a7306fd9abf204f991c15a7cdfab56224db629c-1600x1052.jpg?fit=clip" alt="Sign-in modal that supports phone numbers">
  <figcaption>In many Eastern countries, phone numbers, not emails, are the preferred method identification for creating online accounts.</figcaption>
</figure>

### Social Proof

In the world of eCommerce, trust is the cornerstone of successful transactions. Yet, how trust is built and perceived can vary significantly across cultures: some cultures prioritize the prominent display of security badges for reassurance, while others emphasize customer reviews and testimonials to instill trust in a website.

Understanding these cultural nuances is pivotal in crafting an effective eCommerce strategy that resonates with diverse audiences worldwide.

<figure>
  <img src="https://cdn.sanity.io/images/kqgmf0g2/production/ae4f65150f404d46b77a0fd1f3f6f6ea2d4ef6db-1600x1052.jpg?fit=clip" alt="Shop Safely badge in OLX Mall's checkout flow">
  <figcaption>In OLX Mall, we displayed a “Shop Safely” badge through the entire checkout flow.</figcaption>
</figure>

### We’re Not Even Done

If that wasn’t enough, here are a few more aspects you should consider when designing eCommerce experiences for a global audience:

* **Information Density:** Cultural differences can affect how users expect information to be organized. In some cultures, users may love maximalism and appreciate detailed product descriptions, rich user interfaces, and bright colors, while in others, a more minimalist approach might be preferable.
* **Taxation:** How you apply taxes is dictated by regulatory requirements, but different cultures also have different norms for where and when taxes should be displayed. For specific audiences, showing tax amounts in the wrong place or at the wrong time can increase friction and cart abandonment rates.
* **Imagery:** When picking and displaying images, it’s essential to be mindful of each culture’s sensitivities. You also want to be aware of home and mobile internet speeds in the countries you’re serving: serving a 5MB product image to someone on a 3G connection might not be the best idea!

It would be hard–if not impossible–to provide a comprehensive list of all the elements you should pay attention to. Instead, we recommend constantly referring to the principles of Cross-Cultural Design and using them to inform your day-to-day decisions.

## Sharpening Your Toolkit for Global Design

With localization becoming increasingly important, all the most popular design tools support non-Latin languages and offer features that help in designing for cross-cultural projects.

### Use the Right Figma Plugins

Figma's support for RTL languages is relatively new, having been available for about two years. To change the default [text direction](https://help.figma.com/hc/en-us/articles/4972283635863), select the main menu and go to **Text > Text direction**. Then, when you use the Text tool, the text direction will be set automatically.

There are also several plugins available that let you add your translations quickly and easily. Our favorite ones are:

* [Translator](https://www.figma.com/community/plugin/743218037112142643/translator), which boasts support for 130 languages and translates entire pages very quickly, making it an excellent choice for a quick preview of your layouts in various languages.
* [Cube Translation](https://www.figma.com/community/plugin/1205127328344023071/cube-translator), which uses AI to enhance translation accuracy and provides more robust tooling for real-time collaboration and content synchronization.

As always, your mileage may vary, so we encourage you to experiment with a few different plugins and pick the one most suited for your use case!

### Choose Multilingual Fonts

Selecting the appropriate font for an international project can be a challenging task. It's important to note that not all web fonts support multiple languages, and in some cases, you might encounter unreadable rectangular symbols (referred to as "Tofu").

Multilingual fonts are specifically crafted to solve this problem and accommodate various languages. The most comprehensive open-source, multilingual font family is [Noto](https://fonts.google.com/noto) (its name stands for “no tofu”), and it offers support for more than 1,000 languages.

If you want something more unique, [Google Fonts](https://fonts.google.com) provides a variety of fonts that are either multilingual or designed for specific languages–you can easily find them by applying the language filter to your search.

![Hello is written in different languages with Noto font](https://cdn.sanity.io/images/kqgmf0g2/production/f885f7fee73faf86874c394e4ff0d91df07f1849-1600x1052.jpg?fit=clip)

### Adapt Your Images

As we’ve mentioned, a critical aspect of images is cultural inclusivity. Culturally inclusive images are significant as they portray diversity and support representation. If you have a dedicated creative production team, work with them to develop assets that are suitable for your audience. If you don’t, websites like [Unsplash](https://unsplash.com/) have handy search tools to help you find what you need.

Once you have your images, you also want to ensure they’re optimized for your audience’s internet speeds. [TinyPNG](https://tinypng.com/) is often the go-to choice and, despite the name, also works with JPG and WebP files. We recommend pairing it with a robust CDN for optimizing images on the fly.


## Ready To Take On the World?

As explored in this article, culture plays an immense role in shaping how people interact with and perceive the digital shopping experiences we create for them. As you expand internationally, recognizing these influences is not just a consideration but the key to thriving in an increasingly diverse eCommerce ecosystem. Cross-Cultural Design can help you do just that.

If you have questions on how to make these principles work for your team, or need help designing for a global audience, [feel free to reach out](https://nebulab.com/contact-us)–we’d love to chat!

Expanding Your Brand Globally With Cross-Cultural Design

Here at Nebulab, we’re privileged to work with tens of brands across different categories, business models, team compositions, and revenue stages, helping them shape, launch, and refine their eCommerce experiences. Some of these brands started with us, while others used to work with different agencies and told us about their experience.

While every agency has its own culture and way of doing things, we’ve identified a few traits that separate successful brand-agency collaborations from the rest. These are not defined processes, but rather a philosophy for working together.

In today’s article, we have distilled this philosophy into five fundamental principles. When implemented, we’ve found that these principles consistently lead to dramatic increases in agency productivity and effectiveness.

If you already have an agency and would like to take your collaboration to the next level, or are looking for an agency and unsure how to evaluate their work methodology, you should dive right in!


## 1. Promote Knowledge Sharing

Many executives provide context to their agency on an as-needed basis: burned by previous experiences or just strapped with time, they create a structure where communication only flows in one direction, and the agency only knows what they absolutely need to do their job.

While this might get you the short-term results you’re looking for, it also means you’re missing out on _a lot_ of value your agency could bring to the table.

Pretty much all eCommerce agencies are verticalized–that means they only work in the eCommerce industry. As a result, they accumulate valuable expertise about industry trends, baseline performance, and best practices, not to mention the networks that they often manage to build up over time.

**If your relationship with your agency resembles an assembly line, it’s very unlikely you will ever benefit from any of their organizational knowledge.**

Instead, aim to remove all communication and knowledge barriers between your team and your agency. Give them free access to your team, and expose them to as many ceremonies and artifacts as possible–all hands, cross-functional meetings, strategy documents, and anything else that might be useful.

Once you do that, you’ll be surprised at all the different ways your agency can help you.

**Recommended read:** [Sense and Respond](https://www.amazon.com/Sense-Respond-Successful-Organizations-Continuously/dp/1633691888/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=1693399466&sr=8-4)


## 2. Demand Extreme Ownership

Here’s a controversial take: dedicated QA teams are a waste of time and money–at least in the way most brands structure them. If everything your agency does needs to pass a QA check, you’re doing it wrong.

This doesn’t just apply to QA but to any other areas where your agency needs “gatekeepers” or handholding. Instead, **you should aim for a structure where your eCommerce agency is responsible for all stages of execution:**

* Your agency should be responsible for contributing–as much as possible–to the product roadmap, based on their knowledge of your brand.
* Your agency should be responsible for refining your requirements and uncovering edge cases, problems, and needs you might have missed.
* Your agency should be responsible for QA’ing their own work, releasing it, and ensuring it’s working as expected once it’s live.
* Your agency should be responsible for proactively diagnosing and fixing the problem when something goes sideways—as it inevitably will.

If you’re reading this list and thinking, “My agency would never be able to do that,” there’s a fundamental lack of trust that you need to resolve. Perhaps they don’t have the skillset, or you tried giving them more freedom, and they failed. Talk to them openly about what you’re trying to achieve and see if the situation improves.

**Recommended read:** [Turn The Ship Around](https://www.amazon.com/Turn-Ship-Around-Building-Breaking/dp/0241250943/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1693407060&sr=8-1)


## 3. Think in Products, Not in Projects

A structured product management practice is what separates the brands that aimlessly wander from project to project and the brands that are intentionally pursuing a business strategy with their eCommerce website.

Unfortunately, many brands confuse _product_ management–the practice of collecting and leveraging quantitative and qualitative data to inform your product roadmap–with _project_ management–the practice of establishing and following a structured process in the execution of said product roadmap. Let's put it this way:

* Doing product management without project management means moving chaotically in the *right* direction.
* Doing project management without product management means moving meticulously in the *wrong* direction.

A good place to start is how you frame problems and validate solutions: **rather than just writing down business requirements, use quantitative and qualitative data to explain the business need driving a particular initiative.** Then, once a solution is implemented, use data to validate the impact of the solution.

Obviously, there’s much more to product management than just leveraging data: a good product manager is a master storyteller and can craft compelling narratives for why your brand should head in a particular direction, collaborating with different stakeholders and rallying your whole team behind a shared vision.

In the past, we have written extensively about the value of product management and how to establish a product management practice in your eCommerce team, so feel free to check out our previous articles [here](https://nebulab.com/blog/ecommerce-product-management) and [here](https://nebulab.com/blog/product-led-ecommerce-growth).

**Recommended read:** [Escaping the Build Trap](https://www.amazon.com/Escaping-Build-Trap-Effective-Management/dp/149197379X/ref=sr_1_1?keywords=escaping+the+build+trap&qid=1693410820&sprefix=escaping+the+build+trap%2Caps%2C212&sr=8-1)


## 4. Improve Continuously and Systemically

You and your eCommerce agency should be on a path of continuous, systemic improvement of your baseline performance. Rather than shooting for the stars only when the situation requires it and then falling back down to your usual standards, **you should constantly reassess your work together to understand how to take things to the next level.**

If you’re unsure how to do this effectively, try running a retrospective. In a retrospective, all team members can bring and discuss their feedback in a blame-free environment, with the only goal of improving the team’s performance. Retrospectives are most often used by software development teams, but they are a generic tool that can be applied to pretty much any business scenario.

Retrospectives allow you to improve continuously, but you should also ensure you’re improving systemically. By that, we mean that you should strive to maximize the impact of any work you do by considering how the work will affect different areas of your business, now and in the future.

A prime example that we like to use is building a design system for your brand. A design system will allow you to dramatically increase your iteration speed in the long term: you’ll be able to build more in a shorter timespan and reduce the amount of decision-making needed during the design process.

Unfortunately, design systems never seem important in the short term: **you need to make a conscious effort and invest a bit of your time in your future needs**–in a way that’s compatible with your immediate goals, of course.

**Recommended read:** [The Goal](http://amazon.com/Goal-Process-Ongoing-Improvement/dp/0884271951/ref=sr_1_1?crid=291LJ6ND5CVPB&keywords=the+goal&qid=1693411801&sprefix=the+goal%2Caps%2C305&sr=8-1)


## 5. Do What’s Right, Not What’s Popular

The relatively recent commoditization of eCommerce infrastructure is fantastic news for brands: you can now build rich eCommerce experiences with a fraction of the effort that was previously required. Sign up for any modern eCommerce platform, and the amount of functionality available out of the box is mind-boggling.

However, this comes with a side effect: **many brands have stopped thinking about how to properly align their [eCommerce stack](https://nebulab.com/blog/ecommerce-tech-stack) with what their business really needs.** Instead, they just pick whatever’s most popular and stick to that. Unfortunately, agencies are not immune to this pattern–especially those that lack experience or strong R&D capabilities.

The result is a sea of online stores that all look and act the same and a borderline irrational fear of doing anything that deviates from the status quo.

**Best practices should be considered a starting point that you can build upon, not an absolute constraint.** Whenever you’re making a choice, it is your agency’s responsibility to present all your options and then determine what resonates the most with your market, vision, and business requirements.

Don’t get us wrong: there _is_ a cost for deviating from the most traveled road, and you need to be able to quantify it. It all boils down to whether the additional benefits justify it.

**Recommended read:** [The Lean Startup](https://www.amazon.com/Lean-Startup-Entrepreneurs-Continuous-Innovation/dp/0670921602/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=1693414149&sr=8-1)


## Change Is Hard, Not Impossible

As you’ve seen by now, none of the principles we’ve just outlined are quick wins–in fact, many of them require a significant mindset shift, and we can’t promise that they will deliver results overnight.

What we _can_ promise is that **this way of working is infinitely more powerful than more transactional agency relationships**, where you’re just paying money in exchange for pixels or code.

We’ve also seen first-hand that this kind of change can be implemented–you just need to be patient and accept that there will be slip-ups in the process. When they happen, treat them as your opportunity to practice continuous improvement!

5 Principles for Doing Great Work with Your eCommerce Agency

When it comes to customer loyalty in DTC, two strategies dominate the industry: subscription business models, where a consumer commits to a recurring payment, typically in exchange for a discount, and loyalty programs, where a consumer receives rewards–most often in the form of cashback–in exchange for performing specific actions, such as completing an order, referring a friend, or talking about a brand on social media.

These models, which both have excellent reasons to exist, are often implemented by brand executives desperately looking for a quick win: CPG brand looking for more predictable revenue? Launch a couple of subscription plans and profit. Diverse catalog that can support more frequent or larger purchases? Roll out a cashback scheme and live happily ever after.

And while it all makes sense in theory, the unfortunate news is that it doesn’t quite work like that–not anymore, at least, and most certainly not for everyone. **Both subscriptions and loyalty programs come with two significant drawbacks**, which have gradually reduced their effectiveness over the last few years:

* **Transactionality.** A customer signing up for a subscription service or your loyalty program tells you very little about that customer’s affinity with your brand–it simply means that they saw an opportunity to save some money and took it. You are–almost literally–paying customers to shop with you. There’s little preventing customers from switching brands as soon as they find a better deal–**short-term incentives drive short-term behavior.**
* **Saturation.** If you’ve heard anything about “subscription fatigue,” you’ll know what we’re talking about. Consumers are tired of juggling multiple subscription boxes, and they are instead looking for ways to streamline and consolidate. And while loyalty programs are less susceptible to this–since they’re free to use most of the time–**the fact that every single brand has some form of loyalty program has essentially leveled the playing field.**

So, does that mean that customer loyalty is dead? Not quite–it’s just that you can’t stand out by doing the same things as everyone else. **In the DTC sea of sameness, there’s a massive opportunity for brands to break through the noise and generate organic stickiness,** but the strategies look a bit different than before and require much more intentionality.

Today, we want to tell you about one of these strategies: membership programs.

## What Exactly Is a Membership Program?

Membership programs are an established concept for large brands but are still relatively unexplored in the DTC world. In fact, many brands confuse membership programs with traditional loyalty programs because of their similarities, which contributes to the confusion.

**At its core, a membership program is a loyalty program on steroids.** It is usually sold as a digital subscription rather than being offered for free, and program members get access to various benefits. Some might be monetary rewards (e.g., discounts and cashback), but you’ll also find perks such as early access to new products, exclusive communities, members-only content, and free or discounted services.

If you go back to the two problems we’ve identified with subscription models and loyalty programs, you’ll see how memberships address both:

* **They eschew transactionality and pursue identity.** By going beyond monetary rewards, **memberships provide brands with an escape from transactionality.** A well-rounded membership program elevates brands, enabling them to become a customer’s reference point for running a given aspect of their lives.
* **They eschew saturation and pursue exclusivity.** I can sign up for a thousand free loyalty programs and continue to shop from a thousand different brands, but I can only sign up for so many paid membership programs. No matter how insignificant, **the membership fee forces customers to make a choice and stick to it.**

The mix of identity and exclusivity makes for a robust customer loyalty flywheel: the initial cost of becoming a member motivates me to use my membership. As I use my membership–and barring any breaches of consumer trust–I identify myself more and more with the brand, which increases the perceived value of the brand.

All of this might sound like theoretical mumbo-jumbo, so let’s look at an example.

### How Petco Makes $120M/Year from Memberships

Petco offers a membership program called Petco Vital Care comprised of two tiers: a free tier which is a run-of-the-mill loyalty program, and a paid tier called Vital Care Premier. For $19.99/month, members can benefit from extra discounts and services such as pet sitting, grooming, and vet visits for their dogs.

The results are astonishing: **in Q4 2022, Petco Vital Care counted 500,000 paid members–about $120M/year in incremental revenue for Petco.** That number, by the way, is just the membership fee and doesn’t account for the fact that members have a lifetime value 3.6X higher than casual shoppers.

![](https://cdn.sanity.io/images/kqgmf0g2/production/efd6ac6c17c1fca084bac9df95a87b9a477b4eda-2560x2488.png?fit=clip)

Through Vital Care, Petco is not only diversifying their revenue streams but also creating a compelling unifying force for their products and services. If you’re an Amazon Prime customer, this concept shouldn’t be a surprise. **Just like Amazon wants to be your end-all solution for shopping, Petco wants to be your end-all solution for pet care.**

Of course, Petco is a publicly traded $6B/year retailer that operates thousands of stores across the US, and they have the economies of scale to offer their members an incredible level of convenience. Even for a relatively established DTC contender in their category, replicating Vital Care would be virtually impossible.

However, that doesn’t mean membership programs are inaccessible for small brands–they just need to be structured thoughtfully.

## How to Structure Your Membership Program

If we managed to convince you that rolling out a membership program is the right thing for your online store, awesome! But where do you start? In the following paragraphs, we’ll outline a five-step process you can follow to design, validate and roll out a membership program to your customer base.

### 1. Talk to Your Customers

Seriously, _do_ talk to them.

If you aren’t conducting regular interviews–[which you should](https://nebulab.com/blog/ecommerce-product-management), but just in case–f**ind 30-50 customers from different cohorts to understand whether they would have any use for a brand membership and what it might look like.** Ideally, you’re looking to answer as many as possible of the following questions:

* What problems are your customers solving with your product(s)?
* How do they currently perceive your brand? What do they love about it?
* What adjacent brands do they shop with regularly?
* What adjacent services do they consume regularly?
* Do they already have any memberships? What do they like/dislike about them?

![](https://cdn.sanity.io/images/kqgmf0g2/production/1a2947fe9354c18325c2bc8b9f25cb2d9d41d78c-1200x869.jpg?fit=clip)

Of course, you’ll want to adjust and enrich these based on which category you operate in. For example, if you sell workout apparel, where do your customers work out? If it’s at home, do they subscribe to a separate workout app to track their workouts? Do they also care about nutrition? If yes, where are they getting their educational content from?

**In addition to the interviews, you should look at analytics, primary and secondary competitors, and key market trends.** Your goal should be understanding how your brand fits into your customer’s day-to-day and whether there’s an opportunity to move into adjacent problem spaces.

As a final note, remember that **your membership will not appeal to all your customers–and it shouldn’t.** Memberships require customers to invest a significant amount of financial and social capital into your brand–as a result, they will only work for customers willing to take that leap of faith. Use this initial phase to understand what that ICP looks like, and double down on it when you do additional research about your membership program.

### 2. Design Your Member Benefits

Once you understand the opportunity space, you must decide what to offer as part of your membership. Generally, membership benefits can be put in one of five buckets:

* **Money:** this includes discounts, cashback, free shipping, birthday gifts, and any other monetary reward. These are things your customers could easily purchase themselves or find elsewhere, which makes them more immediate to understand but less likely to generate long-term loyalty.
* **Access:** very often, members have early access to new product releases, or exclusive access to certain pieces of merchandise. Even if you don’t have a large product catalog, you can get creative with partnerships, digital products, and other goodies.
* **Content:** given how valuable good content is, it might seem ridiculous to gate it. But making certain content only available to your members is a fantastic way to foster a sense of exclusivity and identity, as long as you have a unique or particularly valuable perspective to offer.
* **Services:** when you look at Petco Vital Care, the non-monetary part of their paid membership tier is comprised almost exclusively of services. Petco delivers most of their member services in-house, but you can always partner with a third-party service provider.
* **Community:** network effects make communities incredibly sticky. In addition to being an incredible perk, brand communities can become a solid sounding board for your new product ideas and a formidable source of organic marketing.

When it comes to your member benefits, you must balance putting together a package compelling enough that customers will want to sign up, and keeping it small enough for your team to launch and sustain over the long run.

**If you’re just starting out, we recommend starting with monetary benefits (which can be implemented almost for free) and an additional category your members deeply care about.** Once you launch your program, you’ll have plenty of time to adjust and expand it.

### 3. Determine Your Pricing

At this point, you’re ready to start thinking about your membership’s pricing structure.

Our recommendation for most brands is to start with two tiers: a free tier, which is essentially just a traditional loyalty program, and a paid tier, which gives customers access to member perks. **You shouldn’t separate your loyalty and membership programs, as that would most likely confuse customers.**

![](https://cdn.sanity.io/images/kqgmf0g2/production/e90b647471606b469b4141a39710bec2d252defb-2880x2149.png?fit=clip)

As for the exact price point, this will vary greatly depending on your target market, product category, and member benefits. A helpful tool for determining a range of acceptable prices is the [Van Westendorp Price Sensitivity Meter](https://www.forbes.com/sites/rebeccasadwick/2020/06/22/how-to-price-products/) (PSM). With this model, you ask your potential member for questions:

* What price would be so low that you start to question the membership’s quality?
* At what price would the membership begin to seem a bargain?
* At what price would the membership begin to seem expensive?
* At what price would the membership be too expensive?

By plotting your answers, you can determine the range of prices your customers would be willing to pay for your membership.

Obviously, you should still validate whatever numbers you get to ensure they work for your business. This is also where it pays off to offer a membership that is more heavy on non-monetary rewards, as they will typically be less burdensome on your margins at scale.

### 4. Define a Go-to-Market Strategy

You know who you’re selling to, what you’re selling, and for how much. All that’s left to figure out at this point is _how_ you’re going to sell it–that is, your go-to-market strategy.

The first thing to keep in mind here is that **when it comes to memberships, paid social–and other paid channels in general– should be approached with caution:** unless you have an incredibly compelling offering, it is extremely unlikely you will be able to achieve a reasonable CAC. As we’ve mentioned before, selling a membership requires a degree of trust much higher than your typical eCommerce conversion.

As long as you collect the right zero-party and first-party data, you can easily use email and SMS marketing automation platforms to identify and reach potential members. Ideally, **you want to reach out as soon as a customer is identified as a potential fit for your membership program**–what this means exactly will depend on the ICP you’ve outlined in phase #1 and will vary over time.

As for your website, you should design thoughtful touchpoints that remind customers of the value of your membership and provide easy paths to conversion. For instance, if you’re offering free shipping as part of your membership, your checkout flow should clearly indicate that and allow customers to opt into the membership and benefit from the free shipping perk in one smooth click.

Finally, **referrals and gift memberships can be very powerful in driving organic customer acquisition, so you should at least experiment with them.** These channels allow you to bypass the consumer’s initial “trust gate,” leading to higher conversion rates.

### 5. Launch, Track, and Iterate

You’re all set! Now you just need to launch your membership.

Depending on your tech stack and how you’re structuring your program, you will likely need to use a few different tools. On Shopify, our favorite membership apps are [Conjured Memberships](https://apps.shopify.com/membership-program?locale=it)–a solid solution with very accessible pricing–and [Inveterate](https://www.inveterate.com/)–a more modern and flexible platform, well-suited for brands that need custom functionality or use a [headless architecture.](https://nebulab.com/blog/headless-commerce)

If you’re looking to break beyond the walls of your eCommerce site, [Circle](https://circle.so/) is a standalone platform for brands to launch their private communities. It’s an incredibly powerful option if you want to create a dedicated space for members-only content, discussions, and events, and it can easily drive the entire Community aspect of your membership program.

![](https://cdn.sanity.io/images/kqgmf0g2/production/6ef9d98a89f6a19f6faa7cc1bf1ae597a94b263b-2560x2488.png?fit=clip)

**Whatever tools you use, take the time to truly understand their potential and make them yours!** Memberships are only valuable when they deeply resonate with the brands that drive them and the consumers they serve. If you’re just going through the motions, your membership program will be short-lived.

After the launch, use member interviews and exploratory analytics to gauge the effectiveness of your program and adjust course accordingly. Most brands will want to track at least some of the following:

* How many customers are you converting into paid members?
* Are members using all the benefits in their membership? How much?
* What is the customer lifetime value and LTV:CAC ratio of members vs. non-members?
* What are your margins for members vs. non-members?
* What does retention look like for your membership program? Why do members cancel?

Feel free to enrich these as needed to drive your brand’s goals, **but never lose track of the basics:** maintaining a healthy foundation will give you the peace of mind you need to grow your membership program.

## Is It Time to Switch to Memberships?

Many brands have already started to roll out membership programs as part of their offering, and we’re excited to see this trend unfold over the following years: while subscription-based models and loyalty programs will never lose their place, they can rarely foster true customer loyalty.

As you’ve seen, the caveat is that a membership program requires more maintenance than other models, so you should ensure your team has the bandwidth to support it before venturing down this path.

If you’re wondering what a membership program can do for your brand or looking for help rolling out your program, don’t hesitate to reach out!


Why Memberships Are The Future of Customer Loyalty

If you operate a retail brand today, you should pursue an omnichannel marketing and distribution strategy. And if you’re pursuing an omnichannel strategy, you should at least consider launching a mobile application for your online business. The benefits of eCommerce mobile apps are very alluring:

* **They make it easier to identify return customers,** providing richer, deeper opportunities for personalizing the customer experience.
* **They allow you to send push notifications to your users.** That’s a real-time, high-engagement, fully-owned marketing channel–and it’s free, too.
* **They offer your customers a faster, more convenient online shopping experience,** making for higher conversion rates, better retention, and larger baskets.

However, mobile apps are not for all brands: depending on what type of app you want to build, the financial investment can be significant. T**he more you want your app to act as a customer acquisition driver, the more expensive it will be to build and operate.** And ironically, brands that need acquisition-focused apps are usually the ones with the least money to spend on them, which makes this a complex juggling act.

The goal of this guide is two-fold: we want to provide you with all the context you need to make this decision in the most informed and balanced way possible, and if you decide to move forward, we want to offer practical tips to design and build an eCommerce app that will delight your customers while pursuing your business goals.

## Transactional Apps Drive Lifetime Value

If we asked the average user to picture a mobile app for an eCommerce brand they like, they would probably copy-paste the brand’s online store into a native UI, ending up with a shopping app that simply serves as an additional sales channel. We typically refer to these as “transactional apps” because their only purpose is to facilitate transactions between a brand and their customers.

While there’s nothing wrong with transactional apps per se, you should know that this is not the only type of app you can build–although it’s the easiest. **Transactional apps are incredibly useful if you already have significant brand equity or a high repeat purchase rate and want to get more value from your existing customers.** By providing a better, more user-friendly shopping experience than your other channels and potentially your competitors, you can improve your conversion rate, average order value, and repeat purchase rate.

![](https://cdn.sanity.io/images/kqgmf0g2/production/635f4d681b5cbf832e452b6f69380fc936f3600d-2400x1500.png?fit=clip)

**What a transactional app can’t help you with is customer acquisition.** Anyone who shops through a transactional app should be considered a high-intent customer and would have likely shopped with you anyway, although their orders might have been a bit smaller or less frequent in other channels.

One of the most popular transactional apps is Nespresso’s mobile app: it allows you to place orders, manage your Nespresso subscription, and manage your Nespresso coffee machine, all without opening their website. The app does a great job of eliminating any friction in the shopping experience, increasing repeat purchase rate and average order value for all existing Nespresso customers.

## Experiential Apps Drive Customer Acquisition

We’ve seen that transactional apps boost your customer lifetime value, not your acquisition rates. Does that mean you shouldn’t build a mobile eCommerce app if you’re focused on customer acquisition? Not quite–it just means your goal should be to build an app that’s experiential rather than transactional.

Experiential apps take the concept of an eCommerce app a step further. Rather than simply facilitating a transaction your customers can already complete on your website, **experiential apps provide value in and of themselves.** This can come in the form of exclusive content, a community, or a tool/service that is relevant to your physical product(s). These apps effectively become part of your brand identity rather than being another sales channel.

**The idea behind experiential apps is to build brand awareness and capture low-intent customers** by providing them with free, immediate value, only nurturing and converting them at a later stage. It’s a much longer-term bet than launching a transactional app but it can also pay off huge dividends over time. Experiential mobile apps are one of many ways you can pursue a [Product-Led Growth strategy.](https://nebulab.com/blog/product-led-ecommerce-growth)

![](https://cdn.sanity.io/images/kqgmf0g2/production/68db8d648a056e09c99d04923a473428bdf01c76-2400x1500.png?fit=clip)

Note that **most experiential apps also offer transactional capabilities,** allowing you to kill two birds with one stone: high-intent customers can use your mobile shopping cart to buy from you, while low-intent shoppers can use the experiential features to explore your brand at their own pace–and eventually convert into paying customers.

Personalized vitamin brand [Care/of](https://www.takecareof.com/) recently released an app that is equal parts transactional and experiential: the app sends you reminders and allows you to track your vitamin intake, as well as keep track of your daily habits. By performing these actions, you earn points, which you can redeem for free rewards–the perfect entry point into Care/of’s world. At the same time, existing customers can use the app to manage their Care/of subscription.

## Greenfield Builds vs. App Builders

Once you have a clear idea of what kind of app you want to build, you need to decide how you want to build it. While your tech team or mobile app development agency might have strong opinions over which tech stack they want to use, it’s essential to be aware of the implications of your choices.

**Traditionally, mobile apps have been built from scratch,** using technologies such as Swift (which is specific to iOS) or React Native (which allows you to power cross-platform native apps with a single codebase).

**Building your app from scratch is basically the equivalent of writing your own checkout code,** and it has many of the same advantages and limitations. It gives you tremendous flexibility to build whatever app you have in mind–which is fantastic if you’re launching an experiential app–but it also requires a significant investment and technical know-how.

**A greenfield app will take anywhere between 8 and 12 weeks and cost you $50-100K,** depending on your agency/tech team composition. These apps also tend to be more expensive to operate and maintain over time.

![](https://cdn.sanity.io/images/kqgmf0g2/production/a796fd0d1992c28ec77d4059b627ec951d39201d-2560x1850.png?fit=clip)

**The alternative to a greenfield build is to use an app builder.** Over the last years, several startups have emerged that offer a much cheaper and quicker way to launch a mobile app than building it from scratch: you simply connect them to your Shopify store or other eCommerce platform, customize your app by using a drag-and-drop interface that allows you to reuse predefined templates, and click a button to have your app published in the Apple and Android app stores.

App builders are especially popular in the eCommerce domain, because the user experience of purchasing a product online tends to be very repeatable. **Launching an app with one of these tools can take as little as two weeks, and pricing is usually fairly accessible.** [Tapcart](https://www.tapcart.com/), for example, is the most popular app builder for Shopify and starts from $300/month.

However, these tools have a downside: because you need to operate within the constraints of your app builder, you are much more limited in terms of the functionality you can implement. **This makes app builders a terrible choice for experiential apps, where you want the app to stand out and capture your customers’ attention.**

## What Type of App Should You Build?

Ultimately, there’s no one-size-fits-all answer: whether to build a transactional or experiential app depends on your eCommerce store’s stage, customer profile, business model, tech savviness, and a thousand other factors that are pretty complex to account for.

In general, **if you want to drive customer acquisition and have the resources, you should go with an experiential app.** It’s your best shot at capturing customers that are interested in what you have to offer but might not be ready to shop with you just yet.

However, **if your primary goal is to create a low-friction sales channel for your mobile users, you should likely build a transactional app instead.** It will give you the best bang for your buck, increasing customer satisfaction, repeat purchase rate, and basket size.

## Tracking Your Mobile App’s Performance

What KPIs to track for your mobile app depends on the type of app you’re building: tracking the performance of an experiential app will look very different from monitoring the performance of a transactional app, since the goals are fundamentally different (acquiring customers vs. increasing LTV).

However, you should always track both product metrics and business metrics:

* **Product metrics** measure how well the app itself is performing. How many users are downloading your app? How often are they opening it? What’s the average session length? What are the biggest points of friction?
* **Business metrics** measure how well your app is moving the business forward. How many paying customers is your app generating? What’s the AOV of an app order vs. a mobile/desktop website order?

To answer these questions, you need to make sure your app is instrumented correctly to capture this data. While this will come for free with app builders, you’ll need to be much more intentional about analytics when building an app from scratch.

![](https://cdn.sanity.io/images/kqgmf0g2/production/58a36d4bfc3bc7ff9e4358948a51e89862292ef9-2970x1980.jpg?fit=clip)

Finally, a note of caution: especially when building a transactional app, **you should be mindful that mobile app customers are a unique segment,** and you can’t draw one-to-one comparisons with your general customer population.

For example, you might be tempted to compare your average in-app conversion rate to your average on-site conversion rate, but that’s a pretty useless insight: almost by definition, your mobile app users are much higher-intent than your website users since they went through the pain of finding and downloading your app. The fact that your app’s conversion rate is 2X your website’s conversion rate doesn’t really mean anything.

Ideally, **you want to compare metrics across customer segments that are as similar as possible** (e.g., highly-engaged customers that regularly shop online vs. in-app) to ensure you’re assessing your app’s performance fairly.


## Ready to Launch Your App?

We’ve just provided a high-level overview of what it takes to design and build a mobile app for your eCommerce business. As you’ve seen, it’s a project that can have incredible benefits but also requires a clear, upfront understanding of your motivations.

If you’re unsure whether a mobile app–or what kind of app–is right for you, we’re here for you! Feel free to reach out for a free consultation with our brand strategists, and we’ll help you make the best choice for your brand.

The Honest Guide to Mobile eCommerce Apps

The modern direct-to-consumer brand has potential access to a plethora of information about their customers: post-purchase surveys, CSAT scores, site analytics, [A/B testing](https://nebulab.com/blog/ecommerce-ab-testing), market research… Often, it can all be a bit too much, with brands not being sure how to use this information in a structured and strategic way to scale their business.

Luckily, that is precisely the problem product management was born to solve. Product management is the job of defining _what_ you should build, _how_ you should build it, and _when_ you should build it. It is a proven problem-solving methodology that allows you to collect and deploy information to work toward your business objectives.

Even though you might not have direct product management experience, you may already be doing some product management. For example, if you are looking at your conversion funnel analytics to understand where users are dropping from your checkout flow and then [running A/B tests](https://nebulab.com/blog/ecommerce-ab-testing) to determine how to improve your conversion rates, you’re doing product management.

In this article, we’ll try to provide you with a more structured approach that will allow you to elevate your product management skills, turning them into a repeatable workflow for identifying, prioritizing, and pursuing the most impactful goals for your brand. These are the same techniques used by behemoths such as [Zappos](https://www.zappos.com/) and [Warby Parker](https://www.warbyparker.com/) to achieve the impressive scale they’ve experienced over the last decade, so you’ll be in good company!

## Understanding and Applying Research Methodologies

At the core of product management lies product research, the practice of collecting data and insights that can inform which problems you should solve and how to solve them best.

Over their career, experienced product managers learn to master various research techniques. You might have heard about some of them–such as A/B testing, customer interviews, and surveys–while others might be more obscure–such as tree sorting, fake door tests, and contextual inquiry. You’re encouraged to do your own research (no pun intended!) and learn more about each technique.

For now, you should know that every research technique exists on two spectrums: quantitative or qualitative and generative or evaluative. Let’s see what that means!

### Quantitative vs. Qualitative Research

Quantitative research is used to collect numerical data, generally through automated techniques such as closed-ended surveys or product analytics. The data is then consolidated and interpreted to identify a problem or opportunity in front of your business.

For instance, if your checkout conversion rate is well below the average for your industry, that might be something you want to work on with your team.

However, the numbers alone might not always tell you exactly _why_ something is happening: your conversion rate might be low because your prices are too high or the user experience of your checkout flow is confusing. That’s where qualitative research comes in.

Qualitative research, on the other hand, is used to collect in-depth information, generally through techniques such as customer interviews or open-ended surveys. The information is then collected, parsed, and distilled by a human being into insights–tiny nuggets of information that have some practical implication for your business.

For instance, if you interview ten customers who dropped out of checkout, and seven of them mention that they weren’t sure when they would receive their order, you might conclude that customers find your order tracking process challenging to understand. You can then use this information when prioritizing your work to improve the conversion rate (more on this below).

Note that quantitative research doesn’t always have to come before qualitative research: you will find yourself going back and forth between the two depending on the problem you’re currently focusing on and how you’re approaching it.

### Generative vs. Evaluative Research

The examples we have made in the above paragraph are all about _generative_ research, which is done to identify a problem to solve or an opportunity to tackle. In generative research, your goal is to gain an intimate understanding of your market, customers, and product to understand _what_ you should build and _when_ you should build it.

The research doesn’t stop when you have identified a problem or an opportunity. In fact, that’s just half of the equation. The other half is about using product research to evaluate potential solutions to the situation in front of you. That’s where evaluative research comes in.

In evaluative research, you aim to understand _how_ to solve the problem or tackle the opportunity. This can be done with various techniques, some of which can be generative or evaluative depending on the context: for instance, usability testing can be performed to identify problems with your existing checkout flow, or it can be performed to validate the UX of your proposed redesign.

Mastering some generative and evaluative research techniques will help ensure your work is product-driven end-to-end. Many retailers let the data and insights guide their product roadmap but fail to validate their design solutions. This can lead to doing work that doesn’t move the needle or even moves it in the wrong direction.

### Establishing a Continuous Discovery Practice

While it’s tempting to do product research only when you run out of things to do, the best teams are running research systematically–a practice referred to as “continuous discovery.” Continuous discovery combines automated and manual work to ensure a stream of qualitative and quantitative insights flows into your brand.

There’s no one-size-fits-all approach to continuous discovery, but there are some techniques that we’ve seen work for the majority of eCommerce and direct-to-consumer brands:

* **Post-purchase surveys.** Every eCommerce business should be running post-purchase surveys. At a minimum, you want to ask customers how they found out about you, which will help enrich your attribution data, but you can also use these to collect feedback about other aspects of the customer experience.
* **On-site analytics.** Solid on-site analytics will help you collect valuable first-party data, which you can use to spot challenges and opportunities and validate the effectiveness of new features, products, or UX improvements. The trick is not to overdo it: otherwise, you risk drowning in a sea of metrics.
* **Business reports.** Your eCommerce platform should offer some out-of-the-box reporting that you can use to quickly answer critical business questions, such as where your customers are coming from or what products are driving the most sales. However, you shouldn’t be afraid of implementing custom reports as needed.
* **Continuous interviews.** We’ve left this for last, but it’s arguably the most crucial research technique in your tool belt. You should try interviewing at least two customers a week, asking a mix of generative and evaluative questions about whatever you’re currently working on.

As you’ve seen, the key is embedding little product research opportunities at critical moments of the customer journey so that you don’t have to think about them consciously. If you need more in-depth information about a specific aspect, you can still go out and execute a full-blown research project, but continuous discovery will provide you with a solid foundation to start.

## The 6-Step Process to Accomplish Anything

Now that you understand what product management is and how to conduct product research, you might wonder how to tie these techniques to your business goals in a structured, systematic way. That’s precisely where the Opportunity Solution Tree (OST) comes in.

The Opportunity Solution Tree is a visual framework that helps your team stay focused on the current business goal while also ensuring they’re exploring the entire problem space. Depending on what you’re doing, you can either see the whole picture at a glance or drill down into the nitty-gritty of each project. Furthermore, an OST is designed for continuous optimization and evolution, which makes it the perfect tool in environments where you want to move fast but with intentionality.

![](https://cdn.sanity.io/images/kqgmf0g2/production/f4efe697bad7b33a7525c24f001cf2936087db01-2056x3272.png?fit=clip)

Here’s how you build an OST:

1. **Start from the desired outcome.** This is usually informed by your overarching business strategy. For instance, an outcome might be “Lower the return rate for our online store to 20%.”
2. **Identify opportunities to achieve the outcome.** You will typically do this through generative research. For instance, you might interview ten customers who have returned a product in the last month and find that they got the wrong size. You would then create an opportunity labeled “Customers purchase the wrong product size.”
3. **Brainstorm solutions.** In this phase, involve as many relevant stakeholders as possible: your marketing team, your development team, etc. Use research insights and your team members’ intuition to develop ideas for tackling each opportunity. Ideally, you refine the solutions to 1-3 per opportunity to keep the process manageable.
4. **Design experiments.** Each solution should come with an experiment, which ensures the solution is actually going to tackle the opportunity. This is a crucial step: by adopting a data-informed approach, you’ll eliminate your biases, assumption, and emotional attachment to specific ideas. In some cases, you might want to run multiple experiments to evaluate different aspects of a solution.
5. **Evaluate your solutions.** The next step is to run the experiments you’ve designed to test the validity of your solutions: are they creating the impact you expected? Can you see any side effects to address before moving forward?
6. **Implement the winners.** At this point, you should have a list of solutions your team can implement to achieve the desired outcome!

Here’s a bonus tip: in the OST included above, you might notice that we have broken down the main “Customers get the wrong size” opportunity into two sub-opportunities: “Customers get the wrong size when buying for themselves” and “Customers get the wrong size when buying for others.” This is a common and encouraged practice when designing an OST: you should split your opportunities into the smallest possible size while ensuring that your opportunities are Mutually Exclusive, Collectively Exhaustive (MECE). This will help you work in small chunks, which makes the process faster and more efficient.

The OST is a dead-simple yet incredibly powerful tool that can help you pursue virtually any business goal when appropriately followed. It might not be obvious, but OSTs aren’t limited to your eCommerce site: you can apply this process to improve other areas of your brand, such as fulfillment or customer service. The value of this technique lies in the fact that it forces you to structure your work and follow facts, not intuitions.

## Good Product Management Takes Practice

Most eCommerce companies are skeptical of product management at first. When you’re a small startup, every bit of process you add to your day-to-day seems like a luxury you cannot afford.

And yet, we’ve seen time and again that the brands with a clear vision and strong product management fundamentals to execute it are the ones who thrive: they exhibit lower customer acquisition costs, higher retention rates, and higher average order values. Most importantly, they move more quickly and intentionally than their competition.

You might be very excited to go out and try the new techniques you’ve just learned, and we very much encourage you to do so. However, remember that we’ve barely scratched the surface of product management in this article: while the fundamental principles are relatively simple, product management remains a vast discipline.

We have not said anything about when to use which research technique, how to develop an overarching product strategy rather than simply tackling one outcome at a time, what systems and tools are best to collect the outcomes of your research, and many other aspects that take years of practice to master fully.

If you’re curious to try product management or already have a product-driven approach and want to take it to the next level, we’re happy to help!

Supercharge Your DTC Growth with Product Management

With the rising cost of advertising and inflationary pressures making it hard to acquire, activate, and retain customers profitably, direct-to-consumer (DTC) brands are increasingly looking for ways to lower operating costs and scale more efficiently. This often takes the form of wholesale partnerships or marketplace expansions, which allow brands to tap into existing audiences and offload last-mile distribution.

We strongly believe a wholesale motion should be a crucial part of any modern brand’s go-to-market strategy. However, the DTC channel offers several opportunities that would allow brands to disengage from performance marketing as their only methodology of customer acquisition. At the same time, DTC brands can benefit from unique advantages, such as end-to-end control over the customer experience and direct access to zero- and first-party data.

This article will explore product-led growth, a methodology adopted by startups such as Dropbox, Slack, and Zoom to achieve low-cost, exponential growth. We’ll unpack the fundamentals and benefits of product-led growth, how it can be applied to eCommerce and DTC, and how you can take your first steps toward establishing a product-led growth strategy for your DTC presence.

## What Is Product-Led Growth?

Product-led growth (PLG) is a business methodology originally popularized by [OpenView](https://openviewpartners.com/) in 2016. It consists of techniques that allow you to shift away from spending marketing dollars to capture and retain customers, letting your product do the selling instead.

In contrast to more traditional approaches, such as market-led and sales-led growth models, companies that adopt product-led growth put their product experience at the center of the brand journey and take a product-first approach to scale their revenue and customer base.

They also automate secondary functions such as customer success and invest heavily in self-serve onboarding experiences, which allows potential customers to experience and play with the product before committing to the purchase.

For SaaS startups, this can take different forms, such as: offering customers a free trial, taking them through a self-guided onboarding tour, automating customer support, or facilitating word-of-mouth by rewarding customer referrals.

A well-executed product-led growth strategy has numerous benefits:

* **Lower Customer Acquisition Cost (CAC):** by letting your product and existing customer base do the selling and relying less on marketing campaigns, brands can reduce their CAC.
* **Higher Lifetime Value (LTV):** product-led growth leads to more engaged customers, which exhibit a higher Average Order Value (AOV) and Repeat Purchase Rate (RPR), making for a higher customer lifetime value.
* **Higher Revenue per Employee (RPE):** by automating as much as possible of the customer journey, you can lower your operating costs and free up resources to focus on more strategic initiatives.
* **Deeper customer understanding:** to adopt a PLG strategy, you’ll need an intimate knowledge of your customer base. This positively impacts all areas of the business, such as your fulfillment, customer service, and marketing teams.
* **Improved team alignment:** since product-led growth encompasses the entire organization, team members in a PLG company are more aligned and focused than marketing-led or sales-led teams, which makes them happier and more efficient.

As you can see, product-led growth allows you to create a flywheel that positively impacts key metrics across all areas of your organization. As you become more experienced at practicing product-led growth, you’ll start seeing the world through a different lens: rather than relying exclusively on paid acquisition channels, you will begin experimenting with ways your product can generate traction and create efficiencies.

## Does Product-Led Growth Apply to eCommerce?

The answer is: it depends. While product-led growth has been initially designed for traditional software companies, you can–with some creativity–adapt many of its elements to work for the business model and customer journey of an eCommerce/DTC brand.

For an eCommerce brand to become a product-led company, you must broaden your perspective of what constitutes your “product.” Many brands identify this directly with their physical product and consider the rest of the shopping experience an implementation detail. This mindset severely limits your ability to benefit from a product-led growth strategy.

![](https://cdn.sanity.io/images/kqgmf0g2/production/16f5b011c01d62e0d9a223638a5fc607bf5a84df-2560x2402.png?fit=clip)

Instead, product-led brands consider every customer touchpoint part of their product, and they’re constantly thinking about how to create new touchpoints to engage, activate and retain the customer. Here are a few examples of brands that are using techniques borrowed from product-led growth:

* Vitamin brand [Care/of](https://careof.org/) has a [mobile app](https://apps.apple.com/us/app/care-of/id1273387955) that allows to personalize their subscription plan, track their vitamin and health routines, and get rewarded for consistency. The app allows potential buyers to experience Care/of’s product’s value while building further engagement with established/active users.
* Swiss sportswear brand [On](https://www.on-running.com/) recently released [Cyclon](https://www.on-running.com/en-us/collection/cyclon), a program that allows customers to “subscribe” to specific products, such as running shoes and tees. They have taken a sporadic event, such as buying a new pair of shoes, and turned it into a SaaS-ified experience that boosts customer retention.
* Rather than asking customers to pay for their orders upfront, apparel brand [Stitch Fix](https://www.stitchfix.com/) allows subscribers to try outfits and only pay for what they keep. This allows customers to experience the value of the brand before committing.

Subscription-based and membership-based brands have an inherent advantage over brands that favor a one-time purchase journey. This is because they start with a much larger “surface area” to engage their customers. However, brands that don’t have a subscription or membership program–and have no intention of establishing one–can still see success by borrowing and implementing individual elements from product-led growth.

## Embracing Product-Led Growth for Your Brand

Brands looking to start with product-led growth often get discouraged by the number of initiatives they could experiment with. If you’re coming from a traditional marketing-led approach, it can be hard to adopt the right mindset. 

If you don’t know where to start, an excellent first step is to map customer touchpoints across different stages of your shopping funnel and user experience, from brand awareness to order fulfillment. There are a few ways to do this:

* Involve stakeholders from different departments to understand how they interact with the end-user, directly and indirectly.
* Talk to your most loyal (and least loyal!) customers to collect feedback on how your brand fits into their day-to-day, their current pain points, and any ideas they might have.
* Look at quantitative analytics to uncover usage and engagement patterns.

The more feedback and data you can collect, the more holistic your understanding of your brand-customer relationship will be, and the more opportunities you’ll uncover for a product-led growth transition!

Once you have your customer touchpoints mapped out, look at each critically and ask yourself the following questions:

* **How can you command a greater share of customer attention?** Many DTC brands have a transactional relationship with their customers and fail to invest in a longer-term relationship. In reality, zero-party and first-party data allow most brands to create deeper connections: what are some “aha” moments you can generate?
* **How can you deliver value before capturing value?** For a DTC brand, this often takes the form of content-driven education or offering a tool that helps customers enter your brand’s world and experience its value _before_ a traditional activation. Sneaker marketplace [The Edit](https://www.theeditldn.com/), for example, provides a free [personal shopping service.](https://www.theeditldn.com/en-eu/pages/personal-shopping-service)
* **Can you create efficiency by investing in automation?** This is often more nuanced than a simple yes-or-no answer. Any investment in automated/self-service workflows must offer a justifiable return on team efficiency or customer engagement (or both!). Generative AI, in combination with low-code/no-code platforms, creates some fantastic opportunities to automate customer service, product quizzes and similar while mainaining a human touch.
* **How can you spark virality?** Product-led companies are masters at making their products viral. eCommerce brands have many opportunities in front of them: packaging, transactional notifications, and even customer service interactions can become ways to generate positive word-of-mouth.

If you come up with an endless list of initiatives, don’t panic! Start with smaller experiments that allow you to build momentum and train your product muscle, and see how your customers respond. A strong product management foundation can help identify the biggest point of leverage.


## 5 Examples of Product-Led Initiatives for eCommerce Growth

For inspiration, here are the five most common product-led initiatives that we see eCommerce and DTC brands apply:

* **Membership programs.** While traditional loyalty programs primarily reward spending through cashback or similar models, well-designed membership programs take the brand-customer relationship one step further by leading customers to identify with the brand. This can take the form of early access to new products, in-person or virtual get-togethers, direct access to company founders, and any other perks relevant to a brand’s unique customer base.
* **Referral programs.** Happy customers love to spread the word, and referral programs allow them to do just that. It’s common for brands to reward referrals with discounts and promo codes, but we encourage brands to design a bespoke strategy that will resonate more with their customer base. If you’re a luxury brand, offering swag/products in partnership with other brands might be better than offering $20 off.
* **Try before you buy.** Allowing your customers to experience your physical product before committing to a purchase is the epitome of delivering value before capturing value and can be a great way to engage undecided customers (especially when paired with some of the other initiatives in this list!).
* **Educational content.** Content is one of the most common organic marketing efforts pursued by DTC brands, and with good reason. Producing valuable, educational content for your audience is a straightforward way to generate brand awareness by solving a genuine problem. If you go down this path, nvesting in a solid [content infrastructure](https://nebulab.com/blog/ecommerce-content-management) will pay dividends.
* **Web-based/mobile apps.** Often, brands design mobile apps that are purely transactional, making them useless to customers that have not already decided to shop with the brand. In doing so, they miss invaluable opportunities to nurture their audience through content and interactions that don't aim for a direct sale.

While these are all good starting points that will apply to many brands, you should have the courage to explore unique ideas that will make you stand out. Rolling out a successful product-led strategy requires a deep understanding of your customers, how they experience your brand, and what opportunities you can capitalize on to become an indispensable part of their daily routine.

If you need help rolling out your product-led approach, [reach out!](https://nebulab.com/contact-us) Since 2012, we’ve helped tens of DTC brands scale their presence by developing unique experiences. We’re happy to help you figure out if product-led growth is right for you and how you can get started on your product-led journey.

Scaling DTC Brands Through Product-Led Growth

In our [latest article](/blog/ecommerce-ab-testing), we wrote about the value of A/B testing (also
referred to as “split testing”) and how eCommerce brands can set up and scale an effective A/B testing strategy. By
getting the fundamentals right, brands can use A/B testing to generate unbiased, data-informed market insights. Large
brands often run tens of experiments at any given time and use the results to directly inform their product strategy.

However, we also touched briefly on the hidden complexity behind an A/B testing operation: in fact, **one of the curses
of A/B testing is its apparent simplicity.** It’s easy to get lured into signing up for an A/B testing tool without a
clear understanding of how it works, only to find ourselves weeks later with tests that are inconclusive or just plain
incorrect.

This article will dig deeper into this complexity, highlighting some of the most common pitfalls brands face when
running experiments. We will also discuss the scenarios in which A/B testing is _not_ the way to go and the alternative
practices brands should adopt instead.

## The 7 Most Common A/B Testing Mistakes

A/B testing is a form of statical hypothesis testing. As such, it is prone to all the typical pitfalls of statistical
analysis: most notably, **if the data you’re using to run the analysis is incorrect, biased, or skewed in any way, the
results of your analysis are also very likely to display the same problems**–garbage in, garbage out.

Even with modern A/B testing platforms, it is still unbelievably easy to skew the results of an A/B test. Your tools can
help you write less code and run the math for you, but they won’t be able to make strategic decisions for you–such as
which metric to pick–or to shield your test from external factors–such as a concurrent A/B test skewing your test
population.

With this in mind, let’s see some of the most common mistakes and oversights a brand might make when designing,
executing, and analyzing an A/B test.

### 1. Type I and Type II errors

All A/B tests are subject to two different types of errors:

* **Type I errors (false positives)** occur when we detect a non-existent difference between the experiment and the
  control group, i.e., we conclude that our experiment affected our target metric when it actually didn’t.
* **Type II errors (false negatives)** occur when we fail to detect a difference between the experiment and the control
  group, i.e., we conclude that our experiment failed to affect our target metric when it actually did.

We can guard our tests against Type I and Type II errors by picking an appropriate statistical significance and power:
the _higher_ our significance, the more resilient our test will be against Type I errors; the _lower_ our power, the
more resilient our test will be against Type II errors. Combined, these numbers represent our desired confidence in the
test result.

As an example, if we pick a significance of 80% and a power of 5%, it means that:

* There’s only a 20% probability that our experiment group will outperform our control group by chance.
* There’s only a 5% probability that our control group will outperform our experiment group by chance.

**Higher confidence levels mean we can take more drastic actions as a result of our test but also require larger test
populations,** which may be challenging to reach for smaller brands.

An 80% significance and a 5% power is a good starting point for most A/B tests, but you should use your judgment: in
some tests, the cost of making a mistake in either direction might be higher or lower than usual; in others, you might
only want to worry about false positives or false negatives.

### 2. Novelty Effect and Change Aversion

Two interesting dynamics can threaten the validity of A/B tests, and they both stem from how your users react to change.
These are more relevant for products with a high percentage of returning users, so you should be extra careful if your
brand offers subscriptions, for instance, as they could prevent you from getting reliable results.

**The Novelty Effect occurs when users engage with a product more than usual because they’re fascinated by a new feature
or a change in an existing feature.** For instance, users might purchase more if you introduce a brand-new loyalty
program to drive incremental recurring revenue. However, as they adapt to the change, most people will gradually regress
to the average user behavior patterns.

Change Aversion is the exact opposite and often happens with significant redesigns of existing functionality: **you
might find that affectionate users engage less with your experiment,** as they were used to the previous way of doing
things and don’t like that their workflows got disrupted. Over time, they will likely get used to the new design and
re-engage with your brand as usual.

For both problems, **the solution is to segment your A/B test results by new and existing users.** By analyzing the
performance of these two buckets separately, you can more easily isolate the effect of your experiment from the effect
induced by novelty/change aversion. Of course, you'll have to figure out what counts as a “new” or “existing” user, and
it might differ depending on the test you’re running.

### 3. Network Effect

**The Network Effect occurs when users of an A/B test influence each other,** effectively “leaking” outside the bucket
they belong to (i.e., the control group interacts with the experiment, or the experiment group reverts to control). This
most often occurs with “social” functionality, where users interact with each other directly.

Consider the case of a second-hand marketplace that wants to offer users the ability to exchange goods directly without
a cash transaction. By definition, such a feature will require two users to participate: the sender and the receiver.
One quick solution would be to assign users randomly to the experiment or control group and only allow users in the
experiment group to use the new functionality. However, this might lead to a sub-par UX, causing frustration and skewing
the test results.

Instead, **you should cluster users into groups, with all users in the same group being more likely to interact with
each other.** For instance, you might cluster users by state, assuming that most of your marketplace’s transactions
happen within the same state. You would then assign each state to the control or experiment group. Users might still
interact across different states, influencing each other, but clustering helps minimize the likelihood of spillover.

The Network Effect is relatively uncommon in eCommerce, but it’s still worth understanding if your brand allows users to
interact with each other (as in the case of a marketplace). It can lead to unexpected results and can be incredibly
sneaky to detect. As a rule of thumb, you should always consider whether any tests you’re designing have the potential
to introduce a network effect and plan accordingly.

### 4. History Effect

**The History Effect occurs when an event in the outside world affects the results of your A/B test.** This can be
anything from a marketing campaign to a shopping holiday. These events are likely to change the behavioral patterns of
your visitors compared to the average, which will cause you to extrapolate incorrect insights.

For example, let’s assume you’re testing whether offering a discount in exchange for newsletter signups significantly
increases subscribers. If you decide to run the test during a site-wide sale (e.g., because of Black Friday/Cyber
Monday), your test might be inconclusive.

**To mitigate the History Effect, ensure you have solid processes to ensure you’re not running A/B tests concurrently
with major media coverage and PR events.** It also helps to run your A/B tests for at least two complete business
cycles, which typically translates into 2-4 weeks for most brands.

### 5. Simpson’s Paradox

**Simpson’s Paradox is a particularly sneaky type of error that occurs whenever you inadvertently introduce weighted
averages into an A/B test,** which can happen in a few cases:

* **When you adjust the traffic split for an A/B test during test execution.** Example: you start your test at 50%/50%,
  then change it to 90%/10% when you see that the experiment is outperforming the control.
* **When your website traffic segmentation is not consistent across different variants of your test.** Example: you
  segment your test by returning vs. new visitors, but you have 1,000 new customers visit the experiment, and only 500
  visit the control.

In these scenarios, you might find that any correlation identified in individual test segments disappears or is inverted
in your aggregate results. This is because the aggregate result calculation effectively becomes a weighted average, and
your larger segments will “overwhelm” the smaller ones.

You can find a more academic explanation of Simpson’s paradox
[here](https://learn.microsoft.com/en-us/archive/msdn-magazine/2005/december/test-run-software-testing-paradoxes), but
there are a few things you can do to prevent Simpson’s Paradox from finding its way into your test results:

* **Ensuring your test populations are accurately randomized** and evenly distributed among different test variants. In
  other words, you should have the same number of visitors from each segment to each variant of your test.
* **Running an A/A test** (i.e., a “fake” A/B test where both variants are the same) can be helpful to ensure proper
  randomization.
* **Looking at test results across different segments** ensuring and not just at the aggregates so that you can spot any
  inconsistencies.
* **Relying on your A/B platform’s built-in capabilities,** e.g., Optimizely’s
  [Stats Accelerator](https://support.optimizely.com/hc/en-us/articles/5326213705101-Stats-Accelerator-Acceleration-Under-Time-Varying-Signals),
  to make your tests more resilient to Simpson’s Paradox.

### 6. P-hacking

P-hacking is an extremely common A/B testing pitfall–so much so that it used to be _encouraged_ by A/B testing tools
such as Optimizely. Simply put, **P-hacking is the practice of changing a test’s original parameters to reach a
pre-determined conclusion.** This can come in different forms:

* Some teams stop a test as soon as it reaches statistical significance rather than letting it run for its established
  duration.
* Some teams increase the test population until they reach statistical significance.

**P-hacking is often caused by pressure from your leadership or digital marketing team** to get a specific result from an
A/B test or to maximize the impact of a successful experiment as quickly as possible. Unfortunately, this is not how
traditional A/B testing works: once you have established your sample size, you simply need to let your run test run its
course and evaluate the results only at the end.

Because this methodology isn’t particularly well-suited to the speed at which startups typically move, many A/B testing
platforms ended up implementing alternative algorithms. Optimizely, for instance, introduced Stats Engine in 2015, which
allows A/B testers to peek at test results without the risk of taking action prematurely–you can learn more about how it
works in
[this introductory article](https://www.optimizely.com/insights/blog/statistics-for-the-internet-age-the-story-behind-optimizelys-new-stats-engine/)
by the Optimizely team.

While features such as Optimizely’s Stats Engine or VWO’s Bayesian engine help A/B testing teams avoid pitfalls such as
P-hacking, they don’t eliminate the need for proper test planning.

### 7. Instrumentation Effect

While most pitfalls outlined in this article are statistical, the Instrumentation Effect is much simpler: **it occurs
when your analytics, A/B testing infrastructure, or test implementation don’t work correctly**, skewing test results.
Here are a few examples:

* Your analytics setup sometimes reports conversions twice, skewing the total number of conversions you use to evaluate
  your test results.
* Your A/B testing setup sometimes puts the same customer in different buckets throughout the same A/B test.
* One of your test variants has a user experience edge case that prevents specific customers from completing their
  interaction with the webpage.

Because these bugs happen at the very source of your data, no statistical methods can solve any of these problems for
you. Instead, you need to regularly and rigorously test every part of your A/B testing infrastructure:

* Before running an experiment, **make sure that all the metrics you are interested in are being reported accurately.**
* **Test your experiments for usability and integrity** with the same attention you’d reserve to a permanent feature.
* **Run A/A tests to verify that your A/B testing setup works correctly** and that your upstream data collection is
  reliable.

## A/B Testing Is Not a One-Size-Fits-All Methodology

Reading this article, you might think that we want to discourage eCommerce brands from running A/B testing, and you’d
be–at least partially–correct. It’s not that A/B testing doesn’t have its place in an eCommerce brand’s strategy. But
**the effort involved in planning, executing, and analyzing an A/B test, assuming that you want to get significant
results, is often not sustainable by most early-stage brands.**

Anyone not adequately trained in the statistical techniques behind A/B testing will have a tough time guarding their
tests against the pitfalls we’ve outlined–which, by the way, are a subset of all the different statistical and practical
errors A/B testers can incur. Tools can help mitigate some of these errors to an extent, but they can’t turn an
inexperienced team into data analysis experts overnight.

Furthermore, **A/B testing is very often not the best research methodology.** There are many scenarios in which A/B
testing falls short.

* First and foremost: **A/B testing, by its very nature, is focused on short-term gains.** As we have seen, these can
  sometimes come at the expense of long-term business results: focusing on click-through and conversion rates might come
  at the expense of retention and customer LTV.
* As a result of the above: **A/B testing tends to deprioritize disruptive innovation,** leading teams to focus on
  incremental gains instead—its typical application is in conversion-rate optimization. If your brand is working on a
  massive product launch, or a brand new membership program, A/B testing will not offer any meaningful insights into how
  your customers might respond.
* **The cost of designing and launching an A/B test is high:** every test you run effectively creates two “branches” in
  your digital experience. This means your team will have to tiptoe around your A/B test until it’s run its entire
  course, slowing down further innovation and improvements in that product area.
* **A/B testing is a quantitative and evaluative research methodology.** As such, it needs an initial hypothesis to
  validate–and one that can be clearly and unequivocally validated with a data-driven approach. Anything requiring
  generative or qualitative research, which often involves talking to your customers, is not a good fit for A/B testing.

## Start A/B Testing When You Have Product Management Fundamentals

So, are we suggesting that retailers shouldn’t A/B test? Not at all: A/B testing has its place, and when employed
correctly, it can be instrumental in improving a business’s KPIs and bottom line. To dismiss A/B testing as too
complicated to be worth the effort would be incredibly short-sighted and detrimental.

However, **many eCommerce businesses dive head-first into A/B testing without proper product management fundamentals.**
We’re talking about generative and evaluative research methodologies such as heatmaps, user interviews, user testing,
on-site surveys, session replays, historical analytics, feature flags, and many other techniques.

These practices have a broader set of potential use cases and are also a prerequisite for being able to A/B test
intentionally. Plus, they’re almost always _simpler_ to implement and leverage than an effective A/B testing
infrastructure!

The next time you–or someone else on your team–want to run an A/B test, stop for a moment and ask yourself: **is there a
more straightforward, more efficient way to answer this question/validate this testing hypothesis?** You might be
surprised about how many alternatives you have at your disposal.

In the next few weeks, we’ll be exploring precisely these product fundamentals, explaining when and how they are best
used, and how you can orchestrate them together to form the basis of a strong product management practice for your
eCommerce brand.

How to Make Your eCommerce A/B Tests Useless

eCommerce brands have a variety of techniques at their disposal for understanding their customers and optimizing their KPIs: most of these techniques have been borrowed from modern product management practices and can be directly applied to eCommerce–A/B testing is one of these.

A/B testing (sometimes referred to as “split testing”) is a technique that uses statistical algorithms to determine which variation of a given behavior is most likely to optimize for a predetermined quantitative outcome. **By using live traffic to analyze user behavior, A/B testing can provide an objective, data-driven answer to nebulous questions**, such as whether offering free shipping to your customers will significantly affect add-to-cart rates.

With that said, **A/B testing is one of many techniques brands can employ and arguably one of the most complicated to execute correctly**. Unfortunately, we often see brand founders and executives jump into A/B testing without clearly understanding the required skillset or effort, only to arrive at disappointing conclusions and abandon the practice altogether.

We firmly believe that A/B testing has its place. Still, we also have strong opinions about when it should and shouldn’t be employed and the requirements for running a successful A/B testing operation. In this guide, we will break down some of the complexity behind A/B testing, help you understand whether it’s a good option for your brand, and offer practical tips and considerations for rolling it out.

## A Primer on How A/B Testing Works

At its core, A/B testing is a simple concept: we design two variations of the same web page (version A and version B), distribute our traffic evenly among the two variations, then see which one reported the best performance.

Going back to the “free shipping” example, an online store could show a free shipping banner to half their customers (this is the experiment group) and use the original page for the other half (this is the control group). At the end of the test, whatever version got the highest conversion rate would be considered a winner (with some statistical caveats).

This is the simplest possible type of A/B testing, but there are a few alternatives:

* **In A/B/n testing**, more than two variations are tested (e.g., no free shipping indication vs. a free shipping banner vs. a free shipping popup).
* **In multivariate testing**, each variation alters multiple elements on the page (e.g., a free shipping banner and a popup, just the banner, just the popup, no free shipping indication).
* **In bandit testing**, more and more traffic is automatically directed to the winning variation (e.g., if the free shipping banner converts more than the original page, we automatically start showing it more and more often).

![MailChimp A/B testing](https://cdn.sanity.io/images/kqgmf0g2/production/9c659965ed7f4ff19fa622d3e58e7b19fc883353-2560x2512.png?fit=clip)

It’s important to note that while this article talks specifically about A/B testing web pages, the technique can be applied—at least to an extent—to email marketing, social media, and other types of digital properties. Furthermore, eCommerce platforms, marketplaces, and marketing tools often provide native A/B testing capabilities:

* Amazon allows its merchants to A/B test content such as product images
* Hubspot allows testing landing page templates and email campaigns.
* Google Ads allows testing different ads to optimize clickthrough rates.

These concepts are deceptively simple, which is why so many A/B testing platforms promise exceptional ROI and quick results. **In reality, A/B testing comes with many pitfalls and “gotchas” that practitioners should understand thoroughly**. Running an effective A/B testing operation on an eCommerce website requires significant preparation, effort, and discipline.

## What an Effective A/B Testing Process Looks Like

Let’s take a peek into what a successful, effective A/B testing operation looks like in detail.

### 1. Picking a Problem Space

There are many resources online advertising “the best 99 A/B testing ideas,” and it might be tempting for inexperienced executives to jump in and start testing. Unfortunately, these blanket experiments are unlikely to move the needle–in some cases, they might even be detrimental to a brand’s KPIs. Furthermore, they completely ignore the true purpose of A/B testing, which is not conversion rate optimization but refining our understanding of our market, business, and customers.

For this reason, before diving head-first into changing the color of our CTA buttons, we must understand the problem space we want to explore. This can be a very narrow product opportunity, such as whether a new version of the search functionality will lead to better recommendations, or a broader area of the business that we want to understand better, such as how we can improve our conversion rates during the checkout process.

![POA template](https://cdn.sanity.io/images/kqgmf0g2/production/a7dfcc5783e16119a81831284987627f9fcb093f-2560x2512.webp?fit=clip)

Whatever the case, **we need to articulate precisely what questions we want to answer and why we think an A/B test is the correct methodology to answer them**. This is most often done through a Product Opportunity Assessment (POA), a document that explains what problem we’re solving and for whom, analyzes the market and the problem space, any business- and customer-facing implications of solving the problem, and provides a final recommendation (go/no-go) based on the information we have collected.

A/B testing, when employed correctly, is an invaluable tool that allows eCommerce product managers to quantitatively confirm or disprove existing hypotheses related to a particular opportunity. Still, it’s not a replacement for picking and refining an opportunity in the first place. Unfortunately, brand executives and marketers sometimes fall into the trap of running mindlessly through a list of standard A/B tests, leading to short-term, black-box optimizations at best and a waste of resources.

### 2. Designing the Test

Once the opportunity is well understood and prioritized, it’s time to design the A/B test. The first step is formulating a hypothesis that we want to confirm or disproven, which usually looks like this:

> We think that, by [experiment], we can increase [metric] by an [absolute/relative] [Minimum Detectable Effect]%.

Stating the hypothesis is the first step, but we will need a few more elements before launching our experiment. In particular, we need to establish the following:

* **Our current conversion rate**. If we don’t have it, this is a good time to stop and put the proper instrumentation in place.
* **The desired statistical power**. This indicates how likely we are to detect a difference between the control and the experiment, assuming it exists. Higher values give us more confidence in the test results but require larger samples.
* **The desired significance level**. This indicates how likely we are to detect a difference between the control and the experiment when it doesn’t exist. Lower values give us more confidence in the test results but require larger samples.

![Evan Miller's A/B testing sample size calculator](https://cdn.sanity.io/images/kqgmf0g2/production/e69b939e8d2e7df81f552d122ff5d4ffd00fba9e-2560x1534.webp?fit=clip)

Once we have established these parameters, we can plug them into one of many A/B test sample size calculators–Evan Miller’s is arguably the most popular, but any popular A/B testing platform (e.g., **LaunchDarkly**, **Optimizely**, **VWO**) will also do the math for you.

Finally, we must decide how long we want to run our test. **It’s usually recommended to run tests for at least two complete business cycles**. This helps to protect our experiment from a few common pitfalls, such as external validity threats, novelty/maturation effects, and change aversion. We’ll cover these in a separate article!

### 3. Launching the Experiment

The next step is to work with our product team to design and implement our experiment.

Most modern A/B testing platforms allow non-technical users to launch tests with complete autonomy. After copy-pasting a snippet of JavaScript code to their website, brand operators can design and launch experiments that alter UI elements without touching a single line of code: users can alter page layout, CTA styles, and other elements. This capability allows product managers and stakeholders to move quickly and saves engineering bandwidth for high-impact product work. However, it also comes with some caveats of which users are typically unaware.

First of all, **experiments that have been implemented without the assistance of a product team might present bugs or inconsistencies that make them less palatable to new and existing brand customers**. This might skew our test results: what if our latest category page experiment failed to outperform the control because the customer experience was counterintuitive? In some cases, such pitfalls can completely invalidate an experiment, resulting in a waste of resources.

![Optimizely homepage](https://cdn.sanity.io/images/kqgmf0g2/production/f8e3234adf8087323de71b30402eb2e6bdc7133e-2560x1702.webp?fit=clip)

Secondly, it’s not uncommon for a large brand to run tens of experiments simultaneously. **When experiments run in the browser, they can have significant performance implications and harm the user experience**.

**Brands should invest in A/B testing infrastructure that allows them to design and launch experiments quickly while continuing to involve the product team.** This often comes in the form of streamlined processes, strong design/development primitives–such as a reusable design system and UI kit–and clear guidelines on what is considered “good enough” for an experiment.

### 4. Analyzing Test Results

Once the test is completed, it’s time to analyze the results. Typically, there are two questions we’re looking to answer for each A/B test.

**The first and most obvious is whether the experiment outperformed the control**–or, in other words, whether our hypothesis was confirmed or disproven by the test. If the experiment outperforms the control, we can say that our hypothesis is correct–within the established levels of statistical confidence, of course. We might also find that the control outperformed the experiment or that the test was inconclusive (i.e., neither variation significantly outperformed the other, and no winner can be established).

**The second question is what secondary implications the test had on our experiment population.** This might involve looking at other metrics or specific customer segments to understand whether the test affected our customers in non-immediate ways. Here are a couple of examples:

* A test might tell us that offering 50% off on the first order of our subscription product increases our subscription activation rate. However, when we look at secondary metrics, we might find that the experiment group also has a much lower retention rate than the control group, causing us to lose money on every conversion. Is this outcome desirable for our eCommerce business?

* A test might be inconclusive or present the control group as a global winner. However, when we dive into the data, we might find that the experiment blatantly outperformed the control for specific segments. Sometimes, this might indicate an opportunity to offer a more [personalized experience](https://nebulab.com/blog/ecommerce-personalization).

![LaunchDarkly metrics view](https://cdn.sanity.io/images/kqgmf0g2/production/35a9f4a0a28701605f61c311163f4345cd12eec8-1200x857.webp?fit=clip)

As a rule of thumb, it can be helpful to map some of these secondary considerations when designing the test. However, this analysis is very exploratory, and it’s impossible to list all the possible outcomes in advance. **Brands should take the time to review test results with different stakeholders so that everyone can bring their KPIs and perspective to the table.**

Once we have finished analyzing the results, it’s time to archive them. This is a step that most practitioners skip, but it’s incredibly valuable: **archiving the results of our A/B tests allows us to establish them as a first-class research methodology** rather than a short-term approach to conversion optimization. Ideally, insights derived from A/B tests should systematically become part of our organizational knowledge.

### 5. (Bonus) Re-Testing as Needed

What’s true today might not be true tomorrow. When they first embrace a product-led approach to brand growth, we see many founders make the mistake of thinking that any insights they have uncovered are set in stone and will never need to be revisited. In reality, markets change constantly, and so does our business.

We don’t encourage re-running A/B tests for the simple sake of it–in most situations, the effort of re-testing far outweighs the benefits. However, **practitioners should feel comfortable re-running an old test or testing old assumptions in novel ways**.

## An End-to-End A/B Test Example

Let’s see what an end-to-end A/B test execution might look like by following the process we have just outlined:

1. As we’ve mentioned, it all starts with identifying a problem space we want to explore. In this case, let’s assume we are trying to understand why our product page has a particularly high bounce rate. We draft a Product Opportunity Assessment, collecting all the information we have gathered.

2. We collect a few hypotheses about why this might be happening, based on what we know about the business and our customers: maybe visitors can’t find critical information in the product description; maybe the particular variant they are looking for is out of stock; or maybe they aren’t willing to pay shipping costs.

3. We start by testing the shipping cost hypothesis. After looking at Google Analytics, we conclude that increasing add-to-cart rates by an absolute 10% would be considered a win.

4. Because offering free shipping comes at a considerable cost, we want to be very confident about our test results, so we pick a 95% statistical power and a 10% significance level for our test.

5. We plug the numbers into our favorite A/B test sample size calculator, which tells us we’ll need to direct 858 visitors to each branch of our test. Based on our traffic patterns, we think we can accomplish this in two weeks.

6. We work with our design and engineering team to implement an experiment that offers customers free shipping and displays the offer prominently on the product page.

7. We use our favorite A/B testing tool to launch the test.

8. After two weeks, we look at the results of the test. It turns out that the test was overall inconclusive: offering free shipping did not significantly affect the add-to-cart rate. However, when we look into the results across different segments, we find that the experiment group outperformed the control group for products over $150.

9. We archive the results of the test and refine our POA accordingly.

![LaunchDarkly results view](https://cdn.sanity.io/images/kqgmf0g2/production/bb3782925740b9b70a5349429382e14e496c3113-1200x860.png?fit=clip)

Now that we have the results of the test, we may decide to:

* Offer free shipping to everyone. Our business might have a policy of offering the same shipping conditions to everyone.

* Offer free shipping only on products over $150 to maximize our ROI. We might even play with different placements of the free shipping indication: what if we included the banner in the shopping cart or checkout page?

* Run another A/B test on a more promising target audience. We could test free shipping for products over $150, to be confident that it will actually move the needle for that segment.

* Collect more information through alternative product research methodologies like user testing or heatmaps.

* Not do anything: a more detailed evaluation might find that free shipping is not the highest-impact solution to this problem (e.g., perhaps we’d be better off adding testimonials to the product page or offering an upsell).

As we’ve mentioned, **an A/B test doesn’t have to lead to immediate action**. By treating our tests as a source of insights rather than a mere CRO methodology, we can deepen our knowledge of our customers with statistically verifiable, data-driven information that will enrich our product strategy and ultimately increase our bottom line.

## What Comes Next

We could talk for ages about the pros, cons, prerequisites, and implications of A/B testing, but this is more than enough for a single article.

**In the following articles, we’ll explore the most common pitfalls operators, marketers, and product managers incur when setting up and executing an A/B testing strategy**. We’ll talk about statistical significance, the shortcomings of using A/B testing as your only source of product knowledge, and what alternative strategies brands must employ before considering running an A/B testing operation.

In the meantime, if you have any questions about any topics we have discussed or need help designing an A/B testing strategy for your eCommerce site, [don’t hesitate to reach out!](https://nebulab.com/contact-us)

eCommerce A/B Testing: Strategies for Success

With 9 out of 10 online shoppers stating that they want retailers to offer recommendations based on their interests, and
considering the vast amount of data and technology brands now have, there are few excuses not to have a personalization
strategy in place. eCommerce personalization is proven to increase conversion rates, customer retention, and lifetime
value, creating a virtuous cycle that can turn your visitors into loyal customers.

And yet, we often see brands struggle with rolling out an effective eCommerce personalization strategy: founders aren’t
sure how to segment their customers, evaluate the effectiveness of their personalization program, or what technologies
to adopt.

This article will demystify eCommerce personalization, providing you with a straightforward, data-informed approach for
designing, implementing, and validating your personalization program.

## What Is eCommerce Personalization?

Much confusion stems from the vagueness of the term “personalization.” If you Google it, you’ll find books, articles,
and SaaS products that all give it a different meaning: they talk about A/B testing, machine learning algorithms,
retargeting, user-generated content… It can be hard to understand where to start.

At its core, eCommerce personalization is the technique of using the information you have about your customers to
display content that is tailored to them. You can personalize across different dimensions (e.g., personalize by country,
browsing history, demographics), at different touchpoints (e.g., your website, your email campaigns, your ads), and with
different techniques (e.g., machine learning, user-generated content, human curation). No matter *how* you personalize,
the goal is to create a customer experience that feels unique.

## Designing Experiments with GTDT

When we coach founders that want to start experimenting with personalized eCommerce, we encourage them to think of
personalization as the means, not the end. Like all initiatives, personalized shopping experiences must be designed
thoughtfully and intentionally for maximum effectiveness. Adopting a tool or installing a plugin will only take you so
far if you don’t have a clear understanding of what you want to achieve with your personalization program.

Unfortunately, most resources offer an endless list of personalization examples from famous online retailers but no
indication of *why* or *how* those brands designed their personalization programs. This leaves operators scratching
their heads as they try to replicate the success of these brands. As a result, they tend to go for “blanket solutions”
that are easy to implement but ultimately leave the most exciting opportunities on the table.

Over time, we have developed a model that helps brands roll out thoughtful personalization experiments that get them
closer to their goals. **We call it GTDT, which stands for Goal, Technique, Dimension, and Touchpoint.** In the
following paragraphs, we will explain this process, providing you with all the tools you need to design your
personalization program.

### Goal

This might seem obvious, but surprisingly often, online stores will launch personalization capabilities to tick off a
checkbox with no clear goal in mind. Unfortunately, this not only means they will roll out an ineffective
personalization program, but it also means they will not be able to validate the effectiveness of their program: if you
don’t know what metric you’re optimizing for, you will not know what metric to look at.

The first step for any good personalization experiment is to understand what goal you’re aiming for—everything else
follows. Depending on your brand’s SKU catalog and business model, a personalization experiment for increasing your
average order value will likely look much different from an experiment to improve your add-to-cart or repeat purchase
rates.

If you’re unsure what goals you should be prioritizing, talk to your team and pick the one that feels most urgent right
now. Where are you falling behind compared to the industry benchmarks and your (or your board’s) expectations? What are
your customers telling you in your interviews? (You ***are*** doing customer interviews, right?) What are your plans for
the next 12-18 months?

Don’t make the mistake of falling into analysis paralysis: the beauty of running experiments is that you can quickly
pivot if you find that you’re optimizing for the wrong things. Make a data-informed decision, launch your experiment and
move on!

### Technique

With eCommerce personalization rising in popularity, several tools have emerged that promise to offer the definitive
solution to all your personalization problems. A/B testing tools, content management systems, eCommerce platforms, UGC
aggregators… almost every tool provides some level of personalization nowadays.

Unfortunately, without a clear personalization plan, it’s easy to get carried away by shiny object syndrome and try
every tool in hopes that it will solve all your problems. Do this enough times, and you’ll end up with a Frankenstein
monster of solutions that don’t integrate and annoy your customers with endless popups and broken UIs.

Before picking a tool or technology, decide **how** you want to personalize. You should do this, first and foremost, by
continuously referring back to your experiment goal and dimensions, but you should also lean on your brand’s strengths
and values. If you’re a fitness brand that’s all about community, you might want to leverage the power of user-generated
content, at least in *some* of your experiments. If you’re a luxury brand selling elevated essentials, perhaps you can
offer human-curated recommendations to your customers.

This last example brings us to the next point: don’t be afraid to do things that don’t scale, especially in the early
stages of your company. Many brands go from zero to a hundred by integrating deep learning models that are complex to
tweak and customize, and they don’t realize that they’re missing out on many lower-hanging opportunities. You’d be
surprised by how much you can accomplish with some basic customer segmentation and a human touch.

### Dimension

Once you know what you’re aiming for and how you want to get there, it should be easier to understand which dimensions
you want to personalize across. For example, you might want to personalize content based on geography, customer lifetime
value, previous purchases, demographics, or other factors.

It might help to group personalization dimensions into three big buckets:

- **Historical.** These are actions your customer has taken before. For instance, you might segment customers based on
  their AOV or purchase history.
- **Demographical.** These are traits that will always be true about your customer. For instance, you might segment
  customers based on geography, gender, or age.
- **Contextual.** These are actions your customer is taking now. For instance, you might segment customers based on
  their cart contents or session length.

When thinking about dimensions, don’t get limited by data availability: just because you don’t know your customers’ age,
it doesn’t mean you shouldn’t use it in a personalization experiment. Part of your personalization program should be
designing ways to collect or infer the information you need to carry out your experiments, which has the added benefit
of enriching your understanding of your customers over time.

You also don’t want to limit yourself to generic customer data: we find that the most successful personalization
programs use proprietary brand data to create win-win outcomes. If you sell pet food subscriptions, you might want to
curate your product catalog based on the customer’s pet type or age. If you sell sports equipment, you could send your
customers content specific to their favorite sports. Think about the different ways customers engage with your brand,
and try to design your experiments to optimize and improve those interactions.

### Touchpoint

With your goal, dimension and technique nailed down, it’s time to pick a personalization touchpoint. With this term,
we’re referring to the specific customer interaction you want to personalize. This will likely depend on your goal and
dimension: for example, if you want to increase AOV (goal) by looking at cart contents (dimension) to suggest upsells
(technique), you can only do this after the customer has added something to their cart or completed their purchase.

When deciding which touchpoint to personalize, we encourage brands to look beyond their product pages or on-site user
experience. Even with the average brand, there are so many ways your customers might interact with you and so many
opportunities to personalize those interactions. The most effective personalization programs are omnichannel and focus
on often-neglected interactions, such as transactional notifications, or create entirely new touchpoints, such as
sending customers a personalized card for their birthday.

Again, don’t get limited by your current touchpoints: if you want to send personalized email campaigns but are currently
not doing any email marketing, don’t be afraid to start now. If you think push notifications might resonate with your
customer base, why not give them a try?

The goal is to catch your customers when they need personalization even though they don’t know it, and leverage the
power of data to turn a mundane interaction into an intimate, personalized experience.

## Measuring Experiment Effectiveness

Designing and launching your experiment is only the first step. For an effective personalization program, you want to
validate the effectiveness of your experiment, double down on the ones that work, and kill the ones that don’t.

To do this, you must go into every experiment with a clear definition of success. This means answering the following
questions:

- What metric(s) do you expect the experiment to move, and in what ways?
- Are you already measuring the metrics you need? If not, how can you measure them? Do you need time to get a baseline
  for comparison?
- For how long will you let the experiment run after measuring the results?

### A/B Testing vs. Attribution Models

A special mention here goes to A/B testing: like with AI/ML, inexperienced founders often jump into A/B testing without
a clear understanding of the technique. While it’s tempting to run all personalization experiments as A/B tests,
sometimes this can be overkill or even detrimental: A/B tests require specific expertise, dedicated infrastructure, and
relatively high traffic volumes to reach statistical significance.

Typically, we only recommend A/B testing for large brands, running experiments where the results are highly uncertain,
and a clear control group can be established (e.g., customers that see the regular homepage vs. customers that see the
personalized homepage). In all other scenarios, a robust attribution model is a more reliable way to measure the
effectiveness of your experiment—even better when it’s paired with qualitative customer insights.

### Following Through on Experiment Validation

However you decide to validate your experiment, make sure it’s easy to roll back if needed and remember to look at the
data and take action accordingly! A recurring “experiment review” meeting with your team, where you review all
experiments that need to be validated and decide how to move forward, can do wonders to keep you accountable.

Finally, don’t be too rigid: if you expected a cross-selling experiment to drive $100K in revenue, but it only drove
$80K, it might still be worth keeping, depending on the effort you need to turn it into a permanent, first-class
capability. For some experiments, it might be helpful to establish different thresholds of success. Going back to our
example:

- Anything below $50K might be a clear failure.
- Anything between $50K and $100K might be up for discussion.
- Anything above $100K in incremental revenue might be a clear success.

Generally speaking, whenever you make decisions about your digital experience, you want to be data-informed, not
data-driven.

## Ready to Start Personalizing?

eCommerce personalization can create remarkable outcomes: when leveraged intentionally, personalization programs
increase revenue, customer loyalty, conversion rates, and lifetime value. It’s a tool that should be part of every
eCommerce store’s marketing strategy.

With the GDTD model, you have a streamlined process to design, launch and validate your personalization experiments.
It’s a high-impact tool that evolves with your brand as you scale, better understand your customers, and develop more
sophisticated ways to engage them.

If you have questions or need help with your brand’s personalization program,
[we’d love to hear from you.](https://nebulab.com/contact-us) Let’s start personalizing!

The Nebulab