Keeping customers after the first purchase is one of the most complex parts of running an online brand. You spend money and time getting people in, but many leave without coming back. Without a clear way to measure how many stay, you’re left guessing which tactics work and which waste budget.

The customer retention rate formula solves that problem. It shows the percentage of customers who continue to make purchases over a specified period. Tracking this number helps you see if loyalty programs, follow-ups, and offers are actually building repeat sales and long-term value.

In this blog, you’ll learn what the customer retention rate measures, how to calculate it step by step, which data to collect first, how to compare it with current benchmarks, how it connects to lifetime value, which supporting metrics to track, common mistakes to avoid, and a simple case study to see it in action.

Key Takeaways:

• Measuring the number of customers you retain over time helps you determine if your retention efforts are practical.
• A clear formula (CRR) eliminates guesswork and ensures consistent tracking across months or quarters.
• Comparing your retention rate with industry averages reveals your current standing and what you should aim for.
• Retention is directly linked to customer lifetime value, which in turn affects revenue and growth planning.
• Testing and refining loyalty tactics with clean data helps avoid mistakes that can mask real performance.

What the Customer Retention Rate Measures and Why It Matters

Customer Retention Rate (CRR) measures the share of customers you keep over a chosen time period. It indicates whether people who have purchased from you once return and become repeat customers. This metric tells you if your offers, service, and follow-up are keeping customers rather than losing them.

Keeping more customers has a big financial upside. Multiple industry analyses indicate that small increases in retention can significantly multiply profits for the business. That makes CRR a high-leverage metric for measuring the value of loyalty, repeat purchase tactics, and reactivation efforts.

The Exact Customer Retention Rate Formula (Step-By-Step)

When you see the acronym CRR, expand it to Customer Retention Rate. Use this formula:

CRR = ((E − N) ÷ S) × 100

Where:

• S = number of customers at the Start of the period.
• E = number of customers at the End of the period.
• N = number of New customers acquired during the period.

This form excludes new customers, enabling you to track how many of your initial customers remain with you.

Calculation Example:

Pick a time period you track (month, quarter, or year). Example values for one month:

• S (start) = 200 customers.
• N (new during the month) = 30 customers.
• E (end) = 210 customers.

Step 1: Subtract the number of new customers from the total count: 210 − 30 = 180.

Step 2: Divide that retained number by the start count: 180 ÷ 200 = 0.9.

Step 3: convert to percent: 0.9 × 100 = 90%.

So CRR = 90% for that month. This means 90% of the customers you began the month with were still customers at the end of it. Use the same arithmetic for quarterly or yearly windows.

Data You Must Have Before You Calculate

1. A clear time window (month, quarter, or year). Pick one and stay consistent so you can compare periods.
2. The count of customers at the start of that window (S). This should be unique customers, not orders.
3. The count of customers at the end of that window (E). Again, unique customers.
4. The number of truly new customers acquired during the window (N). Exclude reactivated or returning older customers from this number.
5. A consistent rule for who counts as a “customer” (purchase threshold, active subscription, or other) and the data source you trust (CRM, store platform, billing system). Use the same rule each period to avoid misleading swings. 

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Begin tracking monthly and maintain the same customer definition for at least three months to identify clear trends. Combine CRR with purchase frequency and average order value to determine if retention improvements also boost revenue per customer. 

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After gathering and applying the formula, you’ll want to see how your results compare to others in your industry. That’s where benchmarks come in.

Benchmarks and What ‘Good’ Looks Like in 2025

Use the table below to compare your CRR to similar industries. The numbers reflect 2025 benchmarks aggregated from industry reports and platform studies:

How to read the table and avoid common traps

• Match what you measure to the same metric in the table. The annual CRR is not the same as a returning-customer rate or monthly active retention rate. Pick one and compare like for like.
• Use cohorts when you run tests. Cohort retention (customers who signed up in the same period) indicates whether a change actually had an impact. Short windows help you learn fast.
• Watch margin effects. Offering heavy discounts to raise retention can harm customer lifetime value (CLV, the revenue expected from a customer over the course of their relationship). If retention rises but CLV falls, rethink the tactic.
• Don’t mix industries or purchase frequencies. Some sectors appear more favorable because purchases are frequent or contracts are long-term. Pick the row that aligns with how often customers buy from you and how you measure retention.

Select the correct metric, compare it to the relevant industry row, and focus on a single, clear cohort test to measure the real impact.

Benchmarks tell you where you stand, but retention doesn’t work in isolation. It directly impacts other key metrics, such as lifetime value and churn.

Also Read: 9 Successful Loyalty Program Examples to learn from in 2025

How Retention Connects to CLV, Churn, and LTV Forecasting

Retention refers to the percentage of customers who continue to make purchases. It increases CLV (customer lifetime value, also known as LTV) and reduces churn (the rate at which customers stop buying).

Longer retention increases the average customer lifespan and often boosts purchase frequency and average order value, all of which are factors in LTV formulas (AOV × frequency × lifespan). Use cohort retention curves to create more accurate LTV forecasts, rather than relying on single-number estimates. 

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To get a complete picture, you’ll need to look beyond CRR and monitor supporting metrics that reveal customer behavior and revenue impact.

Top 8 Metrics to Track With Retention Rate

Track these eight metrics alongside your retention rate to identify who sticks, who spends, and where to take action:

• Customer retention rate (CRR): percentage of customers retained. Formula: ((End customers − New customers) ÷ Start customers) × 100.
• Churn rate: the percentage of customers lost during a given period. Use the same time window as CRR.
• Customer lifetime value (CLV / CLTV) — projected revenue per customer (AOV × purchase frequency × average lifespan is a simple model. Use CLV with CRR to set retention spend.
• Repeat purchase rate: share of buyers who return, a direct signal of loyalty and program effectiveness.
• Average order value (AOV): revenue ÷ orders. Rising AOV with steady CRR grows revenue per retained customer.
• Purchase frequency/time between purchases: orders per customer and median days between buys; shorter gaps lift CLV.
• Cohort retention: retention by signup or campaign cohort; use it to spot which efforts truly keep customers.
• Net revenue retention (NRR) / revenue churn: dollar-level retention after upsells, downgrades, and churn; tells if retained customers grow or shrink revenue.

Monitor these together each period, and you’ll quickly see whether retention moves are improving customer value or just volume.

Tracking these numbers is useful, but they can be misleading if you make common calculation errors or mix definitions.

Common Mistakes and How You Can Avoid Them

When applying the customer retention rate formula, a few errors can skew your numbers. Here’s what to watch out for and how to fix them:

1. Mixing up user vs. revenue retention

User retention refers to the number of people who stayed, while revenue retention refers to the amount of money that remained.

Fix: Track both separately and compare them side by side.

2. Counting cancellations too fast

A cancellation doesn’t always mean churn.

Fix: Give time for win-back efforts before marking lost.

3. Looking only at overall retention

Retention patterns change at different stages of the customer journey.

Fix: Measure early, mid, and late stages separately.

4. Using inconsistent time frames or segments

Switching periods or mixing groups leads to skewed results.

Fix: Keep time frames and segments consistent in every calculation.

5. Ignoring edge cases

Pauses, refunds, or seasonal accounts can distort results.

Fix: Establish clear guidelines for handling these cases.

Getting these basics right keeps your numbers clean and your retention strategy grounded in reality.

The easiest way to see how the formula works in real life is through an example. Here’s a case study of a brand applying it with measurable results.

Real-World Example & Case Study

A home furnishings brand sought to attract more repeat buyers and establish a clearer path to convert first-time shoppers into returning customers. 

They added a Nector loyalty program that combined points, a branded rewards page, and referral incentives. The program made it easy for customers to earn and redeem rewards, and provided the brand with simple analytics to track program performance.

Results: 

After launching the program, they reported a 70× return on investment, 12.7% of revenue attributed to Nector, and 12.4% of customers signing up for the loyalty program.

Why It Matters for Your Retention Rate:

Those results show two things that move the customer retention rate you calculate with the usual formula (CRR = ((E-N) ÷ S) × 100):

• More customers are reordering, which increases the number of E-customers at the end of the period. A higher signup rate provides you with a pool of members to target with post-purchase flows, thereby reducing the number counted as “lost” between periods.

To measure the impact directly, calculate your retention rate for the cohort before the Nector rollout and for the cohort after rollout using the same time window. The difference shows the program’s CRR lift and ties the revenue gains back to retention.

Case studies show the formula’s impact, but applying it to your own brand often requires the right tools. This is where Nector can help.

Also Read: 2025 DTC Trends: How Shopify Brands Can Stay Ahead with Loyalty and Retention

Boost Retention and Repeat Purchases With Nector

Tracking your customer retention rate formula helps you understand how many customers remain loyal over time. If the number is lower than expected, it often means shoppers don’t feel a strong pull to return. Fixing that usually requires more than discounts; it needs a simple way to keep customers engaged and buying again.

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Nector helps by adding loyalty features that fit right into your store:

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• Centralized Customer Data Portal: Syncs customer profiles, loyalty activity, real-time insights, and analytics in one dashboard. That visibility enables you to act on retention trends more quickly.
• Automated Engagement Tools: Set up automatic emails and prompts to remind customers to reorder or engage again—boosting the “E” in your retention formula.
• Redeem Points at Checkout & Dedicated Rewards Page: Let customers redeem loyalty points during checkout or through a branded rewards page, making repeat buys feel rewarding and effortless.
• Smart VIP Tier Management & Smart Coin Expiry System: Offer tiered rewards and expiration rules to encourage active participation and discourage stagnation.
• Referral and Review Workflows: Built-in referral bonuses and incentives for reviews help bring back dormant customers and attract new ones, positively impacting your retention rates. 

Each feature helps increase the number of customers who stay active by the end of a period (the “E” in the customer retention rate formula), thereby improving your CRR without adding friction.

Conclusion

To measure customer retention, use a clear and consistent formula for retention. Track the same period each time, count unique customers, and exclude only those who are truly new. Watch cohort trends, average order value, and purchase frequency to see if retention drives revenue. 

Compare against the right industry benchmarks to avoid errors such as mixed definitions or seasonal distortions. Retention is most effective when measured carefully and reviewed in conjunction with related metrics.

Nector offers a fully customizable loyalty platform that integrates seamlessly with e-commerce systems, such as Shopify and WooCommerce. It brings together rewards, referrals, reviews, and VIP tiers under one roof, with real-time analytics and automated engagement all designed to help you earn repeat customers without adding operational friction.

‍Book a demo today to see how Nector can help you drive long-term customer loyalty.