Ecommerce Customer Value: The Key to Long-Term Growth

To ensure long-term growth and profitability, ecommerce businesses should focus on building long-term customer relationships rather than just pursuing short-term sales.

A metric that reveals the complete economic value of customer relationships over a period, is called customer lifetime value (CLV).

In this article, you will learn more about ecommerce customer value, how to (really) calculate it, as well as factors and strategies that can influence your ecommerce CLV.

Key takeaways:

• To calculate the actual profit potential of each customer, your CLV formula needs to have the gross margin and customer churn rate.
• Customer retention rate, average order value (AOV), and purchase frequency influence the CLV.

Retaining an existing customer is sometimes over 8 times more profitable than acquiring a new one.

To draw this conclusion, we took:

• The average product price as $115, according to Oberlo’s study.
• The amount one customer spends over a period as $750 (calculated as $115 average purchase value x 5 purchases per year x 3-year lifespan) as an example.
• The average customer acquisition cost of $86, as per FirstPageSage’s study.

Therefore, to match the $750 customer lifetime value from retaining one customer, the business would need to acquire approximately 9 new customers ($750 CLV / $86 CAC = 8.72 customers).

Understanding and maximizing customer value leads to sustainable growth in ecommerce, as your old customers cost you less while they bring more revenue for your business in the long run.

Plus, increasing your CLV doesn’t only bring you more revenue, it serves as a customer compass that fine-tunes your ideal customer persona, improves products and services, and boosts loyalty and brand awareness.

What is customer value in ecommerce?

Customer value, particularly customer lifetime value (CLV), refers to the total revenue a business generated or can expect to generate from a customer throughout their relationship. 

CLV includes factors like average order value, purchase frequency, and customer lifespan, to precisely measure how much an existing customer has taken part in the total revenue of one business.

We can divide the CLV into historical and predictive metrics. 

Historic customer value is more straightforward and takes into account past purchases, while predictive lifetime value predicts how much a customer will spend on your business, with metrics such as acquisition costs, business overheads, etc.

CLV has an effect on revenue, profitability, and marketing strategies. How?

Customers with higher CLV generate more revenue over time through repeat purchases. The brand “Edgar & Cooper” get almost 50% of their revenue from old customers, as per this case study.

CLV helps businesses understand how much they can afford to spend on acquiring new customers (CAC). A healthy CLV to CAC ratio (ideally between 3:1 and 5:1) indicates that the revenue generated from customers significantly exceeds the cost of acquiring them, ensuring profitability.

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With CLV ecommerce businesses can shape their strategies to better target their ideal customer personas, nurture existing relationships, and invest in retaining strategies. With a new loyalty program, “Esmi” managed to enroll 58% of its customer base, as per this case study.

How to calculate customer lifetime value (CLV)

Let's break down the basic customer lifetime value formula:

Average Purchase Value×Purchase Frequency)×Customer Lifespan

Formula components:

• Average Purchase Value: The mean amount spent per transaction
• Purchase Frequency: How many times a customer buys in a given period
• Customer Lifespan: How long someone remains an active customer

To illustrate this with a realistic example from ecommerce, consider a business where customers spend an average of $50 per purchase and make about 5 purchases per year over a typical lifespan of 3 years. 

In this case, the CLV would be $750 ($50 × 5 × 3)

This is a simplified model that makes several assumptions:

1. Customer spending and purchase frequency remain consistent over time
2. Doesn't factor in customer acquisition costs, and ignores the time value of money (treating future purchases as equal in value to present ones)
3. Doesn't account for seasonal variations and assumes linear customer behavior. 

This basic CLV calculation provides a useful starting point for understanding customer value and making business decisions, but the advanced CLV formula with gross margin provides more precise data.

Advanced CLV formula with gross margin

Let’s break down the advanced CLV formula:

CLV=(Customer Churn Rate xAverage Purchase Value×Purchase Frequency)×Gross Margin

This formula improves upon the basic version by including two dynamic ecommerce business metrics:

• Customer Churn Rate: Measures the percentage of customers who stop doing business with you over time, effectively replacing the simpler “Customer Lifespan” metric with a more dynamic measure. 
• Gross Margin: The percentage of revenue, retained after direct costs of goods sold, adds a new profitability dimension that the basic formula overlooks entirely.

Using our previous example but adding these new components, let's say:

• Average Purchase Value = $50
• Purchase Frequency = 5 purchases per year
• Annual Churn Rate = 25% (meaning the average customer stays for 4 years)
• Gross Margin = 60%

The calculation would be: CLV = ($50 × 5 × 4) × 0.60 = $1,000 × 0.60 = $600

This $600 CLV is more realistic than the $750 we calculated in the basic formula because it accounts for the actual profit potential of each customer, not just revenue. 

While the basic formula might suggest higher customer value ($750), it doesn't consider that a significant portion of that revenue (40% in this case) goes to cover direct costs. 

Plus, the Churn Rate metric instead of a fixed Customer Lifespan provides a more dynamic and realistic view of customer behavior, as it's based on actual customer retention data rather than assumptions about how long customers might stay. 

Understanding customer churn

Customer churn is a metric representing the rate at which customers stop doing business with a company over a given period. 

As shown in the advanced formula, it is a metric that directly impacts Customer Lifetime Value (CLV) through an inverse relationship — the lower the churn rate, the higher the CLV. 

For example, reducing churn from 30% to 20% means that instead of losing nearly one-third of customers annually, you're retaining more customers who continue to generate revenue.

Let's break down the math to show why this matters so much:

With a 30% churn rate:

• Average customer lifetime = 1/0.30 = 3.33 years
• If Average Purchase Value = $50, Frequency = 5/year, Margin = 60%
• CLV = ($50 × 5 × 3.33) × 0.60 = $500

With a 20% churn rate:

• Average customer lifetime = 1/0.20 = 5 years
• Same other values
• CLV = ($50 × 5 × 5) × 0.60 = $750

Take a look at the table that shows how CLV varies across different churn rates and gross margins. The darker blue colors indicate higher CLV values.

As you can see, even small improvements in either churn rate or gross margin can significantly impact CLV. 

This visualization demonstrates why ecommerce brands should invest heavily in both customer retention (to reduce churn) and operational efficiency (to improve margins).

Pro tip: The relationship isn't linear — reducing churn from 50% to 40% has a different impact than reducing it from 20% to 10%, consequently, early-stage improvements in customer retention often have the best results.

Factors that influence customer value in ecommerce

Customer value in ecommerce is influenced and shaped by three interconnected factors: customer retention rate, average order value (AOV), and purchase frequency. 

These metrics work together as the “cornerstones” of sustainable ecommerce business growth, determining how much revenue a customer generates during their interaction with the brand.

When optimized together, they create a multiplier effect – higher retention leads to more frequent purchases, which typically correlates with increased average order values, ultimately ensuring sustainable revenue growth.

Customer Retention Rate

Customer retention rate is the percentage of customers who continue to do business with a company over a specific period, typically measured yearly.

It's calculated by taking the number of customers at the end of a period, subtracting new customers acquired during that period, and dividing by the number of customers at the start. 

If a company starts with 1,000 customers, gains 200 new ones, and ends with 800 customers, the retention rate would be 60% ((800-200)/1,000).

Customer retention rate directly boosts CLV, for example, if your retention rate improves from 70% to 80%, it leads to:

• The average customer lifespan increases from 3.3 years to 5 years
• With a $50 average purchase and 5 purchases/year: CLV jumps from $825 to $1,250

Plus, retained customers typically buy more often as they become familiar with your brand, and they are likely to participate in loyalty programs and respond to promotional offers

 If retained customers increase purchases from 5 to 6 times per year, there is a significant increase:

• Old CLV: 5 purchases × $50 × 3.3 years = $825
• New CLV: 6 purchases × $50 × 3.3 years = $990

Average Order Value (AOV)

Average Order Value (AOV) represents the average amount spent each time a customer makes a purchase. It is calculated by dividing total revenue by the number of orders in a given period. 

AOV multiplier in the CLV formula, as increasing AOV directly amplifies the value of each customer interaction. 

For example, if your AOV increases from $50 to $60, and a customer makes 5 purchases per year over 3 years, their CLV would jump from $750 to $900.

Here are five strategies that improve AOV for ecommerce brands:

Key strategies to improve AOV include:

1. Bundle products

Instead of making one purchase, you can easily increase the order value of a cart by adding bundle offers.

• Create complementary product packages
• Offer “complete the look” recommendations
• Bundle popular items with accessories

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Source: Lively

If customers leaving during the checkout phase, take a look at exit-intent pop-up tools.

2. Offer volume-based discounts

To increase the average order value, you can make it irresistible to not buy in bulk.

• Implement tiered pricing structures
• Offer bulk purchase incentives
• Set free shipping thresholds over a certain amount

Source: Pretty Litter 

3. Try upselling and cross-selling

Upselling and cross-selling will reveal products similar to the ones your customers want, increasing the chance of them buying more.

• Suggest premium product versions
• Recommend complementary items
• Display “frequently bought together” items

Source: Crate&Barrel

4. Have strategic pricing

A bit of a risky tactic is strategic pricing, which helps you ensure a certain amount for each purchase.

• Create anchor pricing with premium options
• Implement minimum order values
• Offer installment payment options

Source: Alfred

5. Give personalized recommendations

Personalized instead of generic recommendations have a greater chance of increasing the order value since you are offering something the person most likely wants or needs.

• Use AI-driven product suggestions
• Create personalized shopping experiences
• Target recommendations based on browse/purchase history

Source: Dossier

Purchase Frequency

Purchase frequency measures how often customers make repeat purchases within a specific timeframe, typically calculated as the number of orders per customer annually. 

Increasing purchase frequency has a powerful impact on customer value, just like AOV. For example, if a customer's annual purchases increase from 4 to 6 times, with an average order value of $50 over 3 years, their CLV grows from $600 to $900.

Here are five strategies that improve purchase frequency:

1. Have a loyalty program

With a loyalty program that rewards customers with each purchase, you are increasing the likelihood of them coming back. To increase purchase frequency you can:

• Implement point-based reward systems
• Offer tier-based benefits
• Create VIP early access to sales

A fashion ecommerce brand called Lively boosted average customer lifetime value by 39% once they implemented a loyalty program. Their loyalty program gives away a point for each dollar spent, as well as extra points for referrals and birthdays.

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Source: Lively

2. Do strategic email marketing

Communicating with your customers regularly via email, can help increase their purchase frequency, and here is how:

• Set up post-purchase nurture flows
• Set cart abandonment reminders
• Send personalized product recommendations

• Create targeted promotions based on purchase history
• Send teaser emails for product launches

Source: Bark

Check out this guide on improving shopping cart abandonment.

3. Offer subscription models

To ensure you have recurring payments from customers, you can offer subscription models, like:

• Introduce subscribe-and-save options
• Create membership programs
• Develop auto-replenishment services

Source: Pretty Litter 

5. Run limited-time offers

Running limited-time offers helps acquire more purchases during a specific time frame. You can:

• Run flash sales
• Create seasonal promotions
• Implement scarcity-based marketing

Source: Nectar

Strategies to increase customer lifetime value

In the following section, we’ll go over the four strategies that can increase customer lifetime value for your ecommerce brand:

Learn more about ecommerce growth strategies in this article.

1. Personalization and customer experience

Seeing relevant product recommendations and timely reminders prompts customers to purchase again.

Plus, relevant, personalized experiences reduce churn by making customers more connected to the brand and its offers.

Therefore, a positive customer experience drives loyalty and CLV, but how can you make an effort to provide the best customer experience? Here are some recommendations:

• Segment customers by purchase history to trigger automated emails (e.g., sending targeted offers to “skincare enthusiasts” who bought skin products 3+ times) using a CRM.
• Uses AI to personalize product sorting (e.g., showing winter coats first to cold-weather shoppers) or implement a website chatbot that suggests bundles instead of singular products.
• Use geotargeting (personalizing a website based on visitor geolocation) to show the correct pricing, content, and relevant products  to increase sales, and improve the user experience.

Learn more about geomarketing in this guide.

Loyalty and rewards programs

Creating a successful loyalty program requires careful attention to three core elements: value exchange, digital integration, and data-backed optimization.

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Source: Lively

1. Value exchange 

A well-designed value exchange starts with quickly attainable rewards, typically within a customer's first 2–3 purchases, creating immediate engagement. 

Your loyalty program should have transparent point values and a clear redemption process, eliminating confusion.

To keep customers actively participating, offer multiple earning opportunities beyond purchases – such as product reviews, referrals, and social media shout-outs.

2. Digital integration

A fully functional mobile app or platform that provides real-time tracking of points and status, keeping members engaged through immediate feedback. 

With personalized email marketing, you can deliver timely reward reminders and relevant offers, while social media integration adds a social proof element that encourages customer participation.

To learn more about location-based reminders, check out the geofencing guide.

3. Data-backed optimization

By analyzing purchase patterns, ecommerce companies can personalize rewards based on individual buying habits. 

Tracking engagement metrics reveals which rewards most effectively drive repeat purchases, while regular customer surveys provide direct feedback for loyalty program optimization.

Here are some common pitfalls to avoid when making your loyalty program:

• Overly complex rules
• Rewards that are too difficult to achieve, or insufficient value propositions that fail to motivate customers
• Technical implementation challenges like poor platform experiences or delayed point updates

Here are the three major loyalty program types compared:

Program type

Structure

Complexity

Customer value proposition

Data collection

Example

Points program

X$ spent = X points

Medium

Clear value exchange, flexible rewards

Spending patterns

Newegg

Tiered VIP

Gold/Silver/Bronze

levels based on spend

High

Status recognition, increasing benefits

Detailed purchase history

Petco

Referral

Rewards for bringing new customers

Medium

Mutual benefits

Affiliate/network effects

Heights

To track referrals properly, make sure to check out this full guide on tracking links.

Effective upselling and cross-selling

Upselling is a term for encouraging customers to purchase a higher-priced variant of your ecomemrce product, while cross-selling is a term for suggesting complementary products.

Here are some practical tips for implementing these strategies to increase AOV:

• Choose the right upsell/cross-sell: Analyze customer behavior to see if it is better to turn to “bundling”, “customization”, or “upgrade”.
• Highlight the benefits > features: Make sure to highlight the benefits of the premium version of the product/additional product, instead of bare features.
• Perfect the timing: Give your customers time to get to know your product before offering add-ons. It is best to try this technique with older customers.
• Help customers upsell themselves: Demonstrate your higher-end offers or complementary products clearly on the check-out page.

Source: The Dollar Shave Club

Customer support and engagement

Customer support is the line between first interactions and long-term profit because 90% of customers say they will most likely make another purchase after a good customer service experience, as per SalesForce’s research.

Here is how to upgrade your customer support and engagement:

• Provide engaging value-packed content through relevant product information, product improvements, latest collections, seasonal discounts, etc.
• Offer high-end customer support through AI chatbots, 24/7 support, omnichannel support, and a how-to knowledge base (if applicable).
• Engage customers with satisfaction surveys, sharing the product roadmap, user-generated content, reviews, etc.

Common mistakes to avoid when calculating or maximizing customer value

Ignoring gross margin, focusing on acquisition, and using inaccurate data, separately and together, create a“ wrong cycle” for business.

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Ecommerce brands are stuck in a cycle where they consistently invest money in the wrong places while missing clear opportunities to increase profit from their most valuable customers.

This isn't just about inefficiency — it's about concrete losses in profit that could have been reinvested in growth.

Ignoring gross margin

Ignoring gross margin while chasing high-revenue customers can lead to investing heavily in customer segments that generate minimal profit or even losses.

 For example, a brand might spend $200 acquiring customers who generate $1000 in revenue but only $150 in gross profit, creating a net loss of $50 per customer. 

Not factoring in gross margin when calculating CLV creates a deceptively optimistic view of customer value by focusing on revenue rather than actual profit. 

Here's a concrete example: imagine two customers, both spending $1,000 annually over three years, suggesting a basic CLV of $3,000 each. 

However, Customer A buys high-margin products with a 60% gross margin, while Customer B purchases low-margin items with only a 25% gross margin.

True CLV calculation with margins:

• Customer A: $3,000 × 0.60 = $1,800 actual value
• Customer B: $3,000 × 0.25 = $750 actual value

This difference is critical because it affects key business decisions:

• Marketing spend (might overspend acquiring low-margin customers)
• Retention efforts (focusing resources on seemingly “valuable” customers who generate little profit)
• Product development (developing products for customer segments that appear valuable but aren't)
• Inventory management (stocking up on high-revenue but low-profit items)

Focusing solely on new customer acquisition

Focusing too heavily on acquisition compounds this problem — if the company spends $300,000 on marketing to acquire new customers while neglecting a 30% churn rate among profitable existing customers, they're essentially throwing away $90,000 in reliable profit

Retained customers create compounding value:

• They require less support (familiar with products)
• Have higher average order values (trust the brand more)
• More likely to refer others (reducing acquisition costs)
• Provide valuable feedback for product improvement
• Less price sensitive (value relationship over cost)

This makes retention initiatives like loyalty programs, personalized communication, and strategic upselling not just cost-effective but crucial for sustainable business growth.

Using inaccurate data

Using inaccurate data further amplifies these issues by directing resources toward the wrong initiatives — like building retention programs for customer groups that have already churned.

Ecommerce businesses frequently fall into the trap of using outdated customer behavior metrics, such as relying on last year's purchase frequency data despite significant market changes, or not updating customer segment profiles as buying patterns shift. 

Attribution errors further compound these issues – businesses often double-count sales across different channels or misattribute repeat purchases as new customer acquisitions.

To ensure accuracy, implement regular data audits, use unique customer identifiers across channels, update customer behavior metrics quarterly, and account for returns and refunds in calculations. 

Conclusion

Customer Lifetime Value (CLV) is an important metric that directly impacts your ecommerce store’s long-term success and sustainable growth. 

Understand and actively manage CLV, to make more informed decisions about resource allocation, customer acquisition strategies, and retention programs.

The key is to view CLV not as a static number, but as a dynamic metric that reflects the health of your customer relationships and the effectiveness of your business strategies over a period of time.

Remember to regularly monitor your CLV calculations, ideally reviewing metrics monthly and conducting deeper analyses quarterly. This consistent attention allows you to spot trends early, adjust strategies promptly, and maintain a competitive edge. 

 FAQ’s

What’s the best way to track CLV?

Use your CRM to track purchase history, frequency, and average order value, and then add the formula for CLV to your spreadsheet and calculate automatically.

How often should I update my CLV calculation?

CLV calculations should be updated regularly, at least quarterly, to account for changes in customer behavior and business performance. Some businesses update CLV monthly or even weekly to closely monitor trends.

What’s a good CLV benchmark in ecommerce?

A good CLV benchmark in ecommerce is around $168, according to Metrilo’s study. However, it highly depends on your average order value, margin, and the industry you are in.

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