A merchant checking their customer retention rate against a generic "good retention is 80%" benchmark may be comparing their store to the wrong business model. Retention rate by industry depends on purchase frequency, contract structure, and switching cost, but also on the measurement period and definition of an active customer. Shopify brands tracking retention alongside loyalty and referral programs, including those running on Rivo, need a benchmark that reflects how often their customers actually buy.
The sections below break down what retention rate by industry actually looks like across ecommerce verticals, subscriptions, and SaaS, how to calculate it correctly, and what separates a genuinely strong rate from a misleading one.
Key Takeaways
- Retention rate by industry is not one number. Compare the same customer definition, cohort, and observation period.
- Shopify’s retail breakdown reports Bluecore figures of 27.4% overall, ranging from 19.1% in jewelry and accessories to 41.2% in health and beauty. These are reported benchmarks, not a universal target for 2026.
- Customer retention and churn are complements only when they use the same starting cohort, period, and activity rules.
- Monthly subscription churn cannot be compared directly with annual ecommerce retention.
- Measure acquisition costs, retention costs, and customer value in your own business rather than assuming a universal cost multiplier.
- Rivo Analytics Home brings program attribution and customer comparisons into one dashboard; attributed revenue is not automatically incremental profit.
What Is Customer Retention Rate and Why Does It Matter?
Customer retention rate measures the share of customers from a starting cohort that a business keeps over a defined period, expressed as a percentage. New customers acquired during that period are excluded from that cohort. For non-subscription stores, define what counts as active or lost before calculating ecommerce churn.
The reason retention rate dominates so much retention marketing discussion is cost. Repeat purchases can spread acquisition spending across more orders, but the economics depend on margins, incentives, service costs, and purchase frequency. Compare your own acquisition and retention spending rather than relying on a fixed four-to-ten or five-to-25 cost ratio.
The benefits of retention depend on whether repeat behavior produces profitable orders. Track the first-to-second-purchase journey and later purchases separately: a higher return rate among repeat buyers does not prove that any one reward caused the next purchase.
Customer retention rate formula: retained customers from the starting cohort ÷ customers in that starting cohort × 100. The common end-minus-new shortcut works when both counts use consistent active-customer rules and new customers subtracted are those included in the ending count.
What Is the Average Customer Retention Rate by Industry in 2026?
Retention rate by industry varies with how often people buy, how much switching costs them, and whether the purchase is a one-time need or a recurring habit. Rivo’s Shopify retention benchmarks offer related context, but every comparison still needs a matching definition.
Ecommerce and Retail Benchmarks
Shopify’s 2026 article attributes an overall retail retention rate of 27.4% to Bluecore and provides this retail benchmark breakdown:
- Jewelry and accessories: 19.1%
- Home goods: 21.4%
- Footwear: 22.2%
- Sports and hobbies: 27.8%
- Apparel: 31.7%
- Department stores: 36.2%
- Health and beauty: 41.2%
Treat those figures as directional context. The cited summary does not specify enough cohort and observation-window detail to establish a like-for-like target for your store. Other compilations use different definitions of retention and repeat purchasing, so combining them into a single 27% to 38% target band would be misleading.
Subscription and Recurring-Revenue Benchmarks
Subscription businesses often renew automatically, so renewal-based retention measures differ from discretionary repeat purchases. Always identify whether a churn figure is monthly, quarterly, or annual. As an illustration, a constant 3.4% monthly churn rate would leave about 66% of a starting cohort after 12 months: 0.966¹² × 100. It would not imply annual retention above 90%. This is an arithmetic example, not an industry benchmark.
Recurly’s 2025 subscription report reported acquisition rates falling from 4.1% in 2021 to 2.8% in 2024. That describes acquisition, not an improvement in retention. It provides context for why retaining existing subscribers matters, rather than a retention benchmark.
Zuora’s 2025 index release describes a company dataset covering 2024 and a separate US consumer survey. Those are different evidence sources: company churn measures and consumers’ stated cancellation reasons should not be treated as the same metric.
The index reported an association between more flexible revenue models and better business outcomes. That does not establish that adding a revenue model causes a specific improvement in customer retention.
Why do subscribers cancel when they do? In the consumer survey accompanying Zuora’s index, 47% of respondents who canceled a subscription in 2024 cited price increases. Recovery tactics also matter: Recurly’s 2024 report summary reported saving 72% of at-risk subscribers through recovery events and recovering $254 million through dunning in the preceding year. These are historical recovery results from its platform, not overall subscriber retention rates.
SaaS Benchmarks
SaaS retention needs its own comparison rules. Contracts, integrations, and data migration can affect switching decisions, but a software market-growth index is not a customer-retention benchmark. Compare customer retention with customer retention, and revenue retention with revenue retention, using the same period and similar customer segments. Rivo’s discussion of B2B retention metrics provides related context, but a retail store should not adopt a software target without checking the underlying metric.
How to Calculate Customer Retention Rate and Churn Rate
Retention rate and churn rate describe opposite outcomes for the same starting cohort when customer status is defined consistently. Differences in periods, denominators, and activity rules can make two published benchmarks incomparable.
Customer retention rate formula:
For a consistent starting cohort, customer retention rate = retained starting customers ÷ starting customers × 100. The standard retention formula is (E − N) ÷ S × 100, where S is the starting customer count, E is the ending count, and N is new customers included in E. For example, S = 1,000, E = 950, and N = 150 gives 80% retention. For ecommerce, specify whether retained means a repeat purchase within 90 days, within a year, or another explicit activity rule.
Churn rate formula:
Customer churn rate = customers lost from the starting cohort ÷ starting customers × 100. With the same cohort and binary retained/lost rules, churn equals 100% minus retention. Revenue churn measures lost revenue rather than customer counts, so losing a few large accounts can affect it more than losing many small ones.
Net revenue retention formula:
Net revenue retention (NRR) = (starting recurring revenue + expansion − contraction − churned revenue) ÷ starting recurring revenue × 100. All components refer to the same starting customer cohort; revenue from newly acquired customers is excluded. NRR can exceed 100% when expansion offsets losses. Gross revenue retention excludes expansion and therefore cannot exceed 100%. Neither measure is interchangeable with customer retention.
Repeat purchase rate vs. retention rate:
Repeat purchase rate and retention rate are often used interchangeably but are not identical. A repeat purchase rate can measure customers with more than one purchase divided by unique purchasing customers within a specified reporting window. A cohort retention rate follows a defined starting group over time. Some dashboards use lifetime purchase history to identify returning buyers, so check the exact definition before comparing figures.
What Is a Good Customer Retention Rate?
"Good" retention is entirely relative to the industry and the purchase cycle it serves, which is the core reason flat benchmarks on retention rate mislead more than they help.
Published industry lists often combine businesses with different contract lengths and definitions of customer activity. An 80% figure cannot be a useful ecommerce target until its period, cohort, and methodology are known. A percentage without that context may be accurate within its original dataset but unsuitable for your dashboard.
For ecommerce, use your own comparable cohorts as the starting point and consult external category benchmarks only when their definitions match. A 30% rate alone is not enough to classify a store as healthy or a subscription business as struggling. The observation window, purchase cycle, and economics determine what that number means.
One caution worth repeating: a single industry label can hide very different purchase journeys. A low-frequency jewelry purchase and a replenishable beauty product create different opportunities to return. Benchmark against the narrowest comparable vertical available, and keep the measurement rules consistent.
Which Customer Retention Metrics and KPIs Should You Track?
Retention rate alone is a lagging indicator. Pairing it with a few supporting metrics turns it into something a retention team can act on.
- Customer lifetime value (CLV): Average order value × purchase frequency × customer lifespan estimates lifetime revenue when the units match. A profit-based estimate must also account for margins and relevant costs. Assess retention alongside customer value and contribution profit.
- Net revenue retention (NRR): NRR shows whether expansion revenue from an existing cohort offsets churn and downgrades; it is most directly suited to recurring-revenue models.
- Repeat purchase rate: Track repeat buyers using an explicit order-count rule and reporting window, separately from cohort retention.
- Churn rate (voluntary and involuntary): Separate cancellations from payment-related losses so recovery work addresses the right cause. Neither category has a universal rate or effort priority.
- Rivo-attributed revenue and ROI: Rivo Analytics Home reports program revenue and customer comparisons. Its revenue-to-subscription-cost ROI view is an attribution measure; it does not deduct every program cost or prove incremental profit.
What Factors Affect Customer Retention Rates?
Several forces move customer retention rates independently of how well a brand executes its marketing, which is why cross-industry retention comparisons need context before they are useful.
Purchase frequency and category. A consumable product creates repeat occasions that a durable good may not. Examine time to second purchase and cohort return rates against the expected replenishment cycle. A new-to-returning customer ratio also reflects acquisition volume, so it cannot by itself establish that one category retains customers better than another.
Switching cost. Contracts, data migration, and integration effort can discourage switching. Ecommerce customers may face fewer technical barriers, but brand preferences, subscriptions, and benefits can still influence their decisions. High switching costs do not guarantee an 80% retention rate.
Pricing changes. The Zuora consumer survey identifies price increases as a common cancellation reason. For ecommerce, test how promotions affect repeat purchases and margin rather than assuming discount-driven orders represent durable loyalty.
Billing and plan flexibility. Recurly’s 2025 report overview says 71% of subscription businesses in its report offered monthly and annual plans. That documents plan availability, not proof that offering both causes lower churn.
Which Strategies Improve Your Customer Retention Rate?
Improving a retention number starts with the mechanics that drive repeat behavior, not with the benchmark itself.
- Build a loyalty structure around actual repeat triggers. Match rewards to customers’ reasons to return, then measure repeat behavior and margin. A statistic about repeat buyers’ revenue share does not prove that a particular program caused their purchases.
- Reward the second purchase specifically. Test an incentive during the first-to-second-purchase window and compare results with a suitable baseline or holdout. Its value depends on your product cycle and incentive costs.
- Use store credit and cashback to encourage repeat behavior. Rivo supports configurable cashback offers. Outstanding rewards can create future obligations; Rivo’s liability guidance explains why accounting treatment depends on the program and business. Expiry does not justify a blanket “no balance-sheet liability” claim.
- Give retention programs a referral layer. Rivo’s HexClad case study reports over $450K in referral revenue in the first 90 days. The brand’s Director of Retention also reported $100+ higher LTV for referred customers than typical customers. These are reported outcomes, not a controlled estimate of incremental revenue.
- Tier your highest-value customers deliberately. Rivo’s Kitsch case study reports over $5.8M in loyalty-attributed revenue and an 8.7× repeat-purchase comparison for its highest tier. The published comparison does not establish that tiering alone caused the difference; already-loyal customers may qualify for higher tiers.
- Address involuntary churn separately from voluntary churn. Review failed payments and recovery performance alongside cancellations. Prioritize work by recoverable value, customer impact, and implementation effort rather than a universal churn-rate hierarchy.
How Can Customer Feedback Help You Retain Customers?
Retention strategy built purely on transaction data misses the reason customers leave before they leave. A voice-of-the-customer program closes that gap by collecting direct feedback at key moments, post-purchase, post-support-ticket, or pre-cancellation, and feeding it back into the product and retention roadmap.
The goal is to catch the signals that precede churn: a drop in order frequency, a support ticket that goes unresolved, or a survey response flagging dissatisfaction with price or selection.
A simple feedback loop has three parts. First, a short survey triggered at a specific moment, ideally two to three questions, asking about satisfaction with the most recent order or interaction. Second, a tagging system that routes negative responses to a retention or support team rather than letting them sit in a dashboard. Third, a scheduled review of the aggregated feedback against the retention and churn numbers from the same period, so the qualitative input is checked against what customers are actually doing, not just what they say.
Reviewing feedback against actual behavior can help the team distinguish recurring issues from isolated complaints and notice valuable customers whose order frequency is declining.
How Rivo Helps Shopify Brands Measure and Improve Retention
A retention technology stack typically spans three layers: communication (email and SMS), loyalty and rewards, and analytics that ties program activity back to revenue.
For Shopify brands, Rivo offers retention products spanning Loyalty, Accounts, Memberships, Cashback, and Referrals. Available features and implementation requirements depend on the products and plan selected; confirm those details before assuming every feature is included in one subscription.
For merchants migrating from another loyalty platform, start with Rivo’s getting-started guides and confirm which customer records, balances, and program settings can transfer.
On the analytics layer, Rivo Analytics Home compares program-attributed revenue with subscription cost. Its illustrative 12.5× ROI means $12.50 in attributed revenue per $1 of subscription cost. To decide whether a program pays for itself, also account for reward costs, margins, operations, and how much revenue would have occurred without it.
The dashboard also compares customer segments on order value, repeat purchasing, and purchase frequency. These comparisons can identify patterns worth testing, but do not isolate a program’s causal effect. Rivo’s analytics documentation distinguishes its attributable activity from Shopify’s store totals. Shopify brands can explore Rivo to connect retention programs with these reporting tools.
Frequently Asked Questions
What is a good customer retention rate by industry?
A good rate depends on the category, period, cohort, and definition of activity. Compare your store with similar businesses using matching rules, and review changes in your own cohorts over time. A generic 80% target or 27% to 38% range is not enough to judge performance.
What is the average customer retention rate for ecommerce?
Shopify’s benchmark summary reports 27.4% overall retail retention from Bluecore. It is a reference point rather than a universal current ecommerce average: the summary does not supply enough observation-window detail to establish a direct comparison with every store.
What is the difference between retention rate and repeat purchase rate?
Retention rate follows a defined starting cohort over a set window and excludes newly acquired customers from that cohort. Repeat purchase rate counts repeat buyers under the report’s order-history and time-window rules. Both require a clear definition, and they need not produce the same percentage.
Why is ecommerce customer retention lower than subscription retention?
One-time purchases and auto-renewing subscriptions define customer activity differently. A customer who has not bought another durable product may simply have no current need; a subscriber may still be active without making a fresh purchase decision. Whether ecommerce retention is lower depends on comparable cohorts and periods, so do not compare a monthly churn percentage directly with an annual repeat-purchase measure.
What is the difference between customer retention and revenue retention?
Customer retention counts people or accounts retained from a starting cohort. Revenue retention tracks the value kept from that cohort. Net revenue retention includes expansion, contraction, and churn; gross revenue retention excludes expansion. A business can lose customers while maintaining or growing existing-customer revenue if the remaining customers spend more.
How often should customer retention rate be measured?
Review retention on a cadence that matches the purchase cycle, such as monthly operational reporting with quarterly or annual cohort comparisons. Seasonal and durable-goods businesses may need longer windows. Rivo Analytics Home supports time filtering for program reporting, but the reporting interval should not be confused with the cohort’s retention window.
