Retention Rate Calculator
An interactive retention rate calculator built for Shopify, WooCommerce, and Magento stores. Returns retention rate, churn rate, and a cohort-projected LTV impact in one shot.
Retention Rate Calculator
A tool that computes the share of customers you kept across a period, after correctly excluding newly acquired customers.
A retention rate calculator measures how many customers from the start of a window are still customers at the end of it. The formula looks simple — ending customers minus new customers, divided by starting customers — but most stores get it wrong by counting new acquisitions as if they were retained.
For an online store, retention rate is the cleanest read on whether repeat purchasing is healthy. Pair it with churn rate (its inverse) and an LTV projection, and you can decide whether to lean harder into acquisition or invest in lifecycle, subscriptions, and post-purchase flows.
Retention Rate Calculator
Customers at start of period
customers
Active customers on day 1 of your measurement window (e.g. start of the quarter).
Customers at end of period
customers
Active customers on the last day of the window, including any new ones acquired.
New customers acquired in period
customers
First-time buyers acquired during the window. These get stripped out so you measure retention, not growth.
Average order value
$
Used to project the revenue impact of your retention rate.
Avg orders per retained customer / year
orders
Repeat purchase frequency for customers who stick around.
Customer retention rate
84.0%
Customer churn rate
16.0%
Projected annual revenue from retained customers
$655,200
New customers are subtracted so you measure how many of your starting cohort stayed, not how much your customer base grew. If you want gross retention without that correction, set 'new customers acquired' to 0.
The widget above does the math live — change any input and retention, churn, and projected revenue update together. The rest of this page explains the formula, gives you benchmark ranges by vertical, and shows how to interpret the result without falling into the new-customer trap.
The formula behind the calculator
Retention Rate = (E - N) / S
S
Starting customers
Active customers at the start of the measurement window.
E
Ending customers
Active customers at the end of the window, including any acquired during it.
N
New customers
First-time buyers acquired during the window.
A beauty SKU store on Shopify measures Q3 retention. They start with 8,000 customers, end with 9,100, and acquired 2,000 new customers in the quarter.
Starting customers (S): 8000
Ending customers (E): 9100
New customers (N): 2000
→ (9100 - 2000) / 8000 = 0.8875, or 88.75%
Even though the customer base grew by 1,100, retention is 88.75% — meaning 11.25% of the starting cohort churned. Without subtracting new customers, the naive calculation would have shown 113.75%, which would mask the churn entirely.
Subtracting new customers is the step most teams skip. If you simply divide ending by starting, growth from acquisition hides churn underneath. A store can look healthy while quietly losing 20% of its base every quarter — masked by paid traffic refilling the bucket.
The companion churn rate is just 1 minus retention. The projected revenue output multiplies your retained customer count by repeat orders per year and AOV, giving you a back-of-envelope value for the cohort you actually kept.
Typical retention rate ranges by vertical
Annual customer retention rate ranges for online retail, by vertical
| Vertical | Median retention | Top quartile | Repeat purchase cadence |
|---|---|---|---|
| Beauty & personal care | 55-65% | 75%+ | Every 6-10 weeks |
| Apparel & accessories | 30-40% | 55%+ | 2-3x per year |
| Consumer electronics | 20-30% | 40%+ | Every 12-24 months |
| Home & garden | 25-35% | 50%+ | 2-4x per year |
| Food & beverage (subscription) | 70-85% | 92%+ | Monthly |
| Pet supplies | 60-72% | 82%+ | Every 4-6 weeks |
Retention rate is vertical-bound — comparing apparel to subscription food is meaningless. The right benchmark is your own cohorts over time, with the table above as a sanity check on the order of magnitude. If your apparel store is above 55%, the repeat-purchase engine is doing real work.
How to interpret the result
A single retention number is a starting point, not a verdict. Pair it with cohort retention curves to see whether customers are dropping off in month 1 (an onboarding or product-fit issue) or after month 6 (a lifecycle and reactivation issue). The fix is completely different in each case.
Also segment by acquisition channel. Customers from paid social often retain 10-20 points worse than customers from organic search or referral. If your blended retention looks fine but paid-acquired cohorts are leaking, you're funding a growth engine that doesn't compound.
The new-customer trap
If your ending customer count is higher than your starting count, it's tempting to call retention healthy. Don't. Subtract new acquisitions first — otherwise paid traffic is masking the churn of your existing base, and you'll only spot it when CAC goes up and the growth math breaks.
Frequently asked questions
Take customers at the end of the period, subtract any new customers acquired during the period, then divide by customers at the start. Multiply by 100 for a percentage. The calculator above does this in one step and also returns churn and projected revenue.
For most DTC stores, a customer is anyone with at least one purchase in your active window — typically the last 12 months. Don't count email subscribers or accounts without a purchase; they inflate the denominator and make retention look worse than it is.
It depends entirely on vertical. Apparel sits around 30-40% annually, beauty around 55-65%, subscription categories well above 70%. The honest benchmark is your own cohort from the same period last year — improvement over yourself matters more than industry medians.
Retention rate measures whether a cohort of customers is still active over a window. Repeat purchase rate measures whether a customer has bought more than once, ever. Repeat rate is a lifetime metric; retention is windowed and cohort-aware.
Match it to your repeat purchase cadence. Subscription brands measure monthly; apparel and electronics measure quarterly or annually. Measuring monthly when customers buy twice a year produces noise, not signal.
LTV is roughly AOV × purchase frequency × customer lifespan, and lifespan is driven by retention. A 5-point retention lift typically compounds into a 25-40% LTV uplift over a 3-year horizon, because retained customers buy more and refer others.
Because retention measures whether your existing base stayed, not whether your total base grew. Without subtracting new acquisitions, a store with heavy paid spend can show 110% retention while quietly losing 20% of its starting cohort.
The formula works, but the interpretation differs. SaaS teams typically use net revenue retention (which credits expansion revenue) alongside logo retention. This calculator is tuned for transactional retail where every customer counts as one unit.
Diagnose first: is month-1 churn high (product-fit, onboarding, expectations) or later-month churn (lifecycle gap, no reactivation)? Then test specific levers — post-purchase email sequences, subscribe-and-save, replenishment reminders, win-back flows — and measure cohort retention before and after.
They're complementary: churn rate = 1 - retention rate. If 84% of your starting customers are still active, your churn is 16%. Most teams report whichever is closer to zero (so high retention is reported as retention; high churn is reported as churn) to make the number easier to read.
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