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To build repeat business, make the first purchase worth repeating: offer a product that meets the customer’s needs, deliver it reliably, resolve problems well, and make the next useful step easy. Measure repeat behavior over a time window that fits your products. A loyalty program can reinforce a sound customer experience, but it cannot make an uncompetitive offer or poor service sustainable.
Retention and loyalty are related, but they are not the same
Customer retention describes observable behavior: customers continue buying from a business over a defined period. Customer loyalty is a stronger preference or relationship that may lead to repeat purchases, engagement, or recommendations. A second order demonstrates repeat behavior; it does not, by itself, prove emotional attachment.
The distinction matters because each idea calls for different evidence. Use purchase records to measure repeat buying and retention. Treat advocacy or preference as separate questions, supported by measures such as referrals or customer feedback rather than inferred from an order alone. Shopify’s 2026 guide discusses the distinction and practical retention measures: Shopify’s customer retention guide.
Choose the behavior to improve, then measure it consistently
Before choosing a tactic, decide what problem you are trying to solve: Are customers failing to make a second purchase? Are they ordering less often than the product’s normal use cycle suggests? Or are existing customers becoming inactive? Select a defined customer group and time window, then compare like with like. If available, segment by product category or the customer’s first-purchase group.
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| Measure | Calculation | What it tells you |
|---|---|---|
| Customer retention rate | (Customers at the end of the period − new customers acquired during it) ÷ customers at the start × 100 | What share of the starting customer base remains after accounting for new customers. State the period and population. |
| Repeat customer rate | Customers who purchased more than once during the period ÷ unique customers during the same period × 100 | How common multiple purchases were in the selected timeframe. It is not the same as retention rate. |
| Purchase frequency | Orders ÷ unique customers during the same timeframe | Average orders per customer for the period. |
| Average order value | Total revenue ÷ orders placed | Average revenue per order, not a direct measure of loyalty. |
| Churn rate | Customers lost during the period ÷ customers at the start × 100 | The share of the starting customer base that was lost under your chosen definition of “lost.” |
| Customer lifetime value | Shopify’s indicative simplified formula: average order value × repeat transactions × average retention time | An estimate whose result depends on the time horizon and assumptions. Define both before using it to guide decisions. |
These formulas are described in Shopify’s 2026 retention guide. Definitions of an acquired, retained, repeat, or lost customer should remain consistent across the comparison; otherwise, a change in calculation can look like a change in performance.
Use a buying-cycle window, not a borrowed universal target
There is no single “good” ecommerce retention rate that applies to every store. Customers may reasonably replenish a consumable within weeks or months, while a durable product may not need replacing for years. A short window can undercount repeat purchases for durable goods; an excessively long one can obscure a recent change. Shopify’s enterprise retention guide cautions against treating a broad benchmark as universal: Shopify’s enterprise guide to customer retention.
Choose a period that gives customers a reasonable opportunity to buy again for the product category. When comparing cohorts, use the same observation window and explain it. A store’s trend across comparable cohorts is generally more useful than a detached industry average.
Improve the experience before adding incentives
Repeat purchases depend on the whole journey, not only a rewards mechanism. Review where a customer might decide the product is unsuitable, the site is difficult to use, an order is unreliable, or asking for help is too much work.
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- Product fit and discovery: Make product details, sizing or compatibility information, and differences between options clear enough for customers to choose appropriately.
- Website usability: Check the path from product discovery through checkout, including whether key information and support options are easy to find.
- Fulfillment: Set clear delivery expectations and make order status understandable. Investigate late, damaged, or missing orders and the reasons behind them.
- Customer service: Make it straightforward to get a useful response and resolution. Review recurring contacts and unresolved issues, not just response speed.
- Returns: Explain eligibility and the process before purchase, then make the stated process workable in practice.
- Product education: Give customers practical guidance on setup, care, or use when it could help them get value from what they bought.
A 1999 Bain & Company and Mainspring survey of 2,116 online shoppers identified order fulfillment, price, customer service, and website functionality among factors associated with returning to a site. Its age makes it historical evidence about durable categories of customer need, not a current benchmark. In the same survey, apparel repeat customers spent 67% more in months 31–36 than in months 0–6, and grocery customers spent 23% more across those respective periods. Those are category-specific historical findings, not estimates of what a modern store should expect. The report also recorded an average of 3.1 referrals per apparel customer after the first purchase and 7.1 after ten or more purchases; these observations likewise should not be generalized to current markets: Bain & Company and Mainspring’s online retailing report.
Make follow-up useful and well timed
Post-purchase communication can help customers use what they bought and make a relevant next purchase. Its timing and purpose should follow the product and customer need rather than a generic schedule.
- Send setup, care, or usage guidance when it helps a customer get value from the order.
- For replenishable products, time a reminder around a plausible replenishment interval rather than sending it immediately after delivery.
- For complementary products, explain why an item may be useful alongside the original purchase; avoid treating every purchase as permission for an irrelevant upsell.
- Ask for feedback when the store can use it to address friction or improve product information.
Personalization is most useful when it makes a message more relevant—for example, by reflecting the product bought or a meaningful customer preference. Keep the outcome measurable. If testing a replenishment reminder, assess repeat purchases within a sensible replenishment window; if improving service, assess return behavior for the affected customer group. These are ways to apply the measurement concepts above, not guarantees that a particular tactic will work for every store.
Use a loyalty program only when its economics and rules fit
Rewards can give customers a reason to return, but enrollment is not the same as incremental purchasing or profitable loyalty. Decide which behavior the program should encourage—such as a second order, a higher annual spend, or a referral—and estimate the cost of the reward against the contribution the behavior can generate.
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Choose mechanics that match the goal
- Points: Customers earn points and redeem them for benefits such as store credit, vouchers, or free shipping. This can make the next purchase more tangible, but the reward and redemption threshold need to fit purchase cadence and margin.
- Tiers: Different levels can recognize annual spend or other defined behavior. Set thresholds and benefits so they reward customers the business wants to retain without making the economics depend on unprofitable discounting.
- Experiential benefits: Access, recognition, or other non-discount benefits can offer value without relying entirely on price reductions. They still require operating effort and should matter to the customers they are meant to engage.
- Referrals: An incentive may encourage recommendations, but calculate the cost of both sides’ rewards and compare it with the value of acquired customers.
Shopify’s enterprise guide describes these reward approaches and names Smile, Yotpo, and LoyaltyLion as software examples. The guide does not establish an independent ranking of their features or current terms. When a platform is relevant, compare its fit with your ecommerce platform and customer records, online and in-person reward needs, earning and redemption rules, reporting, implementation effort, and total cost. Those costs can include platform fees, discounts, shipping, and the liability created by unredeemed rewards.
What the available survey figures do—and do not—show
Harvard Business Review reported in 2021 that the United States had more than 3.3 billion loyalty-program memberships. Memberships do not establish active participation, incremental purchasing, or profit for an individual merchant: Harvard Business Review’s 2021 discussion of loyalty programs.
In a 2024 article, HBR reported a Bain & Company and ROI Rocket survey of nearly 870 US consumers, 63% of whom said they make buying decisions based on loyalty programs in which they participate. This is a reported survey response, not a causal estimate of the effect a particular store’s program will produce: Harvard Business Review’s 2024 article on loyalty-program effectiveness.
HBR also reported a Bain finding that a five-percentage-point increase in retention was associated with a 25% to 95% increase in profits. This is a broad finding reported secondhand, not a promised ecommerce outcome or forecast for a particular business: Harvard Business Review’s 2014 report on customer retention.
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Test changes against a baseline, not just sign-ups
A program can attract registrations without changing purchase behavior. Likewise, more repeat orders may not improve profit if incentives, fulfillment, or service costs outweigh the value they create. Establish a baseline before changing the experience or launching rewards, then judge the result against the behavior the change was meant to affect.
- Define the question: For example, whether more first-time buyers make a second purchase within a relevant period.
- Set the population and window: Identify the cohort, product category where relevant, and the period in which a repeat purchase would be plausible.
- Choose the measure: Use repeat customer rate for repeat buying, retention rate for the continuing starting customer base, or another measure suited to the question.
- Change one meaningful part of the journey: Examples include clearer product guidance, a service improvement, a better-timed replenishment message, or a carefully costed reward.
- Compare like with like: Use the same definitions and observation window as the baseline, and account for the cost of the change.
Program design is a measurement challenge as much as a marketing choice. HBR’s coverage discusses ways loyalty programs can encourage purchasing, visits, engagement, and recommendations, while also warning that programs can backfire when customer engagement or economics are weak. Neither participation statistics nor broad profit findings prove that a given program will pay off for your store.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to choose a loyalty platform
If the case for a program is sound, choose software around the operating model rather than a feature checklist alone. Shopify’s enterprise guide names Smile, Yotpo, and LoyaltyLion as examples, but it does not provide a current independent comparison of product features, pricing, integrations, or performance. Compare platforms on the requirements that affect your store:
- Store and customer-data fit: Confirm that the platform works with the store platform and customer records you use, and determine whether the records needed to recognize a customer are unified.
- Channel coverage: Check whether rewards need to work across online and physical sales, and whether the product supports that use case.
- Reward flexibility: Compare point earning, redemption, tiers, referrals, and experiential benefits against the behavior you want to encourage.
- Useful reporting: Look for reporting that can distinguish enrollment from subsequent repeat behavior and the cost of rewards.
- Operational burden: Account for setup, ongoing program administration, customer questions, and fulfillment of benefits.
- Total economics: Include software fees, reward costs, discounts, free shipping, and outstanding reward obligations in the calculation.
Software can administer a program; it cannot establish that the program caused incremental, profitable behavior. That question depends on how the store measures outcomes against its baseline.
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Further reading
Frederick F. Reichheld’s The Loyalty Effect is a general business book on loyalty. It is supplementary reading rather than a current ecommerce implementation guide. The Bain and Mainspring report above offers historical online-retailing context.
Frequently Asked Questions
How do I get customers to come back to my online store?
Start with the reasons they might not return: product mismatch, confusing site experience, unreliable delivery, difficult returns, or unresolved service issues. After addressing those, make relevant follow-up—such as product guidance or a replenishment reminder—easy to act on, and track repeat purchases over a period that suits the product.
How do I increase repeat purchases?
First identify where repeat buying is weak and for which customers or products. Improve the relevant part of the experience, test one change, and measure the intended behavior against a consistent baseline. Add incentives only when the behavior they encourage is worth the reward cost.
What is a good customer retention rate for ecommerce?
There is no universal target that fairly compares products with different natural buying cycles. Define the customer population and time window, then compare your own cohorts over a period in which customers could reasonably buy again.
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Do loyalty programs increase repeat business?
They can encourage behavior, but the existence of a program or a large membership count does not establish incremental repeat business or profit for a particular store. Whether one helps depends on customer engagement, reward economics, and measurement against a baseline.
Is repeat purchasing proof that customers are loyal?
No. Repeat orders show repeat behavior. Loyalty is a stronger preference or relationship that may also result in advocacy, so do not infer it from purchase history alone.
Which loyalty software should a store choose?
Shopify’s enterprise guide names Smile, Yotpo, and LoyaltyLion as examples but does not establish a current independent ranking. Compare a platform’s store and data fit, channel needs, reward flexibility, reporting, operating effort, and total cost against the program you intend to run.
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