Retention Rate Benchmarks
Retention rate benchmarks across DTC verticals — consumables, apparel, durables — broken out by 30/60/90/365-day windows and AOV band, with guidance on what's actually "good" for your category.
Retention Rate Benchmarks
Reference ranges for how often e-commerce customers buy again, segmented by vertical, AOV band, and product category.
Retention rate benchmarks tell you what share of first-time buyers come back within a defined window — typically 30, 60, 90, or 365 days — across comparable stores. They matter because retention is the single biggest lever on contribution margin once paid acquisition costs more than a first order returns.
The useful benchmark is never a single global number. A skincare brand selling a 30-day refill is playing a completely different game than a furniture brand selling a once-every-five-years sofa. The ranges below are organised by category type (consumables, apparel, durables), vertical, and AOV band so you can compare against a peer set that actually resembles your store.
The first question to answer before reading any benchmark is whether you're measuring repeat customer rate (share of customers who placed a second order) or revenue retention (share of cohort revenue retained over time). The numbers below are repeat-customer rates — the metric most Shopify and WooCommerce dashboards surface by default.
The other thing that makes published retention numbers misleading: most blog-post benchmarks aggregate every vertical into one figure ("good DTC retention is 27%") and ignore replenishment cycle entirely. A 27% 90-day rate is excellent for mattresses and below average for coffee. Match the window to your natural buying cadence.
90-day repeat customer rate by DTC vertical and AOV band
| Vertical | AOV band | Bottom quartile | Median | Top quartile |
|---|---|---|---|---|
| Skincare & beauty (consumable) | €25-€60 | 18% | 28% | 42% |
| Supplements & vitamins | €20-€50 | 24% | 36% | 51% |
| Coffee, tea & pantry | €15-€40 | 22% | 34% | 48% |
| Pet food & treats | €20-€60 | 28% | 41% | 55% |
| Apparel & accessories | €60-€120 | 9% | 18% | 27% |
| Footwear | €80-€180 | 7% | 14% | 22% |
| Home & decor | €80-€250 | 6% | 12% | 19% |
| Consumer electronics | €150-€600 | 4% | 8% | 14% |
| Jewellery | €100-€400 | 5% | 11% | 18% |
| Kids & baby (consumable) | €30-€80 | 20% | 32% | 46% |
Read the table this way: if you run a skincare store with a 28% 90-day repeat rate, you are right at the median for your category — fine, but a long way from the 42% top quartile. The gap between median and top quartile usually maps to one of three things: a subscription option, a triggered replenishment flow, or a genuinely differentiated product. Apparel is structurally harder because there's no consumable cycle pulling people back.
Median 90-day repeat customer rate across DTC categories
How to read these numbers without fooling yourself
Pick the window that matches your replenishment cycle, not the one that looks good in a deck. For a 30-day skincare refill, the 30-day repeat rate is the operational metric and 365-day rate is the strategic one. For a €600 espresso machine, 90 days is meaningless — measure 12-month attach-rate on consumables and accessories instead.
Second, segment by acquisition channel before you celebrate. Branded-search buyers and email-acquired customers retain at roughly 2-3x the rate of paid-social cold traffic in most verticals. A blended 28% can be 45% from your warm channels and 12% from Meta — and the right action depends on which it is.
Cohort math trap
If you compute retention as "repeat customers this month ÷ all customers this month" you're mixing cohorts and the number will move with acquisition volume, not actual retention. Always anchor the metric to a fixed acquisition cohort (e.g. customers who first ordered in March) and measure their behaviour forward. A growing store will look like it's retaining worse than it is; a stagnating one will look better.
Diagnosing the gap between your number and the top quartile
If you're sitting at median and want to reach top quartile, the diagnostic order matters. Start with second-order timing: pull the histogram of days-between-first-and-second-order for last year's buyers. The mode of that distribution is your natural replenishment window — and any post-purchase flow timed outside it is leaking money. Most skincare brands find a bimodal distribution at 35 and 60 days; sending the replenishment nudge at day 45 misses both.
Then look at first-order product mix. Customers acquired on a discounted starter kit or single hero SKU retain dramatically worse than customers whose first order included two or more products — often a 15-20 percentage point gap at 90 days. This is where retention work feeds back into acquisition: the offer that maximises first-order conversion is rarely the offer that maximises 12-month value. Tie this back to your retention economics work before pushing harder on top-of-funnel.
Frequently asked questions
It's right at the median for skincare in the €25-€60 AOV band. Good enough that you're not bleeding, but the top quartile sits around 42%, and getting there usually requires either a subscription option or a tighter replenishment flow timed to the 30-45 day refill window.
18% at 90 days is the median for apparel and accessories; 27%+ puts you in the top quartile. Apparel retention is structurally lower than consumables because there's no replenishment cycle — repeat purchases are driven by new collections, fit confidence, and email engagement rather than running out of product.
Match the window to your replenishment cycle. Consumables (skincare, coffee, supplements, pet food) should track 30 and 90 day windows as operational metrics. Durables (apparel, home, electronics) should track 180 and 365 day windows. Always also track 365-day repeat rate as a strategic check.
The platform itself doesn't change retention meaningfully — vertical and AOV are far stronger predictors. What does differ is measurement: Shopify's native repeat customer rate uses a different definition than WooCommerce's default reports, so make sure you're comparing like-for-like before benchmarking.
Yes, materially. Brands with a working subscription program typically post 90-day repeat rates 12-20 percentage points above their non-subscription peers. If you compare against benchmarks, segment your numbers into one-time-buyer cohorts and subscriber cohorts — the blended figure hides the real story.
Within a vertical, higher AOV usually correlates with lower repeat rate (longer purchase cycles, higher consideration) but higher LTV per repeat customer. A €150 AOV apparel brand at 12% repeat can be more profitable than a €40 AOV one at 22% — always pair retention rate with average order value and contribution margin.
Retention rate is the multiplier on your second-order revenue, which is what makes CAC payback work past the first purchase. A 10-point lift in 90-day repeat rate typically pulls payback period forward by 1-2 months in consumables and 2-4 months in apparel — see our retention economics breakdown for the full math.
Almost always cohort dilution: paid-social cold traffic retains at roughly half the rate of branded search or email-acquired customers. As paid grows faster than warm channels, the blended retention rate falls even if every channel's retention is stable. Segment by acquisition source before concluding retention is broken.
Quarterly is enough for strategic planning. Monthly refreshes are noisy at typical DTC scale because individual cohorts are small. What you should do monthly is track your own cohort retention curves — the comparison to external benchmarks is a quarterly exercise.
No. Marketplace customers (Amazon, eBay) belong to the marketplace, not the seller, so repeat-purchase tracking is inherently incomplete and rates appear much lower. These benchmarks assume direct-to-consumer storefronts where you own the customer relationship and can match orders across time.
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