Customer Retention Rate Formula: The Complete
Retention & Repeat Purchase Guide
Master the customer retention rate formula for e-commerce and subscriptions: calculate retention, link it to churn and LTV, and improve repeat purchases.
The Customer Retention Rate Formula
Retention = 100 − Churn. Same period for start, end, and new.
Retained customers: those at the end who were already customers at the start (excluding new acquisitions).
Total customers at the beginning of the period. Denominator for the rate.
Percentage of starting customers you kept. Higher is better. Use with churn and LTV.
Quick Example
Start: 600 customers. End: 620. New in period: 100.
Retained = 620 − 100 = 520. Retention = (520 ÷ 600) × 100 = 86.7%
Churn = 100 − 86.7 = 13.3%. Use churn in LTV (lifespan = 1 ÷ 0.133 ≈ 7.5 months).
Understand Who Stays and Who Lapses
StoreRadar shows retention and repeat purchase by segment so you can focus on keeping the customers that matter most.
Customer Retention Rate Formula Variations
Period retention, cohort retention, and revenue retention
Retained = End − New. Same period for start, end, and new. Use for overall health.
Define 'active' (e.g. purchased in window). Track by month 1, 3, 6, 12 for curve.
Use same definition (same cohort/period) for both.
Net revenue retention includes expansion (upsells); gross does not.
Simpler than cohort retention; doesn't show when they came back.
Worked Examples
Step-by-step retention rate calculations
Period Retention Rate
Start of month: 1,000 customers. During month: 120 new customers. End of month: 1,050 customers.
- 1 Customers at start = 1,000
- 2 Customers at end = 1,050
- 3 New customers = 120
- 4 Retained (from start) = 1,050 − 120 = 930
- 5 Retention rate = (930 ÷ 1,000) × 100 = 93%
- 6 Churn = 100 − 93 = 7%
Customer retention rate is 93%; churn is 7%.
You kept 93% of the customers you had at the start. Use for trend and to feed LTV (lifespan = 1 ÷ 0.07 ≈ 14.3 months at 7% monthly churn).
Cohort Retention (Ecommerce)
500 customers made their first purchase in January. In the next 12 months, 175 made at least one more purchase.
- 1 Cohort size = 500
- 2 Retained (repurchased in next 12 months) = 175
- 3 Retention = (175 ÷ 500) × 100 = 35%
- 4 Churn (no repurchase in 12 months) = 65%
35% of the January cohort repurchased within 12 months.
Typical ecommerce retention is 20–40% over 12 months. Use to compare cohorts (e.g. by acquisition channel or first order value).
Retention and LTV
Your monthly retention is 92%. AOV $70, purchase frequency 2 orders per year. What's LTV?
- 1 Monthly retention = 92% → churn = 8% = 0.08
- 2 Customer lifespan (months) = 1 ÷ 0.08 = 12.5 months
- 3 Lifespan in years = 12.5 ÷ 12 ≈ 1.04 years
- 4 LTV = AOV × Frequency × Lifespan = $70 × 2 × 1.04 ≈ $145.60
LTV is about $146. Improving retention to 95% (5% churn) would give lifespan 20 months and LTV ≈ $233.
Small improvements in retention have a large impact on lifespan and LTV—often more than one-time AOV or frequency gains.
Retention Benchmarks by Type
Typical ranges (your results will vary)
| Type | Typical Retention | Notes |
|---|---|---|
| SaaS (B2B) | 90–95% annual | Sticky accounts, contracts |
| SaaS (B2C) | 80–90% annual | Often higher churn than B2B |
| Subscription box | 70–85% monthly | Skip/cancel common |
| Ecommerce (12-mo repurchase) | 20–40% | Many don't repurchase in 12 months |
| DTC / membership | Varies | Depends on product and value |
How to Improve Retention
Strategies that keep customers coming back
Onboarding and First Experience
Great first order and post-purchase communication increase likelihood of return.
Email and Remarketing
Re-engagement and personalized offers bring lapsed customers back.
Loyalty and Rewards
Points, tiers, and perks increase switching cost and repeat rate.
Subscription or Replenishment
Recurring options lock in retention for eligible products.
Customer Success (B2B)
Proactive check-ins and success plans reduce churn.
Product and Value Fit
Retention reflects whether the product and segment match; fix fit first.
Common Retention Mistakes
Errors that distort retention and churn
Mixing Start and End Cohorts
Using 'customers at start' from one period and 'customers at end' from another, or including new customers in 'retained.'
Retained = End − New (in same period). Start = beginning of period; End = end of period; New = acquired in that period. All same window.
Wrong Definition of 'Active'
For cohort retention, defining 'active' too loosely (e.g. any visit) or too strictly (e.g. 2+ orders), or using different definitions across cohorts.
Define 'active' once (e.g. at least one purchase in next 12 months) and use for all cohorts. Document it.
Ignoring Segment
One retention number hides that high-value or certain channels retain better.
Segment retention by acquisition channel, first order value, product, and cohort. Act on the worst segments.
Confusing Retention with Repeat Rate
Repeat purchase rate (e.g. % with 2+ orders) is not the same as cohort retention over a window.
Retention = % of cohort still active in a period. Repeat rate = % ever making 2+ orders. Both useful; don't mix.
How to Track Customer Retention in WooCommerce
Ways to measure retention and repeat purchase
Option 1: Spreadsheets
Export orders and customers, define cohorts and windows, and compute retained counts manually. Flexible but time-consuming and hard to keep current.
- Full control
- No extra cost
- Manual
- Slow
- Hard to segment
Option 2: Google Analytics
GA4 has some retention and user lifecycle reports. Limited by cookie/session and identity; cohort retention over long windows is harder.
- Free
- Some retention views
- Cookie-based
- Limited cohort depth
- Setup complexity
Option 3: StoreRadar
StoreRadar tracks repeat purchase and retention by segment so you can see who stays, who lapses, and how retention affects LTV—all in real time.
- Automatic retention view
- By segment and cohort
- Real-time
- LTV context
- Monthly subscription
Related Formulas
Retention ties to churn, LTV, and revenue
| Formula | Calculation | Relationship |
|---|---|---|
| Churn Rate | 100 − Retention Rate | Inverse of retention |
| Customer Lifespan | 1 ÷ Churn Rate | Retention/churn set lifespan |
| LTV | AOV × Frequency × Lifespan | Retention drives lifespan and LTV |
| Cohort Retention | % of cohort still active each period | Cohort view of retention |
| Net Revenue Retention | (Cohort revenue end ÷ Cohort revenue start) × 100 | Revenue version of retention; can exceed 100% |
Frequently Asked Questions
Common questions about customer retention rate
Customer Retention Rate = (Customers at End of Period − New Customers in Period) ÷ Customers at Start of Period × 100. Or: (Retained Customers ÷ Customers at Start) × 100. For example, 400 at start, 80 new, 420 at end: Retained = 420 − 80 = 340; Retention = (340 ÷ 400) × 100 = 85%. It measures what percentage of your starting customers you kept.
Retention rate = % of customers you kept. Churn rate = % you lost. Retention + Churn = 100% (for the same cohort or period). So 85% retention = 15% churn. Use retention when you want to emphasize keeping customers; use churn for loss and LTV/lifespan math (e.g. lifespan = 1 ÷ churn).
Define a cohort (e.g. customers who bought in January) and a window (e.g. next 12 months). Retained = those who made at least one purchase in the next 12 months. Retention = (Retained ÷ Cohort Size) × 100. You can do this for multiple periods (e.g. retention by month 1, 3, 6, 12) to get a curve.
Customer retention = % of customers kept. Revenue retention (e.g. MRR or cohort revenue) = % of revenue retained from that cohort. Revenue retention can be above 100% with expansion (upsells). Use customer retention for count-based health; revenue retention for revenue impact.
It varies by business. Subscription SaaS: 90%+ annual retention is strong; 80–90% is common. Ecommerce: often measured as % of cohort repurchasing within 12 months; 20–40% is typical. Compare to your history and segment (e.g. by first purchase value or channel).
Higher retention means longer customer lifespan (lifespan ≈ 1 ÷ churn). LTV = AOV × Purchase Frequency × Lifespan, so retention directly drives LTV. Improving retention often has a bigger impact on LTV than one-time AOV or frequency gains.
See Who Stays and Who Lapses
StoreRadar helps you track retention and repeat purchase by segment so you can improve LTV and reduce churn.
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