The state of D2C, explored.
See what shoppers typically buy, ask, and expect — across 12 categories and 8 countries — then benchmark your own store against it.
Explore the market:
What “normal” looks like in your category.
Pick your category to see the typical ranges for order value, conversion, returns, and repeat buying — in plain English, no dashboard degree required.
Typical order value (AOV)
$40–$75
Visitors who buy (conversion rate)
1.8–3.2%
Orders sent back (return rate)
4–8%
Customers who return to buy again (repeat purchase)
25–35%
Typical order value by category (midpoint of each range, USD)
See the numbersHide the numbers
| Category | Order value (USD) | Conversion | Returns | Repeat purchase |
|---|---|---|---|---|
| Beauty & Skincare | $40–$75 | 1.8–3.2% | 4–8% | 25–35% |
| Fashion & Apparel | $70–$120 | 1.2–2.2% | 15–30% | 18–28% |
| Health & Wellness | $50–$90 | 1.5–3% | 3–7% | 30–45% |
| Food & Beverage | $45–$80 | 2–4% | 1–3% | 35–50% |
| Home & Living | $90–$180 | 1–2% | 6–12% | 12–20% |
| Pet Supplies | $50–$90 | 2–3.5% | 3–6% | 35–50% |
| Electronics & Gadgets | $120–$250 | 0.8–1.8% | 8–15% | 10–18% |
| Jewelry & Accessories | $100–$220 | 0.6–1.4% | 8–15% | 10–18% |
| Sports & Outdoors | $80–$150 | 1–2% | 8–14% | 15–25% |
| Baby & Kids | $60–$110 | 0.8–2% | 8–14% | 25–40% |
| Toys & Hobbies | $50–$95 | 1.4–2.6% | 5–10% | 18–30% |
| Coffee & Tea | $35–$60 | 2.5–4.5% | 1–3% | 40–55% |
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
When your year actually happens.
Typical demand rhythm by month — 100 is an average month for the category, 140 is about 40% busier. Use it to plan inventory and support staffing, not to predict the future.
Beauty & Skincare (relative demand index)
Typical peak: Nov & Dec
Gifting season (November–December) is the big lift; late summer runs quiet. Stock hero SKUs and gift sets before November.
See the numbersHide the numbers
| Month | Demand index (100 = avg month) |
|---|---|
| Jan | 90 |
| Feb | 95 |
| Mar | 95 |
| Apr | 95 |
| May | 100 |
| Jun | 90 |
| Jul | 90 |
| Aug | 95 |
| Sep | 100 |
| Oct | 105 |
| Nov | 140 |
| Dec | 125 |
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
Every category, at a glance (click a row to switch)
Indices are curated editorial pattern shapes, rounded to the nearest 5 — they show a category’s typical rhythm, not a forecast for any store.
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
Same store, different country, different shopper.
Switch markets to see how delivery expectations, spending, and shopping habits shift — every chart on this page follows your pick.
United States
The baseline D2C market: fast free shipping is widely expected, and easy returns are a big trust signal.
- Delivery window shoppers expect
- 3–5 days
- Local currency
- USD
- Spend index vs. US (rough)
- 1.00
- Beauty & Skincare order value here
- ≈ $40–$75 (USD)
All money shown in USD so markets stay comparable.
How fast shoppers expect delivery (typical window, days)
See the numbersHide the numbers
| Country | Delivery window (days) | Spend index vs. US (rough) | Currency |
|---|---|---|---|
| United States | 3–5 | 1.00 | USD |
| United Kingdom | 2–4 | 0.90–1.05 | GBP |
| Canada | 3–7 | 0.90–1.05 | CAD |
| Australia | 3–7 | 0.75–0.90 | AUD |
| Germany | 2–4 | 0.90–1.05 | EUR |
| France | 2–5 | 0.85–1.00 | EUR |
| Netherlands | 1–3 | 0.85–1.00 | EUR |
| India | 3–7 | 0.15–0.35 | INR |
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
How does your store compare?
Type your numbers and see where you land against the typical range for Beauty & Skincare in United States. Your numbers never leave your browser.
Comparison uses curated typical ranges, adjusted by a rough United States spend index. It’s a guide, not a grade — every store is different.
Order value — yours vs. typical ($40–$75)
Your $60 is inside the typical range for Beauty & Skincare stores in United States.
Conversion — yours vs. typical (1.8–3.2%)
Your 1.8% is inside the typical range for Beauty & Skincare.
At $60 × 500 orders, you’re doing about $30,000 a month. Solidly in range — the next win is usually repeat purchases.
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
How much is walking out of your cart?
Most carts never make it to checkout. Put in your traffic and see the typical value left behind each month — and the slice that follow-ups usually win back.
Assumptions (all curated typical ranges):
- 4–8% of visitors start a cart
- 65–75% of started carts are abandoned
- Well-timed follow-ups typically win back 5–15% of the abandoned value
Simple multiplication, rounded — an honest ballpark, not a forecast. Your real add-to-cart rate may differ. Nothing you type leaves your browser.
Carts started / mo (est.)
800–1,600
Carts left behind / mo (est.)
500–1,200
roughly $30,000–$70,000 in value
Typically recoverable with follow-ups / mo
$1,500–$10,000
An estimate from the curated ranges on the left — wide on purpose, because honest ranges beat precise-looking guesses.
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
How many tools are talking to your shoppers?
Tick the kinds of tools you run. We’ll map which shopper-facing jobs overlap, which fall through the cracks — and what changes when one brain does all of them.
The shopper-facing jobs (3 tool categories selected)
- Overlap × 2
Answer shopper questions
Sizing, ingredients, compatibility — the pre-purchase back-and-forth.
Handled separately by Helpdesk / shared inbox and FAQ chatbot — each with its own slice of the customer.
- Covered
Handle “where is my order?”
Order status, tracking, delivery windows, address changes.
Handled by Helpdesk / shared inbox.
- Covered
Recommend products
Suggest the right product, upsell, and cross-sell.
Handled by Email & SMS flows.
- Covered
Follow up on abandoned carts
Nudge shoppers who left something behind.
Handled by Email & SMS flows.
- Gap — nobody owns this
Remember each customer
Preferences, past orders, and context that carries across conversations.
- Covered
Hand off to your team
Escalate to a human with the full story attached.
Handled by Helpdesk / shared inbox.
The one-brain read
With 3 tool categories selected, 1 job is done by more than one tool — usually with different answers and separate context — and 1 job has no owner at all. Either way, each tool only ever sees its own slice of the shopper.
cobay’s approach: one agent that does all six jobs with one shared memory of every shopper — so the answer in chat, the cart nudge, and the handoff to your team all come from the same understanding.
A simplified capability map of typical tool categories — an editorial illustration, not a review or price comparison of any specific product. Plenty of stacks work great; the point is where the context lives.
What shoppers ask before they buy.
The recurring pre-purchase questions in Beauty & Skincare — curated themes, ranked by how often they come up. Every unanswered one is a shopper who probably left.
Top questions in Beauty & Skincare
3 of 4 instantly answerable from store data
“Will this work for my skin type?”
Product fitAn agent grounded in your store data can answer this instantly“Is it fragrance-free and safe for sensitive skin?”
Product fitAn agent grounded in your store data can answer this instantly“When will my order arrive?”
ShippingAn agent grounded in your store data can answer this instantly“It broke me out — can you make an exception to the return policy?”
ReturnsBest finished by a human — with the context handed over
Curated question themes — assembled editorially from public industry research and anonymized aggregate themes, ranked by how often each theme shows up. Not a measurement of any store.
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
The United States twist on the same questions
“Where is my order?” is a top question in every market. In United States, shoppers typically expect delivery within 3–5 days — after that, the question marks start piling up.
The baseline D2C market: fast free shipping is widely expected, and easy returns are a big trust signal.
Pick a different country in the filter bar to see how expectations shift.
Talk to the data. Like it’s a person.
This is how cobay thinks: one brain you can just ask. Here it’s scripted over this page’s curated dataset — on your store, it answers from your real products, orders, and policies.
Pick a question below — answers come straight from the curated dataset on this page.
A scripted demo — no live AI here. Every answer is assembled from the curated industry benchmarks on this page (v1.1, updated July 2026). cobay’s real agent answers from your store’s live data. Tip: press / anywhere on this page to jump here.
Take this view with you.
Your current picks, composed into one clean summary — copy the link for your team, print it for the planning meeting, or grab the whole dataset as a CSV.
cobay Market snapshot
Beauty & Skincare United States
Curated industry benchmarks
v1.1 · updated July 2026
- Typical order value (USD, adjusted)
- $40–$75
- Typical conversion rate
- 1.8–3.2%
- Typical return rate
- 4–8%
- Typical repeat purchase rate
- 25–35%
- Delivery window shoppers expect
- 3–5 days
- Typical demand peak
- Nov & Dec
- #1 pre-purchase question
- “Will this work for my skin type?”
What Beauty & Skincare shoppers ask before buying
- “Will this work for my skin type?”
- “Is it fragrance-free and safe for sensitive skin?”
- “When will my order arrive?”
- “It broke me out — can you make an exception to the return policy?”
The baseline D2C market: fast free shipping is widely expected, and easy returns are a big trust signal.
Curated industry benchmarks · updated July 2026 (v1.1) · how we source this
All of this happens in your browser — no signup, no server, no tracking of what you build.
Where these numbers come from.
Every figure on this page is a curated industry benchmark: a rounded, typical range the cobay team compiles from published industry benchmarks — sources like the Baymard Institute, Shopify commerce reports, Dynamic Yield and Littledata vertical benchmarks, IRP Commerce market data, and NRF returns research. Nothing here is live data, and nothing is a measurement of any named company or store.
We publish ranges instead of single numbers on purpose — real stores vary a lot, and a range is the honest shape of a benchmark. Where a figure is adjusted for a country, we use a rough editorial spend index (clearly labeled), never a precise claim.
The dataset is versioned. This page shows v1.1, updated July 2026. When we re-check the ranges or add categories and countries, the version and date change together — if you spot something that looks off, tell us at support@cobay.com.
A few surfaces need their own honesty notes. The Season Radar shows curated editorial pattern shapes (100 = an average month for that category, rounded to the nearest 5) — a typical rhythm, never a forecast. The Shopper Question Map lists curated question themes ranked editorially, not measured frequencies. The Stack X-Ray is a simplified capability map of generic tool categories — it names no products, quotes no prices, and makes no claims about any specific company. And Ask the Market is a scripted demo whose answers are assembled from this same dataset — there is no live AI on this page.
The “Benchmark my store”, cart-rescue, and stack tools run entirely in your browser — the numbers you type are never sent to us or anyone else.
These are the benchmarks. cobay knows your store.
cobay’s agent understands your products, orders, and customers in real time — and uses it to sell and support, every day.