E-commerce Retention Rate Benchmarks: What Good Looks Like in 2026

"Is our retention rate good?" is one of the most common questions e-commerce operators ask, and one of the hardest to answer without context. A 30% annual retention rate can be excellent for a fashion brand selling occasional statement pieces and worrying for a consumable product with a natural replenishment cycle.

This guide covers retention benchmarks across e-commerce verticals, business models, and AOV ranges, plus the methodology to actually calculate and interpret your numbers. At Scentbird we tracked these for over a decade across millions of subscribers, so most of what follows comes from real cohort behavior rather than survey data.

How to calculate e-commerce retention rate

Before looking at benchmarks, align on how retention is calculated. There are several valid approaches and the one you choose materially changes the number.

Basic retention rate

Retention Rate = (Customers Who Purchased in Period / Customers Who Existed at Start of Period) x 100

If you had 10,000 customers at the start of the year and 3,200 made at least one purchase during the year, your annual retention rate is 32%.

The formula requires defining what "customers who existed at start of period" means. The most common approach is to count anyone who made at least one purchase before the period began. Some brands apply a recency filter, only counting customers whose last purchase was within a certain window, to keep long-lapsed buyers from inflating the denominator.

Cohort retention rate

Cohort retention is more granular and more useful for tracking trends. Group customers by their acquisition month, then measure what percentage of each cohort makes a purchase in each subsequent month.

A cohort retention table typically looks like this:

This format reveals whether retention is improving (newer cohorts retaining better than older ones) and how it decays over the customer lifecycle.

Repeat purchase rate

A simpler proxy for retention:

Repeat Purchase Rate = (Customers with 2+ Orders / Total Customers) x 100

Useful as a diagnostic, but do not confuse it with retention rate. A high repeat purchase rate combined with declining recent cohort retention usually means you are leaning on a loyal legacy base while failing to retain new customers. We saw this pattern at Scentbird more than once, and it is dangerous because the headline number looks fine.

Retention rate benchmarks by vertical

The benchmarks below are typical ranges based on industry data and the brands we work with. Your specific numbers will vary by product, pricing, market position, and customer experience.

Subscription e-commerce

Subscription models have the most directly measurable retention because cancellation is an explicit event.

• Monthly retention rate: 92-96% (4-8% monthly churn)
• Annual retention rate: 55-70%
• 12-month cohort retention: 45-65%

Subscription retention varies dramatically by category. Consumable subscriptions (coffee, supplements, pet food) tend to retain better than curation subscriptions (clothing boxes, beauty samples) because the value proposition stays consistent month to month.

The metric I cared about most at Scentbird was the churn cliff: the point at which monthly churn rate stabilizes. Most subscription brands see elevated churn in months two through four as uncommitted customers leave, then it flattens to a more predictable rate. Where it flattens tells you almost everything about your long-term economics.

Direct-to-consumer brands

DTC retention varies enormously based on product category and purchase cycle.

• Annual repeat purchase rate: 25-40%
• 12-month cohort retention: 20-35%
• 24-month cohort retention: 15-25%

DTC brands with consumable products (skincare, supplements, food) sit at the higher end. Durable goods brands (furniture, electronics, luggage) have lower frequency by nature and should focus on different metrics like brand advocacy and referral rates.

Fashion and apparel

Fashion is seasonal and trend-driven, which creates its own retention dynamic.

• Annual repeat purchase rate: 20-35%
• 12-month cohort retention: 18-30%
• Average order frequency (active customers): 2.5-4 times per year

Fast fashion sees higher frequency at lower per-order value. Premium fashion sees lower frequency but higher AOV and stronger brand loyalty among repeat buyers.

Beauty and personal care

Beauty has some of the strongest retention characteristics in e-commerce, driven by replenishment and routine-based usage.

• Annual repeat purchase rate: 30-45%
• 12-month cohort retention: 25-40%
• Average order frequency (active customers): 3-5 times per year

Skincare retains better than color cosmetics. Customers find products that work for their skin and stay with them. Color has a higher exploration dynamic, which boosts frequency but also makes brand-switching easier.

Food and beverage

Consumable food and beverage brands benefit from natural replenishment cycles.

• Annual repeat purchase rate: 35-50%
• 12-month cohort retention: 30-45%
• Average order frequency (active customers): 4-8 times per year

The challenge for food brands is retail availability. A customer who loves your product might switch to buying it at the grocery store, which shows as churn in your e-commerce data even though they are still a customer.

Health and supplements

Supplements retain well when the customer feels a benefit.

• Annual repeat purchase rate: 35-50%
• 12-month cohort retention: 30-45%
• Average order frequency (active customers): 4-6 times per year

Supplement retention is bimodal. Customers either become long-term users or churn quickly. The first 60 days are where the habit and perceived benefit get established, and almost nothing else matters as much.

Home and furniture

Long purchase cycles by nature. Do not benchmark these against consumables.

• Annual repeat purchase rate: 10-20%
• 12-month cohort retention: 8-15%
• Average time between purchases: 12-24 months

For home brands, retention success usually means capturing the customer's next relevant purchase, which might be a year or more away. Email engagement retention (keeping the customer engaged between purchases) is often a better leading indicator than purchase retention.

Month-over-month vs. annual retention

Monthly and annual retention tell different stories and serve different purposes.

Monthly retention is most useful for subscription businesses and brands with short purchase cycles (under 60 days). It gives fast feedback on whether changes to product, pricing, or experience are actually moving customer behavior.

Annual retention fits brands with longer cycles. It smooths out seasonality and gives a clearer picture of long-term loyalty. The downside is that it lags. By the time annual retention drops, the underlying problems have been building for months.

Cohort retention curves give the most complete picture because they show how retention develops over time per group. They reveal both the rate of decay and where retention stabilizes.

Benchmarks by AOV range

Average order value correlates meaningfully with retention patterns.

Low AOV (under $30)

• Repeat purchase rate: 30-50%
• Typical purchase frequency: 4-8x per year
• Retention dynamics: Lower switching costs mean customers churn more easily, but the low commitment also makes win-back simpler. Volume and frequency are the primary LTV drivers.

Mid AOV ($30-$100)

• Repeat purchase rate: 25-40%
• Typical purchase frequency: 2.5-5x per year
• Retention dynamics: The sweet spot for many DTC brands. Customers are invested enough to develop loyalty without each purchase requiring serious deliberation.

High AOV ($100-$300)

• Repeat purchase rate: 20-35%
• Typical purchase frequency: 1.5-3x per year
• Retention dynamics: Each purchase is more considered, so the product and experience need to justify the price every time. Customer service and post-purchase experience become primary retention levers.

Premium AOV (over $300)

• Repeat purchase rate: 15-25%
• Typical purchase frequency: 1-2x per year
• Retention dynamics: Brand relationship and emotional connection matter more than transactional factors. VIP treatment, personalized service, and exclusive access drive most of the retention.

Cohort analysis methodology

To produce meaningful retention benchmarks for your own business, you need a solid cohort analysis methodology.

Setting up cohort analysis

1. Define your cohorts. Most commonly, by first purchase month. For seasonal businesses, quarterly cohorts may be more practical.
2. Choose your retention metric. The two common options are "made at least one purchase in period" (binary retention) and "revenue generated in period" (dollar retention). Both are useful. Dollar retention can mask underlying problems if a few big orders compensate for a lot of lost customers.
3. Set your time periods. Track at month 1, 2, 3, 6, 12, and 24 to see early-stage and long-term patterns.
4. Calculate for each cohort. Compute the percentage of customers (or revenue) retained at each time period.
5. Visualize trends. Plot cohort retention curves to compare cohorts. Are newer cohorts retaining better or worse than older ones?

Interpreting cohort data

Look for these patterns:

Improving retention curves. If each successive cohort retains better than the previous one at the same time point, your retention work is paying off. That usually reflects improvements to product, onboarding, or customer experience.

Seasonal effects. Holiday cohorts (November/December) often show lower retention because they include gift buyers and deal-seekers who are less likely to become regular customers. Do not be alarmed.

Stabilization point. Most cohort curves show rapid decay in the first few months, then flatten. Where they flatten is your core retention rate, the percentage of customers who become long-term loyalists. Improving that flat line is one of the most impactful things you can do for the business.

Revenue retention vs. customer retention. If dollar retention is significantly higher than customer retention, your retained customers are spending more over time, a good sign of deepening loyalty. If dollar retention is lower, your retained customers may be downgrading or buying less frequently.

Tools like Finsi's retention intelligence module automate this kind of cohort analysis and surface the patterns without manual spreadsheet work, which makes it practical to monitor retention continuously instead of as a quarterly exercise.

Strategies to improve retention

Once you know where your retention sits relative to benchmarks, the question is what to do. Here are the strategies that have consistently moved the number for the brands I have worked with.

Nail the first 30 days

The first 30 days after a customer's first purchase is the most important window for retention. They form their opinion of your brand and decide whether to come back.

Focus on fast, reliable shipping. Send a thoughtful post-purchase email sequence that helps them get value from the product. Ask for feedback. Make the second purchase as easy as possible with relevant recommendations.

Invest in product quality and consistency

No amount of clever marketing can compensate for a product that does not deliver. Product quality is the foundation of retention. Audit your reviews and support tickets for product complaints and address them aggressively.

Build a replenishment engine

For consumable products, time-based replenishment reminders are one of the most effective retention tactics available. Track consumption rates by product and trigger reminders when customers are likely running low. At Scentbird this was one of the highest-ROI flows we ran.

Create switching costs (positively)

Loyalty programs, personalized product profiles, subscription discounts, and accumulated purchase history all create positive friction that makes switching less appealing. The key word is positive. These should add genuine value, not just create annoyance.

Personalize based on behavior

Use customer behavior data to personalize communication and offers. A customer who always buys from a specific category should get recommendations within it, not generic best-sellers. This is where predictive LTV and segmentation come together.

Address churn proactively

Do not wait for customers to leave before trying to retain them. Build systems that flag at-risk customers based on engagement signals and intervene before they churn. Even a simple "we noticed you haven't visited in a while" email can re-engage drifting customers.

Reduce friction everywhere

Every point of friction in the customer experience is a reason not to come back. Audit your checkout, your site speed, your return policy, your support response times. Small improvements compound.

Setting retention goals

With benchmarks in hand, how should you set targets?

Be realistic about your category. A furniture brand targeting 40% annual retention is setting itself up for failure. Use the benchmarks for your vertical and business model.

Focus on relative improvement. If your current 12-month cohort retention is 22%, getting to 26% is real. That 4-point improvement is an 18% relative increase and a meaningful boost to LTV.

Track leading indicators. Retention rate lags. Track email engagement, second purchase conversion, and 30-day repurchase rate to get faster feedback on whether your retention work is moving the underlying behavior.

Segment your targets. Set different retention targets for different customer segments and acquisition channels. Your organic search customers can reasonably be held to a higher standard than customers acquired through aggressive paid campaigns.

Conclusion

Benchmarks give you context, but they are starting points, not destinations. The most valuable insight comes from tracking your own retention over time, understanding the dynamics inside your specific customer base, and systematically testing strategies to improve.

The brands that consistently outperform retention benchmarks share common habits. They obsess over product quality. They invest in post-purchase experience. They use data to flag retention risks early. They treat retention as an ongoing discipline rather than a quarterly project. That is a big part of why we built Finsi.

Know your numbers, understand how they compare, and commit to continuous improvement. In e-commerce, retention is what separates businesses that compound from businesses that churn through customers faster than they can acquire them.

If you want to see your retention rate calculated correctly, by cohort, channel, and product, with benchmarks for your specific vertical, start a free Finsi trial. For retention teams and founders, getting accurate numbers is the first step.

Frequently asked questions

What is a good retention rate for e-commerce?

It depends on your vertical and business model. Consumables (supplements, food, beauty) should target 35-45% annual retention. Fashion and apparel target 20-30%. Subscription boxes target 60-75% at the 90-day mark. If you are below your vertical average, focus on the first 14 days. That is where most of the churn decision gets made.

How do you calculate retention rate in e-commerce?

The standard formula is Retention Rate = (Customers who purchased again in period) / (Customers eligible to repurchase in period). The key word is "eligible." Do not divide by your total customer base, which includes people who bought yesterday and have not had time to repurchase. Use cohort-based calculation: group customers by acquisition month, then track what percentage repurchased in subsequent months.

What is the average repeat purchase rate for DTC brands?

The average DTC brand sees a repeat purchase rate of 25-30%. Top performers in consumable categories (supplements, coffee, skincare) hit 40-55%. The biggest lever for moving repeat purchase rate is timing. Customers who place a second order within 60 days of their first are 3x more likely to become long-term customers than those who wait 120+ days.

How do I improve my e-commerce retention rate?

The five highest-impact retention strategies are: (1) optimize the first 14 days post-purchase with onboarding emails and product education, (2) identify and intervene with at-risk customers before they churn using predictive analytics, (3) build replenishment reminders based on product consumption cycles, (4) create loyalty or subscription programs that add positive switching costs, and (5) recover failed payments through smart dunning, which alone can lift retention by 5-10%.

What retention metrics should I track beyond retention rate?

Track these alongside retention rate: customer lifetime value (LTV) by cohort and channel, LTV:CAC ratio (target greater than 3:1), churn rate on eligible cohorts (not total base), repeat purchase rate, time to second purchase, and Net Promoter Score. The combination gives you a complete picture. Retention rate alone can be misleading if your calculation methodology is off.