What is a good customer retention rate for ecommerce?

A good 90-day retention rate for ecommerce is 30 to 40%: meaning 30 to 40% of first-time buyers make a second purchase within 90 days. The industry average is 20 to 25%. A brand with less than 20% 90-day retention has an active retention problem that is compounding with every new cohort of customers acquired. The more actionable metric for most brands is the 60-day repeat purchase rate: the percentage of customers who make a second purchase within 60 days of the first. A 60-day repeat purchase rate above 25% indicates a functioning retention system. Below 20% indicates at least one retention signal is active. The specific signals to diagnose are R1 (no post-purchase sequence), R2 (no replenishment flow for consumables), and R3 (no win-back sequence for lapsed customers).

How do I calculate my ecommerce churn rate?

Ecommerce churn rate is typically calculated as: (number of one-time buyers who have not returned within a defined window) divided by (total customers in that cohort). The window is usually 90 or 180 days. For a cohort of 500 customers acquired in January, if 325 of them have not placed a second order by April 1st (90 days), the churn rate for that cohort is 65%. Tracking this by cohort (January cohort, February cohort) lets you see whether retention is improving over time as you build retention infrastructure. A single snapshot churn figure without cohort segmentation is less useful because it conflates customers who churned a year ago with customers who churned last month.

Why do customers buy once and never come back?

The primary reason is post-purchase silence: not a negative experience. Retention Science data shows that 60 to 70% of one-time buyers are open to a second purchase within 90 days, but 68% of those buyers never return because no communication prompted them at the right moment. The brand that goes quiet after the first sale is not losing customers to a competitor. It is losing them to inertia. The second most common reason is the absence of a relevant reason to return: no new arrivals communicated, no replenishment reminder, no loyalty reward for coming back. Third, first-purchase experience problems (product quality, delivery issues, customer service failures) account for a smaller but real percentage: these are not fixable by email, only by the operations and product they represent.

What is the difference between churn rate and repeat purchase rate?

Churn rate and repeat purchase rate measure the same behaviour from opposite directions. Repeat purchase rate is the percentage of customers who return. Churn rate is the percentage who don't. If your 90-day repeat purchase rate is 35%, your 90-day churn rate is 65%. Both metrics are correct; which one you use depends on what you are trying to communicate. Churn rate is useful for unit economics. It frames the acquisition cost problem: if 65% of customers are single-purchase, you are paying acquisition cost for 10,000 customers to generate the lifetime value equivalent of 3,500 retained customers. Repeat purchase rate is more actionable for retention teams. It frames the improvement goal: increasing from 25% to 35% repeat purchase rate is a clear target.

Signal R4: Retention

Part of the Email & Retention signal group

High Ecommerce Customer Churn Rate: Why Most First-Time Buyers Never Come Back

For brands without a retention system, 60 to 70% of first-time buyers make exactly one purchase and never return. Each of those single-purchase customers cost the same to acquire as a retained customer, and generated a fraction of the lifetime value. Signal R4 is the aggregate cost of retention failure: the overall churn rate that results when the post-purchase sequence (R1), the replenishment flow (R2), and the win-back sequence (R3) are absent. Reducing churn from 65% to 50% at 300 orders per month adds $19,440 in annual revenue at the same acquisition spend.

The Acquisition Treadmill

Andrew Faris, on the DTC Podcast, describes the acquisition treadmill: a brand with a 65% churn rate must acquire 65 new customers just to stay flat. Not to grow, to replace the customers it is losing. Every month that acquisition costs increase, the treadmill gets harder to run. The brand is not building an asset: it is filling a bucket with a hole in the bottom.

The unit economics make this concrete. At a $40 CAC and 300 orders per month with 65% churn, the brand is spending $7,800 per month acquiring customers who will never generate a second transaction. If churn drops to 50%, 45 additional customers per cohort return to buy again. At $60 AOV, that is $2,700 in additional monthly revenue ($32,400 annually) at zero additional acquisition cost.

Matt Putra's DTC CFO analysis of the specific scenario in this brief (reducing churn from 65% to 50% at 300 orders per month) shows $19,440 in annual revenue added at the same ad spend. The calculation uses a conservative $54 AOV. With a higher AOV, the impact is proportionally larger.

"You cannot scale your way out of a retention problem. Every dollar you spend on acquisition at a 65% churn rate is paying to replace customers you're already losing. Fix the hole first."
Andrew Faris, DTC Podcast

The Second-Purchase Threshold

Retention Science data identifies a non-linear relationship between purchase count and future purchase probability. A one-purchase customer has a 25 to 30% probability of making a third purchase. A two-purchase customer has a 60 to 70% probability of making a third purchase. The second purchase is not just another transaction: it is the threshold at which a customer transitions from uncertain to loyal.

Taylor Holiday frames this as the core retention argument: the second sale is cheaper and more valuable than the first. The customer is acquired. Trust is established. The post-purchase sequence, the replenishment flow, and the win-back sequence exist for one purpose: to convert first-time buyers into second-time buyers: crossing the threshold where retention becomes self-sustaining.

A brand with a 65% churn rate has 65% of its customers stuck at one purchase, below the second-purchase threshold. Every one of those customers is at 25 to 30% probability of return, not the 60 to 70% they would be at after a second purchase. The entire retention system, R1, R2, R3, is designed to move customers across that threshold.

What a Complete Retention System Looks Like

A brand with a churn rate below 40% has these retention components active and working in sequence:

Post-purchase sequence (R1): catches customers in the 72-hour window after delivery.

Three emails triggered by order delivery: check-in at day 2, product recommendation at day 5, review request at day 10. This sequence is the first-line defence against churn: it converts first-time buyers into second-time buyers before the purchase experience fades.

Replenishment flow (R2): catches consumable customers before reorder intent goes elsewhere.

For brands selling consumables: an automated flow triggered at day 25 on a 30-day product. Timing the reorder conversation before the customer runs out is the single highest-conversion automation for consumable brands. Without it, reorder intent is diverted to competitors or retail.

Win-back sequence (R3): catches lapsed customers at 90+ days.

Five emails over 21 days: check-in, what changed, social proof, specific offer, goodbye email. The recovery layer for customers who slipped through R1 and R2. An 8 to 15% reactivation rate on a cohort of 200 lapsed customers per month is 16 to 30 additional purchases at zero acquisition cost.

Churn rate tracked by cohort in analytics.

Not a single site-wide churn figure: cohort-level tracking that shows whether the January cohort is churning at a different rate than the August cohort. Cohort analysis reveals which retention improvements are working and which cohorts were acquired at times when retention infrastructure was weaker.

Retention metrics reported separately from acquisition metrics.

If the same dashboard is used for acquisition ROAS and retention repeat rate, the acquisition numbers will dominate attention. Retention requires its own reporting: 60-day repeat purchase rate, 90-day churn rate, revenue per customer at 180 days. These numbers tell the health of the business in a way that ROAS alone does not.

Benchmarks to Know

60–70%

First-purchase churn rate for brands without retention systems

60–70%

Probability of a 3rd purchase from a 2-purchase customer

25–30%

Probability of a 3rd purchase from a 1-purchase customer

$19,440

Annual revenue added by reducing churn from 65% to 50% at 300 orders/month

5×

Higher LTV of customers with 3+ purchases vs 1-purchase customers

20–25%

Industry average 90-day retention rate

Related Signals

Low Repeat Purchase Rate

R1 is the first retention signal: the post-purchase sequence that drives the second purchase. A high R4 churn rate is almost always preceded by an active R1: no structured communication in the 72-hour window after delivery where the second purchase is most likely to be made.

No Win-Back Sequence

R3 is the recovery layer for churn: reactivating customers who are already lapsed at 90+ days. Fixing R3 directly reduces the R4 churn count by recovering customers who would have counted as permanent single-purchase churns. R3 and R4 should be built and measured together.

Frequently Asked Questions

What to Do Next

If 60% or more of your customers are single-purchase buyers, you are on the acquisition treadmill. Every dollar of ad spend is paying to replace customers you are already losing: not to grow.

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