Insights
Average Repeat Purchase Rate by Vertical (2026)
The average DTC brand sees about 28% of customers place a second order within 12 months, but that hides a roughly 5x spread by category. Consumables like supplements and food run 30 to 45%; considered purchases like furniture and jewelry sit at 10 to 20%. Benchmark against your own vertical, not the average.
Key Takeaways
- The blended DTC repeat purchase rate is about 28%, but the average hides a roughly 5x spread. Food, supplements, and pet care run 30 to 45%; jewelry and electronics sit at 9 to 18%.
- Consumables repeat because the product gets used up. Considered purchases (furniture, jewelry) do not need replacing, so a 15% repeat rate there is normal, not broken.
- Benchmark against your own vertical, never the all-category average. Panicking over a 15% rate in furniture, or accepting 20% in supplements, are both expensive category errors.
- 76% of all repeat orders happen within 90 days of the first order. Win-back flows that start at 120 days are working the tail of the decision window, not the meat of it.
- The gap between your category average and the top quartile is the room a retention fix can recover. Below average is an execution signal; at average but still unprofitable is a pricing or product problem.
If you run a DTC brand, your repeat purchase rate (the share of customers who come back for a second order) is probably the number you quote with the least confidence, because you have no idea whether it is good. In 2026 the blended ecommerce average is about 28%, but that average is close to useless on its own, because the spread between categories runs roughly 5x from top to bottom. Below we lay out the by-vertical benchmarks so you can tell whether your number is a category ceiling or a fixable retention gap, and what to watch next quarter. This matters because the answer changes what you do: one is a reason to relax, the other is a reason to rebuild your flows.
What repeat purchase rate actually measures (and the window problem)
Repeat purchase rate is simple to define and easy to mangle. Take the customers who placed 2 or more orders, divide by all unique customers, and you have it. The trap is the window. A 90-day repeat rate and a 12-month repeat rate for the same brand can differ by 15 points or more, so a benchmark is meaningless unless you know the window behind it. Most of the published 2026 figures, and everything in this post unless flagged, use a 12-month window.
There is a second definition trap worth naming. Some sources measure repeat customers as a share of all customers (the true repeat rate). Others measure orders from repeat customers as a share of all orders, which is a different and usually higher number. We use the customer-based definition throughout. If your analytics tool reports the order-based version, your figure will look healthier than the benchmarks here, and you will be comparing apples to oranges.
The blended DTC average lands at roughly 28% across most aggregators. That is the number to anchor on, and then immediately set aside, because almost no real brand should be measuring itself against it.
The 2026 benchmarks: repeat rate by vertical
Here is the full picture. Consumable categories sit at the top because the product gets used up and bought again. Considered purchases sit at the bottom because a customer who bought a sofa does not need another one for two years.
The table below carries the full per-vertical detail, including purchase cycle and primary source.
| Vertical | 12-month average | Top-quartile target | Purchase cycle |
|---|---|---|---|
| Food & Beverage | 35-45% | 50%+ | 14-60 days |
| Supplements & Vitamins | 29-36% | 40-45% | 30-90 days |
| Pet Care | 28-35% | 40-60% (w/ subscription) | 30-60 days |
| Sport Apparel | ~33% | 40%+ | 60-180 days |
| Beauty & Skincare | 25-30% (90-day) / 30-40% (annual) | 40-55% | 30-90 days |
| Coffee & Tea | 21-30% | 35-40%+ | 14-30 days |
| Apparel & Fashion | 20-26% | 30-35% | 90-180 days |
| Home Goods & Decor | 18-25% | 28-30%+ | 180-365 days |
| Electronics & Tech | 12-18% | 25%+ | 180-365 days |
| Furniture | ~14-15% | 20%+ | 365-730 days |
| Jewelry & Accessories | 9-11% | 15-20% | 365+ days |
| DTC all-category average | ~28% | 35-40% | varies |
The numbers we trust most: grocery at 35 to 45% blended (Rivo also reports 65.2% repeat purchase intent from a survey, a stated preference and not a measured transaction rate), supplements at 29 to 36%, apparel at 24 to 26%, jewelry at 9.9%. The pattern is the story. When we talk to founders, the apparel ones describe a slow LTV curve almost word for word: 100 bucks in month one, then 105, 107, 108, a very gentle climb. Apparel adds 5 to 10% per period. A supplement brand adds 30 to 40%+. If you run apparel and you built your paid model expecting supplement-style repeat behavior, you will overspend on acquisition and compress your margin to nothing.
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Why you cannot compare consumables to considered purchases
The structural reason for the spread is replenishment cycle. A supplement runs out in 30 to 90 days, so the customer has a built-in reason to return four to twelve times a year. A piece of furniture is a 12-to-24-month decision, sometimes longer. No flow, no loyalty program, no email cadence changes that. So comparing a furniture brand's repeat rate to a supplement brand's is a category error before you even start.
This is also where the unit economics diverge hard. A repeat order carries almost no marginal acquisition cost, so repeat rate is the single biggest lever on blended CAC payback. When repeat rate is structurally too low to recover acquisition cost, every new customer has to pay back on the first order, or the acquisition is net-negative. That is what we mean when we say a brand is renting customers from Meta rather than owning them. An $80 supplement brand at a 20% repeat rate has a CAC payback problem that better flows can fix. A $500 home goods brand at a 20% repeat rate is doing fine, because the AOV does the work the frequency cannot.
Timing makes the consumable advantage even sharper. Across verticals, half of all second orders arrive within 30 days of the first, and 76% within 90 days.
The implication is blunt: the repeat decision is mostly made in the first quarter after purchase. If your post-purchase and replenishment flows are not landing in that window, you are not influencing the decision, you are just observing it.
Category ceiling or retention gap?
Here is the diagnostic that actually changes what you do on Monday. Inside every vertical there is a wide gap between the average brand and the top quartile. That gap is the room a retention fix can recover.
Read it like this. If you are below your category average, you have a retention execution problem, and the gap to the top quartile is your upside. If you are at or above average but still not breaking even on acquisition, the problem is not retention, it is pricing or product-market fit, and no amount of email flows will fix it. The thresholds below give you the rough bands.
| Vertical | Below average (needs attention) | At average (baseline) | Top quartile (strong) | Structural ceiling |
|---|---|---|---|---|
| Supplements | <22% | 22-32% | 33-45% | ~55% (subscription) |
| Beauty & Skincare | <20% (90-day) | 20-28% | 30-45% | ~55% (refill/sub) |
| Apparel | <15% | 15-26% | 27-35% | ~40% |
| Food & Beverage | <25% | 25-38% | 38-50% | 65%+ (grocery, intent-based) |
| Pet Care | <20% | 20-31% | 32-45% | 60%+ (autoship) |
| Home Goods | <12% | 12-20% | 21-28% | ~30% |
| Jewelry | <7% | 7-11% | 12-20% | ~25% (fashion jewelry) |
The diagnostic also catches the happy outlier. When a beauty brand mentions a 42% repeat rate, our instinct is to ask what is driving it, because at that level they are running at nearly double the 90-day category average. That is not a number to leave unexamined, it is usually a subscription or refill mechanic that is worth protecting and doubling down on.
The all-category 28% average is a trap. It will make a furniture brand panic and a supplement brand complacent. The only benchmark that tells you anything is your own vertical's range, and the only number that tells you what to do is the distance between where you sit and where the top quartile sits.
The flows that move the needle, and when to deploy them
If 76% of repeat orders happen inside 90 days, the entire game is influencing the first 90 days. That means post-purchase sequences, replenishment reminders timed to the actual product cycle, and subscription or refill nudges all need to land early. A win-back flow that fires at 120 days is working the 4% tail, not the meat of the distribution.
The compounding is the part operators underrate. In a supplement cohort, we roughly expect 25% of people to come back and buy again in month two, and from there about 90% of those repeat buyers should repurchase again (illustrative from first-party client work, not a published cross-brand benchmark). The first repeat is the hardest and the most expensive to earn; the second converts at a much higher rate. So the highest-impact flow is almost always the one that wins the first repeat inside that 90-day window, because everything downstream compounds off it.
Loyalty mechanics help here too. Loyalty program participants show meaningfully higher repeat rates than non-participants (Smile.io puts the lift at +72%, which is directional internal data rather than a controlled study, but the direction is consistent with everything else). The point is not the exact number. It is that the brands sitting in the top quartile of their category almost always have a deliberate, early, repeatable reason for the customer to come back, and the brands below average usually do not.
What a five-point improvement is worth
Make it concrete. Say you acquire 1,000 customers at a $50 blended CAC. Moving your repeat rate from 25% to 30% means 50 additional customers place a second order, at near-zero marginal acquisition cost. At a $100 AOV and 50% gross margin, that is $2,500 in incremental contribution margin from the same cohort you already paid to acquire. Run that across every monthly cohort for a year and the five points compounds into real money, with no extra ad spend.
The churn framing lands the same point from the other side. A health and wellness brand we worked through the math with was losing 18% of its repeat buyers every month. Going from 18% monthly churn to 14% does not sound dramatic, but the revenue impact is substantial, because you are keeping a larger base intact every single month and that base is the cheapest revenue you will ever have. Plug your own AOV, margin, and cohort size into the same structure before you decide a retention project is not worth the effort. For most brands below their category average, it is the highest-ROI work on the board.
Related reading. For the vertical cuts on the same metric, see our repeat purchase rate by vertical benchmarks. For how we turn repeat rate into a CAC ceiling with brands, see fractional CFO for ecommerce.
Sources and methodology
Cross-vertical benchmarks compiled from published ecommerce retention guides. The per-vertical ranges are aggregated from several independent 2025-2026 benchmark guides rather than a single dataset, because no one source covers every category cleanly. Primary inputs were Rivo's repeat purchase rate guide (28.2% blended average, 9.9% luxury, and 65.2% grocery repeat purchase intent, a survey-stated figure and not a measured transaction rate), and StoreGrowers' ecommerce metrics dataset (apparel 26.0%, cosmetics 25.9%, coffee 29.6%, supplements 29.1%, pet products 31.5%). Note: several StoreGrowers category figures trace to the Metrilo Customer Retention Report (2019), re-cited by current 2025-2026 guides; treat them as directional baselines rather than fresh 2026 measurements.
Beauty and pet figures cross-checked against category-specific sources. Beauty ranges were corroborated with the MageLoyalty 2026 beauty benchmarks (90-day benchmark 25-30%, top performers 40-55%) and pet ranges with the Foundry CRO 2026 pet benchmarks (baseline 28-35%, subscription 40-60%).
Timing distribution is a cross-vertical cohort analysis. The 50.3%-within-30-days and 76.4%-within-90-days figures come from our time-to-second-purchase analysis. The intra-bucket splits between 30 and 365 days are interpolated to the published cumulative checkpoints, so treat the middle buckets as estimates rather than reported values.
Window and definition caveats. Benchmarks use a 12-month window and the customer-based definition (repeat customers / total customers) unless flagged. Sources that include subscription customers report higher than pure transactional DTC, and most published figures are blended. Where a source measured only a second purchase or used a 60-day window, its lower numbers were not mixed into the 12-month ranges.
One known outlier excluded. At least one source cites a 38% repeat rate for jewelry, far above the 9.9-11% every other source reports. That figure most likely measures loyalty intent rather than actual repurchase, so it was excluded from the jewelry range here.
Frequently asked questions
what is a good repeat purchase rate for ecommerce?
It depends entirely on your category. The blended DTC average is about 28%, but a good rate is 35 to 45% for consumables like food and supplements, 30 to 40% for beauty, 27 to 35% for apparel, and 12 to 20% for jewelry or furniture. Compare to your own vertical, not the average.
what is the average repeat purchase rate for a supplement brand?
Supplement and vitamin brands average 29 to 36% on a 12-month basis, with top performers hitting 40 to 45% and subscription-heavy brands pushing past 50%. If your supplement brand is below 22%, that is a retention execution problem, not a category ceiling.
is a 15% repeat purchase rate bad for a furniture or jewelry brand?
No. Furniture sits around 14 to 15% and jewelry around 10 to 11% because nobody buys a sofa or an engagement ring on a 30-day cycle. A 15% rate there is normal. The mistake is judging it against a supplement benchmark and concluding something is broken when it is not.
how do you calculate repeat purchase rate?
Divide the number of customers who placed 2 or more orders in a window by the total number of unique customers in that same window. Most published benchmarks use a 12-month window. Keep your window consistent or you cannot compare your number to anyone else's.
why is my repeat purchase rate low even though my reviews are good?
Great reviews mean the product is good, not that customers are being prompted to come back. Low repeat rate with high reviews usually means the post-purchase flows are missing or mistimed. Most second orders happen within 90 days, so if your reminder and replenishment emails start later, you are missing the window.
how does repeat purchase rate affect CAC payback?
It is the single biggest lever. A repeat order carries almost no marginal acquisition cost, so every point of repeat rate pulls payback forward. A brand stuck at a structurally low repeat rate is effectively renting customers from Meta: each one has to pay back on the first order or the acquisition is net-negative.
what repeat purchase rate should a beauty brand aim for?
On a 90-day basis, 25 to 30% is the standard beauty benchmark. On a 12-month basis, healthy brands land at 30 to 40% and top performers reach 40 to 55%. A beauty brand running 42% is well into top-quartile territory.
how do subscription models change repeat purchase rate benchmarks?
Subscription typically adds 15 to 25 points over the same category's transactional rate. Pet care with autoship can hit 40 to 60% versus 28 to 35% transactional. Most published benchmarks are blended, so if you are pure one-time purchase, read the lower end of every range.