DTC benchmarks only mean something within a category. Directional 2026 ranges: supplements CAC $40 to $80 against AOV $50 to $90 with 40 to 60% repeat; beauty CAC $25 to $60, AOV $40 to $70; apparel CAC $25 to $50, AOV $60 to $120; food and beverage CAC $30 to $70; home and durables CAC $40 to $120 with single-order payback required.
- Most benchmarks blend categories that have nothing in common, which makes founders panic for no reason.
- Payback windows range from one to three months for supplements to single-order for durables.
- Measure yourself against your own category math, not a blended average.
Directional benchmarks by category, 2026: supplements CAC $40–$80 against AOV $50–$90, repeat rate 40–60%, payback 1–3 months. Beauty CAC $25–$60, AOV $40–$70, repeat 30–50%, payback 2–4 months. Apparel CAC $25–$50, AOV $60–$120, repeat 20–35%, payback 4–8 months. Food and beverage CAC $30–$70, AOV $35–$60, repeat 40–60%, payback 3–6 months. Home and durables CAC $40–$120, AOV $90–$250, repeat 10–20%, single-order payback required. The chart below has all five rows. This paragraph exists because a card buried below the fold does not serve the founder who already knows what they came for. For the full picture across both brands and apps, see the 2026 DTC and Shopify app benchmarks.
The trouble with almost every benchmark floating around is that it blends categories that have nothing in common. A supplements founder measuring themselves against apparel math panics for no reason. A furniture founder comparing against a consumable repeat rate draws a false conclusion about their retention. These categories are not in the same game. Their customers buy on different rhythms, their order values sit a decimal place apart, and their payback windows are built on completely different assumptions.
Take everything here as directional. These are pattern-reading ranges from operating across multiple verticals at WIN Brands Group, not audited industry figures. The spread inside any single category is wider than the gap between categories. Use the card to form a hypothesis, then go read your own numbers honestly.
How to actually
use a benchmark
card like this.
A benchmark is a question, not an answer. When your number lands outside the range on this card, the useful response is not "fix it" or "ignore it." It is "why." A repeat rate below your category usually points at product or post-purchase, not at your ads. A CAC above your category might be fine if your order value and repeat rate are also above it. The card only earns its keep when you read the four metrics together.
The four I track on every brand are the four on this card. Acquisition cost, what it costs to land a customer. Order value, what they spend the first time. Repeat rate, whether they come back. And payback, how long until that customer has returned the cash you spent to get them. Those four describe the engine. Everything else is detail hanging off them. If you want to know the most you can actually pay on that first line, my free maximum allowable CAC calculator computes it from your margin and payback target.
One rule before you read the numbers: a healthy brand does not need to beat the card on every line. It needs the four numbers to fit together. A low order value is fine if customers reorder constantly. A high acquisition cost is fine if the order value and repeat rate are high enough to pay it back fast. The card shows category-typical combinations. Your job is to make your own four numbers form a coherent story, not to win every row.
The card itself.
Screenshot it.
Then read on.
Here it is, the whole point of the piece. Five categories, four metrics each, all directional. AOV is average first order value. Repeat rate is the rough share of customers who buy again within the first year. Payback is the typical window to recover acquisition cost on a blended basis.
| Category | CAC / AOV | Repeat rate | CAC payback |
|---|---|---|---|
Supplements | CAC $40–$80 · AOV $50–$90 | High, 40–60% | Fast, 1–3 months |
Beauty / skincare | CAC $25–$60 · AOV $40–$70 | Medium-high, 30–50% | Fast, 2–4 months |
Apparel | CAC $25–$50 · AOV $60–$120 | Medium, 20–35% | Medium, 4–8 months |
Food / beverage | CAC $30–$70 · AOV $35–$60 | High, 40–60% | Medium, 3–6 months |
Home / durables | CAC $40–$120 · AOV $90–$250 | Low, 10–20% | Slow, single order |
That is the card. Notice it does not give you a single CAC number, because a single number would be a lie. It gives you CAC next to the order value that has to justify it, which is the only way the figure means anything.
Reading the rows
the way an
operator would.
Supplements and food are the consumable categories, and the card shows it. High repeat rates, fast payback, because the product runs out and the customer comes back on a predictable clock. That rhythm is why those categories can stomach a higher acquisition cost relative to order value: the second, third, and fourth orders are where the brand actually makes its money. If you run a consumable and your repeat rate is below the range, that is a product or post-purchase problem, and no amount of ad spend fixes it.
Beauty sits close behind, with replenishment driving repeat but slightly more one-and-done risk than a true consumable. Apparel is the middle of the deck: decent order value, medium repeat, a payback window that stretches because customers buy on seasons and moods, not on a schedule. Home and durables are the outlier. High order value, low repeat, and often a single-purchase business where you must recover acquisition cost on the first order or not at all.
The home row is the one founders misread most. They see a high order value and assume the economics are easy. They are not. When a customer buys a sofa once and never again, your entire model rests on first-order contribution. That is a completely different discipline from a supplements brand that can lose money on order one and clean up on the reorder. I get into why these windows diverge in CAC payback by vertical.
Consumables forgive a slow first order. Durables do not. If you sell something people buy once, you have to win on the first transaction. If you sell something they reorder, you can be patient on order one and ruthless about retention. Confusing the two is how brands set the wrong CAC ceiling and either starve growth or buy unprofitable customers.
"A single CAC benchmark would be a lie. The number only means something next to the order value that has to justify it and the repeat rate that pays it back."
If your numbers sit outside your category's row, the question is why, not whether to panic. The form takes two minutes.
Where a card
like this quietly
lies to you.
Benchmarks flatten everything that makes your business specific. Two supplements brands in the same range can have completely different futures because one sells a daily product and the other sells a thirty-day cleanse people do once. The card cannot see that. It also cannot see your margin, which is the number that actually decides whether your CAC is affordable. A $60 acquisition cost is a triumph at 70 percent contribution margin and a disaster at 25.
The repeat-rate figures are the softest numbers on the card. Repeat behavior depends heavily on how you count it, what window you use, and whether you include subscription customers. I deliberately kept these ranges wide because a tight number here would imply a precision that does not exist. Treat the repeat column as "high, medium, or low for the category," not as a target to hit to the decimal.
And the biggest distortion of all: lifetime value assumptions. Half the brands quoting a glorious payback window are leaning on an LTV figure that bakes in years of repeat purchases that have not happened yet. The card sidesteps that by anchoring payback to recovering acquisition cost, not to some projected lifetime. If you want to see how the LTV story gets inflated, I take it apart in the LTV math brands get wrong.
Building the only
card that really
matters: yours.
This reference card is the warm-up. The real exercise is building your own, with your actual numbers, refreshed every quarter. Pull your blended acquisition cost, your true first-order value, your one-year repeat rate, and your honest payback window. Write them next to the category range. Where you beat the range, understand why so you can protect it. Where you trail it, decide whether it is a problem to fix or a deliberate trade you are making.
The brands I have watched compound all do a version of this. They know their four numbers cold, they know how those numbers move when they push spend, and they never confuse the industry average with their own truth. The average is a crowd. Your card is your business.
Do one more thing the generic benchmarks never tell you to do: segment your own card by acquisition channel and by cohort. Your blended CAC hides a healthy channel subsidizing a bad one. Your blended repeat rate hides a great cohort propping up a weak one. Once you split the card that way, you stop managing to an average and start managing to the parts of the business that actually pay you back. That is the difference between a founder who quotes benchmarks and an operator who runs the math, and it is what pairs naturally with knowing your contribution margin cold.
The other thing to add to your card is a channel column. Brands running heavy paid social often see blended CAC that looks fine until they segment by platform. Meta might be delivering $35 CAC while TikTok runs $90. The blended $55 masks a bad channel that is dragging money out the door. Every dollar of budget you reallocate from the bad channel to the good one improves your economics without touching the product or the customer experience at all. That is the math behind DTC acquisition playbooks at scale. Once your channel CAC is clear, the max allowable CAC conversation becomes much more useful, and I break down how to set that ceiling in the max allowable CAC post.
One more layer: cohort segmentation. Brands that launched in a low-cost acquisition environment often have early cohorts with economics that look nothing like what they can replicate today. If your repeat rate and payback figures include those vintage cohorts, the averages flatter you. When you strip back to last-twelve-month cohorts only, you get the true current-state economics, which is the number that matters for any forward planning. The DTC financial stack by stage covers how these metrics evolve as the brand scales past the inflection points.
Common
questions
on DTC benchmarks.
What is a good CAC for a DTC brand?
Depends entirely on your category and order value. Supplements and beauty CAC runs $25 to $80, justified by high repeat rates and fast payback. Apparel sits at $25 to $50 against a higher order value. Home and durables can absorb $40 to $120 only if first-order contribution margin covers it, because repeat rates are low. The CAC number is meaningless without the AOV and repeat rate sitting next to it.
What is a healthy repeat purchase rate?
Consumable categories like supplements and food reach 40 to 60 percent repeat within year one. Beauty runs 30 to 50 percent. Apparel sits at 20 to 35 percent. Home and durables are structurally low at 10 to 20 percent. Beating your category range signals strong retention; trailing it usually points to a post-purchase or product problem, not a marketing problem. See subscription churn for DTC for the retention mechanics.
What is a healthy CAC payback period?
Consumables like supplements and food achieve payback in 1 to 3 months because of fast, predictable reordering. Beauty runs 2 to 4 months. Apparel stretches to 4 to 8 months. Home and durables often require recovering acquisition cost on the first order alone. Anything pushing past 12 months creates a compounding cash flow problem at scale: you keep spending to acquire before the prior cohort has paid back. The full breakdown by vertical is in DTC CAC payback by vertical.
Why do DTC benchmarks vary so much between sources?
Because most published benchmarks blend categories with nothing in common and use different counting conventions. A supplements brand and an apparel brand have completely different repeat dynamics. CAC figures vary by channel, by acquisition mix, and by how brands count the denominator. Use category-specific ranges and confirm the counting convention before comparing. That is what makes this card useful: it is sorted by category, not averaged across everything.
How does this card relate to the DTC Growth Scorecard?
The benchmark card gives you category-level context. The DTC Growth Scorecard helps you assess where your brand sits on the growth curve as you scale toward enterprise, including whether your unit economics are scaled appropriately for your stage. Use the card to sanity-check individual metrics; use the scorecard to diagnose the overall business trajectory.
Screenshot the card, then go build your own. If you want a second set of eyes on whether your numbers are healthy for your category, read payback by vertical, check your contribution margin math, and look at where you stand on the unit economics by category breakdown. Then send me your four numbers if you want a real read on which row you actually live in.
Read your numbers against the right card.
I help DTC brands figure out whether their metrics are healthy for their category, not the average. Co-founded WIN Brands Group across multiple verticals, sold getuptime.co to Tiny. I have seen the spread inside categories, not just the headline averages.
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