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As an e-commerce professional running a Shopify store, one of your main KPIs is to generate new customers. But then, the real challenge kicks in: retaining them. At first glance, if your repeat customers are making additional orders, it may seem like everything is going smoothly. However, not all repeat customers are equally valuable when it comes to growing your store profitably.

So, how can you tell if your repeat customers are actually contributing positively to your bottom line.

Why Repeat Customers Matter: Not All Returning Buyers Drive Profit

Many stores assume that repeat buyers automatically mean higher profits, but that’s not always the case, there’s a big difference between a returning customer and a repeat customer.

  • Returning customers might make a second purchase but never come back again.
  • Repeat customers are loyal shoppers who buy from you consistently over time

Some returning customers might not spend enough to justify their acquisition cost, while others may only come back for discounts, eating into your margins. Without the right analysis, it’s easy to mistake increased order volume for real growth.

To truly understand whether your repeat customers are driving profit, you need to go beyond surface-level sales numbers. A more structured approach—like cohort analysis—helps uncover whether your returning customers are actually valuable over time.

How to Use Cohort Analysis to Track Repeat Customer Performance

A Cohort analysis allows you to group customers based on shared characteristics, such as the month they made their first purchase. By tracking how each cohort behaves over time, you can measure not just how often customers return, but whether they’re actually driving profit.

Instead of viewing customer retention as a single percentage, this method helps you answer important questions:

  • Are your repeat customers spending more over time?
  • How long does it take for a new customer to become profitable?
  • Do certain acquisition channels bring in more valuable customers than others?

How to Perform a Cohort Analysis for Repeat Customers

1. Gather Your Data

To perform a cohort analysis, you’ll need key data points, including:
✅ Customer acquisition dates
✅ Purchase history and order frequency
✅ Average order value (AOV)
✅ Gross profit per customer

Collecting this data manually can be time-consuming. Tools like StoreHero automate this process, providing insights at a glance and helping you make data-driven decisions faster.

2. Segment Customers into Cohorts

Group your customers based on when they made their first purchase (e.g., those new customers from your last Black Friday Campaign). You can also create cohorts based on:


🔹 Behavior: First-time buyers vs. repeat buyers
🔹 Geography: Customers from different countries or regions (e.g. Ireland, US, UK, Australia, etc)
🔹 Product Category: Customers who purchased specific types of products (e.g., skincare vs. apparel)
🔹 Acquisition Channel: Facebook Ads vs. organic traffic vs. email marketing

Segment Customers into Cohorts

3. Track Their Performance Over Time

Analyze how each cohort behaves after 3, 6, 9, and 12 months:
📈 Are they coming back to place more orders?
💰 Are they spending more per purchase over time?
📊 Are they generating enough profit to justify their acquisition cost?

By tracking these trends, you’ll spot which customer segments bring the most value and where you need to improve retention efforts.

3. Track Their Performance Over Time

4. Measure Profitability, Not Just Revenue

Many brands focus only on repeat purchase rates, but profitability matters more. Beyond just tracking revenue, focus on the profit generated by each cohort.

 For example, after 12 months, does the profit per customer increase, or is it stagnating?

Example:

Suppose you run an online store and track your cohorts for the past year. In January, you acquired 600 new customers at an acquisition cost of €15 each. After one month, 16% of them returned and spent an average of €26, generating a gross profit.

Now, you track these customers over the next several months. By the time they reach 12 months, the average profit per customer has grown to €31. This shows that your repeat customers are getting more valuable as time goes on, generating additional revenue and increasing your profit margins.

This kind of cohort data is essential for deciding how much you should be willing to invest in acquiring new customers. If you know that the lifetime value (LTV) of a customer will reach €31, you can afford to spend more on acquisition while remaining profitable.

📹  Watch this video for a deeper example.

Example of Cohort Analysis - Repeat Customers

Key Metrics to Focus On for Repeat Customers

When tracking repeat customer performance, keep an eye on these essential metrics:

  • Repeat Purchase Rate: This measures how often customers return for subsequent purchases. A higher repeat purchase rate indicates stronger customer loyalty.
  • Customer Lifetime Value (LTV): The total profit a customer generates over their entire relationship with your store. A growing LTV means your repeat customers are becoming more valuable over time.
  • Profitability by Cohort: Track how much profit each cohort generates at different stages (e.g., after 3, 6, 9, and 12 months) to understand if repeat customers are consistently contributing to profit.
  • Average Order Value (AOV): The average spend per order. Increasing the AOV for repeat customers boosts overall profitability.

How to Improve Repeat Customer Performance? 

To optimize your repeat customer performance, consider these tactics:

  1. Customer Retention Programs: Use loyalty programs, personalized emails, or exclusive offers to incentivize customers to return. When you make repeat buying easier and more rewarding, customers will come back more frequently.
  2. Upselling and Cross-Selling: Boost the average order value (AOV) by suggesting relevant products to your repeat customers. This increases the value of each repeat purchase.
  3. Personalized Experiences: Segment your repeat customers based on purchase behavior and preferences. Provide tailored recommendations and offers that resonate with them.
  4. Subscription Models: If your product lends itself to it, consider implementing a subscription service. This creates recurring revenue and locks in repeat customers for the long term.

By analyzing repeat customer performance with cohort analysis, you gain a clearer picture of how valuable your returning customers really are. This allows you to make informed decisions about your customer acquisition strategies, retention efforts, and pricing models—ultimately increasing your profitability over time.

Start tracking your repeat customer behaviour today and use cohort analysis to ensure that they’re not just coming back, but coming back profitably.

If you’re looking for a way to make cohort analysis easier and more insightful, tools like StoreHero offer powerful features to help you track repeat customer behavior and profit over time. Ready to see your customer data in action? Give it a try today!

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