Report: How to Increase Repeat Purchases in Beauty

How to Increase Repeat Purchases in Beauty E-Commerce

A Practical Guide to AI-Powered Post-Purchase Upsell, Cross-Sell, and Customer Retention

Executive Summary

For most beauty brands, the customer journey effectively ends at checkout.

The focus is clear here: drive traffic, optimize conversion, acquire new customers. But what happens after the purchase? 

This is often reduced to transactional emails, shipping updates, and the occasional review request.

This is where a significant portion of revenue is lost.

Recent industry data1 shows that:

  • Only 6% of brands actively cross-sell post-purchase
  • 3 in 4 brands do not include any post-purchase offers
  • 88% only ask for reviews; no revenue-generating actions

At the same time, the commercial upside of getting this right is substantial.

Existing customers are a lot easier to convert than new ones. And definitely less expensive. They already know the brand, have demonstrated purchase intent, and provide valuable signals about their needs, preferences, and likely next purchase.

For beauty brands, this creates a clear opportunity to turn one transaction into a longer, more valuable customer relationship.

AI-powered personalization can support this by making every post-purchase upsell more relevant, from recommending complementary products and complete routines to timing replenishment more accurately and guiding customers toward their next purchase.

This report explores how beauty brands can use post-purchase personalization to:

  • increase repeat purchases
  • grow average order value (AOV)
  • improve retention and customer lifetime value (CLV)
  • generate better customer and product insights

The commercial opportunity begins once the first purchase has been made. The brands that continue guiding customers after checkout are better positioned to recover more value from every acquisition.

Table of contents
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I. Why Post-Purchase Is Becoming a Growth Strategy

For years, beauty brands have focused on optimizing every stage of the path to purchase, from attracting new customers and improving product discovery to reducing friction at checkout.

While these efforts remain essential, they’re no longer enough on their own. 

As customer acquisition becomes more expensive, brands are paying greater attention to what happens after checkout, including how a relevant post-purchase upsell can turn an initial order into a longer and more valuable customer relationship. 

What is a post-purchase upsell?

A post-purchase upsell is a recommendation made after an initial order that helps a customer discover complementary products, replenish an existing product, or expand a routine based on what they have already purchased.

⥭ Why Is Beauty Built for Repeat Purchases?

Beauty is uniquely positioned for long-term customer relationships.

Unlike categories built around infrequent purchases, beauty naturally lends itself to ongoing customer relationships. Products are replenished, routines evolve, and customers often return to discover complementary products that fit their preferences over time.

Every purchase creates opportunities for the next one.

Yet many brands still treat each transaction as an isolated event rather than part of an ongoing customer journey.

⥭ The Revenue Opportunity After Checkout

Every completed purchase generates valuable customer signals. Brands can discover customers’ product preferences, shopping behavior, and what they might buy in the future. 

Yet these insights often remain unused. 

Rather than guiding customers toward their next purchase, many brands allow the relationship to lose momentum immediately after checkout. 

For beauty brands, some of the greatest opportunities for long-term growth begin after the first purchase, not before it.

So why are so many brands still missing this opportunity? 

II. The Post-Purchase Gap: Where Beauty Brands Lose Revenue

Beauty brands invest significant time and resources into attracting customers, optimizing product pages, and reducing friction before checkout. Yet once the purchase is complete, many customer journeys become surprisingly limited.

Communication shifts from helping customers discover what’s next to simply confirming that an order has been received and shipped. As a result, the post-purchase upsell is often absent entirely, even when the original order provides a clear basis for a relevant recommendation.

While these touchpoints are important, they rarely encourage another purchase or strengthen the customer relationship.

This creates a disconnect between the investment made to acquire a customer and the value generated after the sale.

What is the post-purchase experience?

The post-purchase experience includes every interaction a customer has with a brand after completing an order, from order updates and customer support to personalized recommendations, replenishment reminders, loyalty activity, and repeat purchases.

⥭ The Data Behind the Post-Purchase Gap2

The Post-Purchase Gap_data_arbelle

⥭ Why Brands Miss the Opportunity

Many post-purchase journeys were designed around operational efficiency rather than customer growth.

Order confirmations, shipping updates, and review requests are easy to automate, making them the default communication sequence for many retailers. Personalization, on the other hand, requires brands to understand what customers bought, what they might need next, and when those recommendations are most relevant.

As a result, post-purchase communication often becomes generic, even though every completed order provides valuable signals about future purchasing behavior.

Key takeaway
The first purchase should provide direction for the next one. Every completed order offers valuable insight into customer preferences, making post-purchase one of the strongest opportunities to increase repeat purchases, basket size, and customer lifetime value.

III. Why Post-Purchase Upselling and Cross-Selling Is Worth the Investment 

➢ The Cost of Acquiring Customers Keeps Rising

For years, growth in beauty e-commerce was driven by acquisition. Brands invested heavily in paid search, social media, influencers, and marketplaces to bring new shoppers to their stores.

That model is becoming increasingly difficult to sustain.

Customer acquisition costs (CAC) have increased by more than 60% over the past several years, with many beauty brands now spending $90 to $130 to acquire a single customer.3 At the same time, McKinsey’s research4 shows that paid marketing channels have become more saturated, making digital advertising both less effective and more expensive. 

It becomes clear, then, that as acquisition becomes more expensive, every new customer needs to generate more value over time.

This is why customer lifetime value has become one of the most important growth metrics in beauty e-commerce.

➢ Every Conversion Matters More

This shift is particularly important in beauty, where winning the first purchase is far from guaranteed.

According to Dynamic Yield,5 Beauty & Personal Care recorded the highest average shopping cart abandonment rate of any measured industry over the past twelve months (from July 2025-June 2026), at 79.81%. Every completed purchase therefore represents a significant investment of marketing budget, customer attention, and buying intent.

Why Post-Purchase Upselling and Cross-Selling Is Worth the Investment_arbelle
Image: Dynamic Yield by Mastercard. The average shopping cart abandonment rate in Beauty & Personal Care

Yet once that investment pays off, many brands fail to capitalize on it. Fail to build on that initial purchase.

For too many retailers, checkout still marks the end of the customer journey rather than the beginning of a longer relationship. Post-purchase communication often stops at order confirmations, shipping notifications, and review requests.

The result is that these significant acquisition investments often produce only a single transaction, leaving repeat purchases and long-term revenue unrealized.

➢ Existing Customers Are the Greatest Growth Opportunity

Unlike many retail categories, beauty naturally creates opportunities for continued engagement, upsells, and repeat purchases.

Products need replenishment. Customers build routines over time. A foundation purchase can lead to a concealer, setting powder, primer, or brush. A lipstick may inspire complementary shades or an entire look.

When brands actively guide these journeys, the commercial impact can be substantial.

Research6 shows that:

  • 76% of shoppers are more likely to purchase when recommendations are personalized.
  • 78% are more likely to buy again and recommend brands that personalize effectively.
  • Retailers implementing AI-powered personalization report 15-30% revenue growth.

This goes to show that rather than continually replacing customers lost after a single purchase, brands can increase the value of every acquisition by strengthening post-purchase engagement.

✧ E-commerce is becoming the replenishment channel

According to McKinsey,7 online channels are increasingly becoming the preferred destination for shopping and replenishment, not just product discovery. As beauty purchases become more routine and repeat-driven, brands have a growing opportunity to strengthen customer relationships long after the initial sale.

The first purchase should not be viewed as the end of the shopping journey, but as the beginning of an ongoing relationship.

➢ From Transactions to Customer Lifetime Value

The strongest beauty brands are no longer measuring success solely by first-order conversions.

Increasingly, they’re focused on metrics such as repeat purchase rate, time to second purchase, average order value (AOV), and customer lifetime value (CLV). 

According to recent beauty retention benchmarks,8 strong-performing brands achieve repeat purchase rates of 30% to 45%, while top performers often exceed 40%, demonstrating the commercial impact of keeping customers engaged beyond their first order.

Moving customers from a single purchase to a lasting routine requires more than promotional emails or generic product suggestions. It requires understanding what customers bought, what they are likely to need next, and when those recommendations will be most relevant.

➥ Identifying these opportunities is one challenge. Acting on them consistently across thousands or even millions of customers is another.

Understanding what each customer is likely to need next, and delivering that recommendation at the right moment, is difficult to achieve manually. This is where AI-powered personalization is becoming an increasingly important competitive advantage.

➥ Check out our report on how personalization in beauty can be monetized and turned into a profit strategy.

Monetizing personalization report

By analyzing customer behavior, purchase history, product affinities, and replenishment patterns, AI enables brands to deliver timely, relevant recommendations that feel helpful rather than promotional. Instead of treating every customer the same, brands can guide each shopper toward products, routines, and experiences that match their individual needs.

As acquisition becomes more expensive, competitive advantage is shifting from attracting more customers to helping existing customers buy with greater confidence, return more often, and generate more value over time.

IV. Key Beauty AI Solutions for Post-Purchase Upsell and Growth

The opportunity behind post-purchase upsells and growth isn’t new.

Beauty brands have always known that customers may return to replenish products, complete a routine, or explore complementary items. The challenge has been recognizing those opportunities for every customer and acting on them at the right moment.

Historically, that has been difficult to do at scale.

Most post-purchase journeys still rely on predefined email sequences, static product bundles, or broad customer segments. A shopper who buys a foundation may receive exactly the same follow-up as thousands of other customers, regardless of their shade, preferences, purchase history, or browsing behavior.

That approach might work in categories where products are largely interchangeable.

Beauty is different:

  • The right concealer depends on the foundation already purchased.
  • The right blush depends on skin tone.
  • The right lipstick may depend on the customer’s coloring, preferred finish, or the overall makeup look they’re trying to achieve.

In other words, beauty purchases are connected. Traditional recommendation systems often treat them as isolated.

Beauty AI changes that.

Instead of relying on predefined rules, modern beauty AI solutions can analyze customer characteristics, previous purchases, product relationships, browsing behavior, and replenishment patterns to understand what an individual customer is most likely to need next.

More importantly, they can deliver those recommendations when they’re most useful.

Rather than interrupting the customer journey with another promotion, AI helps continue it. Then it goes a step further and makes personalization scalable.

Instead of offering one-size-fits-all suggestions, today’s solutions can support different stages of the customer journey with technologies designed for specific shopping decisions. 

A) Virtual Try-On: Building Confidence Beyond the First Purchase

The first purchase is often only the beginning of the customer’s beauty journey.

After finding a foundation they love, shoppers may wonder how a new lipstick, blush, or eyeshadow will look with it. Instead of leaving those decisions to guesswork, virtual try-on allows customers to explore complementary products on their own face before purchasing.

Research consistently shows that visual confidence drives commercial results. Studies have found that virtual try-on can increase purchase likelihood by as much as 2.4 times.9

virtual-makup-try_on_arbelle 1 (1)

For brands, virtual try-on extends the shopping journey beyond checkout by encouraging customers to continue discovering products with confidence, reducing hesitation while increasing opportunities for cross-category purchases.

B) AI Shade Matching: Turning a Single Purchase into a Complexion Journey

Foundation is rarely the final complexion product a customer needs.

A successful foundation purchase naturally opens the door to concealers, powders, primers, contour products, and other complexion essentials. But these recommendations only work when they are accurate.

AI-powered shade matching analyzes characteristics such as skin tone and undertone to recommend products that are compatible with the customer’s existing purchase. Instead of asking customers to guess which concealer matches their foundation, brands can provide recommendations grounded in individual characteristics.

This precision matters. Research shows that 60%10 of shoppers won’t purchase foundation online without access to a shade-matching tool, highlighting how important confidence is in complexion shopping.

Beyond improving conversion, accurate shade recommendations help reduce mismatched purchases, increase customer satisfaction, and create a stronger foundation for future cross-selling.

C) AI Product Recommendations: From Generic Suggestions to Personalized Guidance

Traditional recommendation engines typically rely on purchase history or products that are frequently bought together.

While useful, these approaches often ignore the context behind a customer’s purchase.

Modern AI recommendation systems can combine browsing behavior, purchase history, product affinities, replenishment timing, and customer preferences to deliver recommendations that are relevant to the individual rather than the average shopper.

This shift is significant. Studies11 show that 76% of consumers are more likely to purchase when recommendations are personalized.

On top of that, 78% are more likely to buy again and recommend brands that personalize effectively, while retailers implementing AI-driven recommendations report 15-30% revenue growth.12

ai makeup recommendations for complete beauty basket_arbelle

The result is a recommendation experience that feels less like marketing and more like expert guidance.

D) Look-Based Recommendations: From Individual Products to Complete Looks

One of the newest developments in beauty AI moves beyond recommending individual products altogether.

Rather than suggesting a single complementary item, look-based recommendation engines analyze a customer’s facial features, coloring, existing purchases, and aesthetic preferences to curate complete makeup looks across multiple categories.

This reflects how customers naturally shop.

Few shoppers think in terms of isolated SKUs. They’re trying to achieve a polished everyday look, a professional appearance, or an evening makeup style. Recommending coordinated product combinations helps customers reach those outcomes more easily while increasing basket size organically.

For brands, this approach creates value on several levels:

  • Higher average order value through coordinated multi-product purchases
  • Stronger purchase confidence because recommended products are designed to work together
  • More opportunities to introduce customers to categories they may not have considered independently
personalized makeup recommendations_look finder_arbelle

Instead of asking customers to build a routine product by product, brands help them discover an entire look in a single guided experience.

E) Intelligent Replenishment: Reaching Customers at the Right Moment

Timing is just as important as relevance.

Even the most accurate recommendation is unlikely to convert if it’s delivered too early or long after a product has been used.

AI can estimate replenishment cycles based on previous purchases, product type, usage patterns, and customer behavior, enabling brands to reach customers when they’re most likely to need a replacement.

Rather than sending generic promotional emails, brands can provide timely reminders that feel genuinely useful.

For products with predictable replenishment cycles, such as foundation, mascara, skincare, or everyday complexion products, this creates a natural reason for customers to return while strengthening long-term loyalty.

V. Upselling Works Best When It Feels Like Guidance

One of the biggest misconceptions about post-purchase upsells is that they’re primarily a sales tactic.

In reality, the most effective beauty upsells don’t feel like upsells at all. They feel like good advice.

Customers rarely visit a beauty brand hoping to buy as many products as possible. They want confidence that they’re making the right decisions, trying to answer some practical questions:

  • Did I choose the right shade?
  • What works well with this product?
  • What should I use next?

Brands that answer these questions naturally create more opportunities for additional purchases because they’re reducing uncertainty rather than increasing pressure.

➥ Consider a simple example:

A customer purchases a foundation. Now, a traditional recommendation might say:

< Customers also bought this concealer. >

It’s a perfectly reasonable suggestion, but it provides very little context.

Now compare that with a recommendation that says:

< This concealer matches the undertone of your foundation and provides additional coverage where foundation alone is often not enough. >

The product hasn’t changed. The timing hasn’t changed. Only the context has.

The difference is that the recommendation explains why it matters.

Instead of encouraging customers to buy more, it helps them achieve a better result.

The same principle applies across beauty.

A customer who buys a red lipstick may appreciate guidance on a complementary lip liner. Someone purchasing a bronzer may benefit from a brush designed for that formula. Eyeshadow, eyeliner, and mascara create a complete eye look rather than separate purchases.

The strongest post-purchase upsells work because they are rooted in customer outcomes rather than promotional campaigns.

When upselling becomes guidance, higher average order values become a consequence of better decision-making, not the objective customers experience.

✧ Key insight

  • The best beauty upsells don’t answer the question “What else can we sell?”
  • They answer the question “What will help this customer get the best result?”

Modern beauty e-commerce offers customers more choice than ever before. A single product category may include dozens of shades, finishes, undertones, and formulations. While this variety gives shoppers greater freedom, it also increases the effort required to make confident decisions.

Effective post-purchase guidance doesn’t reduce choice. It makes that choice easier to navigate.

VI. How to Build an AI-Powered Post-Purchase Strategy

By this point, the opportunity is clear. The challenge is turning it into a strategy that delivers measurable business results.

The strongest post-purchase experiences don’t rely on a single technology or campaign. They combine the right solutions at the right moments to help customers make better decisions throughout their shopping journey.

For beauty brands, there are four principles worth keeping in mind.

1. Start With Customer Needs, Not Products

Customers don’t think about upsells. They think about solving a problem.

Whether they’re looking for a matching concealer, wondering if a lipstick suits them, or replacing an empty foundation, every recommendation should answer a real customer need rather than simply promote another product.

2. Match the Technology to the Decision

Different shopping decisions require different types of support.

A customer choosing a foundation shade has different needs from someone exploring complementary products or replenishing a favorite mascara. Selecting the right technology for each decision creates a more relevant and helpful experience.

For example:

Match the Technology to the Decision_table

3. Prioritize Relevance Over Volume

More recommendations don’t necessarily lead to more sales.

Customers are far more likely to engage with recommendations that are timely, personalized, and clearly connected to products they already own or the goals they’re trying to achieve.

The objective isn’t to increase the number of recommendations. It’s to increase their usefulness.

4. Measure Long-Term Customer Value

Don’t judge the success of a post-purchase strategy by a single transaction.

Brands should evaluate how AI-powered experiences influence repeat purchases, average order value, customer lifetime value, product attachment rates, and return rates over time.

These metrics provide a much clearer picture of whether post-purchase engagement is creating lasting customer relationships.

VII. Putting Beauty AI into Practice 

Throughout this report, we’ve explored how beauty AI can strengthen post-purchase engagement by increasing purchase confidence, improving personalization, and helping customers make better buying decisions.

In practice, these outcomes aren’t achieved through a single feature or campaign. They come from combining complementary technologies into one connected customer experience.

  • Individually, each of these technologies solves a specific customer challenge.
  • Together, they create a connected beauty experience that guides shoppers before, during, and after every purchase, helping brands increase average order value, encourage repeat purchases, reduce returns, and build stronger long-term customer relationships.

This is the direction in which beauty commerce is evolving: away from isolated product recommendations and toward intelligent, end-to-end shopping experiences.

✧ Beauty AI Solutions by Arbelle

After exploring the strategies and technologies behind successful post-purchase engagement, the next step is choosing solutions that fit your business goals.

Arbelle combines multiple AI-powered experiences into a single beauty platform, enabling brands to support customers across the entire shopping journey.

  • Virtual Try-On for realistic makeup visualization
  • AI Shade Finder for accurate complexion recommendations
  • Look Finder for complete, personalized makeup looks
  • AI Product Recommendations for intelligent cross-selling and upselling
  • Beauty Analytics for actionable customer and product insights

Whether your priority is increasing basket size, improving purchase confidence, reducing shade-related returns, or strengthening customer loyalty, these technologies can work together to create a more connected and profitable beauty experience.

Want to see how these solutions work in practice? Contact Arbelle for a personalized demo and discover how beauty AI can support your post-purchase strategy.

Sources:

1,2 Shipfusion. The DTC Delivery Files: Cosmetics Edition. PDF download. Published: August, 2025.

3 Eightx. “Average CAC by Ecommerce Vertical 2026: Beauty $110, Apparel $90, Food $75. Available online.” Published: March 12, 2026. Available online.

4 McKinsey & Company. “State of Beauty 2025: Solving a shifting growth puzzle.” Published: June 9, 2025. Available online.

5 Dynamic Yield by Mastercard. “The average shopping cart abandonment rate globally is 77.54%.” Accessed: July, 2026. Available online.

6 Arbelle. “Monetizing Personalization in Beauty: Trends, Tech, and Growth Potential for Modern Beauty Brands.” Published: August, 2025. Available online.

7 McKinsey & Company. “State of Beauty 2025: Solving a shifting growth puzzle.” Published: June 9, 2025. Available online.

8 Mage. “Beauty & Skincare Repeat Purchase Rate Benchmarks for 2026.” Published: February 18, 2026. Available online.

9 TechCrunch. “Snap upgrades its AR Shopping features with real-time pricing, more product details.” Published: January 26, 2022. Available online.

10 Axiology. “How to Choose the Right Foundation Shade.” Published: October 15, 2025. Available online.

11 McKinsey & Company. “The value of getting personalization right—or wrong—is multiplying.” Published: November 12, 2021. Available online.

12 Number Analytics. “8 Stats Proving AI Revolutionizes Retail & E-commerce Markets.” Published: March 27, 2025. Available online.

Frequently Asked Questions

Frequently Asked Questions

1. What is a post-purchase upsell?

A post-purchase upsell is a personalized recommendation made after a customer completes an order. Rather than encouraging an additional purchase through discounts alone, effective post-purchase upsells help customers discover complementary products, complete a beauty routine, or replenish products when they are likely to need them.

2. Why are post-purchase upsells important for beauty brands?

Acquiring new customers is becoming increasingly expensive. Post-purchase upsells help beauty brands increase average order value (AOV), encourage repeat purchases, strengthen customer loyalty, and generate greater customer lifetime value (CLV) from existing customers.

3. What is a post-purchase experience?

A post-purchase experience includes every interaction a customer has with a brand after completing an order. This can include order updates, customer support, personalized recommendations, replenishment reminders, loyalty programs, and follow-up communications designed to strengthen the customer relationship and encourage future purchases.

4. How can beauty brands increase post-purchase engagement?

Brands can improve post-purchase engagement by continuing to guide customers after checkout through personalized recommendations, virtual try-on experiences, shade matching, replenishment reminders, loyalty programs, and educational content that helps customers get more value from their purchase.

5. How do you create personalized post-purchase journeys?

Personalized post-purchase journeys use customer data such as previous purchases, browsing behavior, product preferences, and replenishment timing to deliver relevant recommendations at each stage of the customer relationship. The goal is to provide helpful guidance rather than generic promotions.

6. Which AI technologies support post-purchase growth in beauty?

Several AI-powered technologies can strengthen post-purchase performance, including Virtual Try-On, AI Shade Matching, personalized product recommendations, look-based recommendation engines, intelligent replenishment, and customer analytics. Together, these solutions help brands deliver more relevant experiences and encourage repeat purchases.

7. What is the difference between cross-selling and post-purchase upselling?

Cross-selling recommends complementary products that enhance the original purchase, while upselling traditionally encourages customers to purchase a higher-value alternative or additional products. In beauty e-commerce, post-purchase upselling often combines both approaches by recommending relevant products that improve the customer’s overall routine or look.

8. Can AI improve repeat purchases in beauty e-commerce?

Yes. AI helps brands deliver more relevant recommendations, reduce purchase uncertainty, identify replenishment opportunities, and personalize customer journeys. These capabilities encourage customers to return more often and increase long-term customer value.

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