The benchmark table
All figures below use the customer-level formula (customers with 2+ orders ÷ total customers) over a rolling 12-month window. This is the standard methodology and the one our free tool uses.
| Category | Below average | Average | Strong | Top tier |
|---|---|---|---|---|
| Food & beverage | < 25% | 30–38% | 38–45% | 45%+ |
| Supplements & vitamins | < 25% | 30–38% | 38–44% | 44%+ |
| Beauty & skincare | < 20% | 25–33% | 33–40% | 40%+ |
| Pet supplies | < 20% | 25–30% | 30–35% | 35%+ |
| Health & wellness | < 20% | 25–30% | 30–35% | 35%+ |
| Apparel (mid-market) | < 15% | 18–25% | 25–32% | 32%+ |
| Apparel (luxury) | < 10% | 12–18% | 18–25% | 25%+ |
| Home goods & décor | < 10% | 12–18% | 18–22% | 22%+ |
| Electronics & gadgets | < 8% | 10–15% | 15–20% | 20%+ |
| Jewellery & accessories | < 7% | 9–11% | 11–15% | 15%+ |
| Furniture | < 6% | 8–12% | 12–15% | 15%+ |
Visualized: how much the rates vary
The midpoint of each vertical's average range, shown side by side. The spread is enormous — a 5x difference between the top and bottom categories.
Why the gaps are so large
Three factors explain almost all the variation between verticals:
1. Consumption speed
Products that get used up — food, supplements, skincare — have a natural reorder cycle. The product itself creates the next purchase occasion. Durable goods (furniture, electronics) don't have this. Nobody buys a desk every quarter.
2. Average order value
Higher-priced purchases happen less frequently. A $12 bag of coffee has almost no friction to reorder. A $1,200 necklace requires a new occasion and a new decision. Price and repeat rate are inversely related within almost every dataset we've looked at.
3. Purchase occasion
Some products are bought for yourself, routinely. Others are bought as gifts, seasonally, or for one-off occasions. Jewelry and home décor purchases are often occasion-driven, which means the customer might not have a reason to come back for months or years — regardless of how much they liked the product.
A "low" repeat rate isn't necessarily a problem if your category naturally has low repeat frequency. The question isn't "is 10% good?" — it's "is 10% good for jewellery?" And for jewellery, yes, it is.
What these benchmarks don't tell you
External benchmarks answer one question: "Am I in the right ballpark?" They can't tell you why customers aren't coming back, when the drop-off happens, or which products drive the most repeats.
For that, you need your own data. The most useful comparison isn't your store vs the benchmark — it's your store this quarter vs last quarter. If your January cohort had a 22% repeat rate and your April cohort has 26%, your retention improved by 4 points. That's a more actionable insight than knowing the industry average.
How to read these numbers correctly
- Find your vertical in the table above.
- Check your own rate — use our free tool or calculate it manually.
- Locate yourself in the below-average / average / strong / top-tier range.
- Look at the trend, not just the snapshot. If you're "average" but improving, you're in better shape than a "strong" store that's declining.
Don't panic if you're below average. Don't celebrate if you're above. The benchmark tells you where you are. What you do next — improving retention without paid apps — is what matters.
Methodology notes
These benchmarks are compiled from published DTC retention studies, platform analytics reports, and data from tools that aggregate Shopify store metrics. Key sources include studies by Yotpo, Klaviyo, and independent analysts covering 100,000+ DTC customers.
All figures use the customer-level formula over a 12-month rolling window. We present ranges rather than single numbers because even within a vertical, store size, product mix, and market position create significant variation. A single "average" creates a false sense of precision.