What is a good repeat purchase rate for ecommerce?

The industry average is 27 to 28 percent for Shopify stores, though Bluecore's study of 100+ retailers puts it at 16.5 percent. What matters more is your category benchmark. Grocery and subscription brands hit 40 to 65 percent. Furniture and luxury brands sit at 10 to 15 percent by design. Compare against your category, not the overall average.

How do you calculate the repeat purchase rate?

Divide the number of customers who made more than one purchase in your chosen time period by the total number of customers in that period, then multiply by 100. Use a 12-month window as the standard. The most important rule is consistency — keep the same window so you can track improvement over time without the metric shifting underneath you.

What is the difference between the repeat purchase rate and the customer retention rate?

Retention rate measures whether a customer stayed active — opened emails, visited the site, engaged with your brand. Repeat purchase rate measures specifically whether they bought again. A customer can have high retention and low RPR, which means they are engaged but not converting. RPR is the direct revenue signal. If you can only track one, track RPR.

Why is my repeat purchase rate low?

The most common causes are wrong re-engagement timing (sending a win-back 7 days after purchase for a product with a 30-day replenishment cycle), no personalized second-purchase recommendation, and fragmented customer data that makes it impossible to identify at-risk customers before they churn. Start by calculating the average days between the first and second purchase for your best customers. That number is your re-engagement trigger window.

What is RFM scoring, and how does it help the repeat purchase rate?

RFM stands for Recency, Frequency, and Monetary value. It scores each customer based on how recently they purchased, how often they buy, and how much they spend in total. The most actionable segment is customers with high recency and low frequency — still warm but without an established habit. Using RFM to prioritize re-engagement is more effective than blanket win-back campaigns sent to your entire lapsed list.

Does a loyalty program improve the repeat purchase rate?

Yes, but only in the right categories. Loyalty programs work for high-frequency buying patterns — supplements, pet food, coffee — where customers buy regularly and need a reason to choose you over a competitor. For low-frequency categories like furniture or electronics, points programs see low redemption because customers do not think about your brand often enough for gamification to change behavior. In those categories, timing-based re-engagement and personalized recommendations outperform points programs.

Repeat Purchase Rate 101: How to Measure and Increase It

If your repeat purchase rate feels like a "black box," it's probably because your data is currently screaming from three different rooms.

You've got sales in Shopify, opens in Klaviyo, and a whole lot of "who knows?" everywhere else. You can't fix a leaky bucket if you can't see the holes.

To move the needle, you need a specialized data analyst agent to unify those silos and tell you exactly when your customers are ready to come back for seconds.

This 101 guide clears the fog around the repeat purchase rate, giving you the levers to drive LTV up and CAC down — and shows you how to build the retention journeys that turn "one-and-done" shoppers into your most loyal revenue drivers.

What is the repeat purchase rate?

Repeat Purchase Rate formula and retention dashboard

Repeat purchase rate is the percentage of customers who make more than one purchase from your store within a defined time period.

You calculate it by dividing the number of customers with two or more purchases by your total number of customers, then multiplying by 100.

Repeat Purchase Rate = (Customers with 2+ purchases / Total customers) × 100

If 300 of your 1,000 customers made a second purchase in the last 12 months, your repeat purchase rate is 30%.

The time window matters. Most brands use a 12-month rolling window. Pick one and keep it consistent.
The naming is confusing. Repeat purchase rate, repeat customer rate, and repurchase rate are the same metric.
RPR is not the same as retention rate. Retention measures whether a customer stayed active. RPR measures whether they bought again. RPR is the revenue signal; retention is the engagement signal.

What does a low repeat purchase rate actually cost you?

Acquisition vs Retention Cost — increasing retention by 5% can boost profits 25–95%

Acquiring a new customer costs 5 to 25 times more than retaining one (Harvard Business Review / Bain and Company). Every customer who buys once and never returns is a paid acquisition that generated one order.
A first-time buyer has a 27% chance of buying again. A customer who makes a second purchase has a 54% probability of making a third. The second purchase is the inflection point.
The top 5% of customers generate 35% of revenue (Smile.io). Repeat customers spend 67% more per order than first-time buyers.
A 5% increase in retention can boost profits 25 to 95% (Bain and Company).

The math: with a $90 average order value, a 5% RPR lift across 1,000 customers recovers $4,500. That is from one cohort, before compounding from repeat purchases.

Repeat purchase rate is not a vanity metric. It is the most direct measure of whether your post-purchase experience is working.

How does the repeat purchase rate work?

Every customer who makes a first purchase enters a window. Your product's replenishment cycle sets the length of that window.

A coffee brand's window is roughly 21 days
A supplement brand's window is 28 to 30 days
A furniture brand's window might be 18 months

The customer is most receptive in the last third of that window. The product is running low, but they have not started looking elsewhere. Reach them in that window and the probability of a second purchase is high. Miss it, and the probability drops.

Here is the full loop:

The customer makes their first purchase
Post-purchase flow begins — or does not, which is the most common failure
The replenishment window opens
The brand shows up at the right moment, or the customer moves on
The outcome of this window, repeated across your customer base, is your RPR

The most common failure is step four. Most brands trigger re-engagement on a fixed schedule — "email seven days after purchase" — for every product, no matter the replenishment cycle. The timing is based on the calendar, not on customer behavior.

How to calculate and increase RPR?

Measuring and increasing repeat purchase rate is easier than you think. Follow these steps to calculate, segment, and trigger an email flow using a signal-based approach.

Step 1: Import your data

Step 1: Connect data sources in Intempt Integrations

Your customer data is scattered across Shopify, Klaviyo, and a handful of other tools. None of them agrees on who a customer is.

Connect every source to Intempt first — this creates a single unified profile per customer with real-time event streaming before you touch anything else.

Connect Shopify, Klaviyo, and any other source via Intempt integrations
Verify that product-ordered events are populating on the unified customer profiles
Check that UTM parameters are passing through from Shopify so acquisition channel data is not showing as undefined

Step 2: Calculate your baseline RPR

Step 2: Calculate baseline RPR using Intempt Analytics with Formula mode

Before you can improve the number, you need to know what it actually is — broken down in a way that tells you where the problem lives.

Go to Analytics → Create report → Insights tab → set date range to 12 months.

Set Series A to Product ordered + Unique users — this is your total buyer count
Add Series B: same event, same metric, then add a filter for Orders count > 1 — this is your repeat buyer count
Enable Formula mode and enter B/A*100 → Apply
The result is your current RPR percentage
Benchmark it against your category, not the 27% industry average

Step 3: Find your trigger window

Step 3: Find repurchase trigger window using Intempt Retention report

This is the most important number in your repurchase strategy. It tells you exactly when to reach out — not based on a calendar, but on what your best customers actually do.

Switch to the Retention tab in the same report.

Set Event 1 and Event 2 both to Product ordered
Set the time range to 6 months, retention window to each week
Find the week column with the highest return percentage
Multiply that week number by 7 — this is your delay timer for the journey
Note this number before moving on

Step 4: Build your RFM segments

Step 4: RFM agent segments — Regulars, Promising, Needs Attention, At Risk

A single post-purchase sequence sent to everyone is a calendar-based drip. RFM segments let you target the right customers with different messaging based on where they are in their lifecycle — and they update in real time as new purchase events fire.

Go to Agents → Lifecycle → RFM agent, confirm the model timeframe is set to 180 days. Then go to Users → Segments → Create segment and build three dynamic segments using the RFM Recency Score attribute:

RPR - Promising — Recency Score = medium to high (bought recently, not yet a repeat buyer)
RPR - Needs Attention — Recency Score = low to medium (starting to drift)
RPR - At Risk — Recency Score = low (very inactive, needs a stronger offer)

Each segment auto-updates as purchase events fire — no manual refresh needed.

Step 5: Create your post-purchase messages

Step 5: Build post-purchase emails in Intempt email editor

Build these five emails before you create the journey. Each one maps to a specific signal and a specific segment. Go to Journeys → Messages → Create message → Email.

Review request — send Day 3–5 post-delivery, goes to everyone
Product tips — send Day 5–7, only if no site visit since purchase
Reorder reminder — send at your trigger window day, consumables only
Personalized recommendations — triggered if the product page is browsed but no purchase is made
Exclusive offer — reserved for Needs Attention and At Risk segments only

Step 6: Build the journey

Step 6: Build the Repeat Purchase Engagement Journey in Intempt

Build one journey with multiple branches. Use True/False branches inside a single journey to route each RFM segment to the right message sequence.

Go to Journeys → Create journey and configure:

Trigger: Product ordered event
Entry condition: include users that matched and will match (catches existing and new buyers)
Re-entry: allow re-entry after each new purchase — without this, a customer who buys a second time never re-enters for their third
Goal event: Product ordered — tracks which branch actually drove the conversion
Branch logic: Send Review request to everyone on Day 3–5 → True/False: RPR - Promising? → Product tips → Personalized recommendations. True/False: Needs Attention? → Reorder reminder → Exclusive offer. Remaining (At Risk): Exclusive offer immediately → SMS win-back after 3 days
Exit logic: fires on Product ordered so buyers exit as soon as they repurchase

Step 7: Analyze

After 30 to 60 days, check these three reports to know what is working and what to test next:

Retention report — has the return rate in the trigger window weeks improved versus your baseline?
Journey goal conversion — which branch drove the most Product ordered events?
RFM distribution — are Promising customers shifting into Regulars over time?
Run quarterly A/B tests inside the journey on send timing, subject line, and offer versus no offer

What is a good repeat purchase rate?

The overall eCommerce average sits at 27 to 28% for Shopify stores. Bluecore's study of over 100 retailers puts it closer to 16.5%. The way you define "customer" and the time window you use drive this gap. The more useful benchmark is your category:

Category	Typical RPR	Primary driver
Grocery / Food delivery	40–65%+	Weekly replenishment, habitual buying
Pet supplies	30–40%+	High subscription rates, routine care
Health and supplements	~29%	Monthly replenishment cycle
Fashion and apparel	20–26%	Seasonal buying, trend-driven
Beauty and cosmetics	21–26%	Medium replenishment cycle
Sporting goods	~21%	Lower purchase frequency
Electronics and tech	~18%	Long replacement cycle
Home and furniture	~15%	Very long purchase cycle
Luxury and jewelry	~10%	Low frequency by design

If you sell supplements and your RPR is 22%, that is underperformance. If you sell sofas and your RPR is 22%, that may be strong. Benchmarking against the overall average without category context produces the wrong diagnosis every time.

What are the types of repeat purchasers?

Not all repeat buyers behave the same way. Knowing which type you are dealing with determines which intervention works.

Type	Examples	Your Job
Habitual Repurchasers	Supplements, pet food, coffee	Protect the habit. Make reordering frictionless and offer subscriptions.
Occasion-driven Repurchasers	Fashion, holiday gifts, sporting gear	Own the calendar. Show up with relevant offers before the need actually arises.
One-and-done Risk	Any category (bought once, then went quiet)	Catch them early. Re-engage before the window closes — many brands miss this due to fragmented data.

Real-life examples

Chewy: building 90% repeat revenue through subscription timing

Chewy Autoship program — 20% off first order, 78% of sales from auto-ship

Chewy recognized that pet food is a habitual repurchase category with a predictable cycle. Instead of sending re-engagement emails after customers stopped buying, they removed the repurchase decision entirely.

Their Autoship program lets customers set their replenishment frequency at checkout. 78% of Chewy's sales now come through auto-ship, and approximately 90% of their revenue comes from existing customers.

The mechanism was not loyalty points or discounts. It was eliminating the gap between replenishment need and reorder. The product cycle became the trigger — Chewy did not wait for customers to come back; they built a system where the customer never had to decide to return.

Sephora: using purchase data to drive personalized repeat purchasing

Sephora's Beauty Insider program has over 40 million members and accounts for 80% of North American sales.

The program is not just a points system. It is a data infrastructure. Every purchase feeds a profile that powers personalized recommendations, tier-based offers, and targeted re-engagement.

The result: a 22% increase in cross-sell revenue and up to 51% improvement in upsell revenue. Customers get recommendations based on what customers with identical first purchases went on to buy next — a cohort-level product recommendation that directly drives the second purchase. Sephora's Beauty Insider accounts for 80% of North American sales.

Dollar Shave Club: highest retention in men's grooming

Dollar Shave Club — highest customer retention in men's grooming subscription category

Dollar Shave Club built its entire model around the shaving replenishment cycle and held the highest customer retention rate in the men's grooming subscription category.

Around 50% of their customers acquired in 2014–15 were still active subscribers at month 12. In an industry with notoriously high churn, that is a significant number.

The driver was not the price. It was flexibility. Customers could pause, swap products, or adjust frequency at any time. Reducing friction to modify (not cancel) kept customers in the subscription longer. Rigidity drives churn. Flexibility drives retention.

Key terms to know

Repeat purchase rate (RPR) — the percentage of customers who buy more than once from your store in a defined time period. Standard window is 12 months.
Customer retention rate — the percentage of customers who remain active (engaged with emails, visited the site) over a period. RPR is the revenue signal; retention is the engagement signal.
Purchase frequency — the average number of orders per customer in a time period. Measures how often a customer buys, not whether they came back at all.
Replenishment cycle — the average time between a customer using up a product and needing to reorder. The most important input for timing re-engagement campaigns.
RFM scoring — a segmentation method that ranks customers on Recency (last purchase date), Frequency (number of purchases), and Monetary value (total spend). Customers with high recency and low frequency are the highest-priority segment for repurchase campaigns.
Post-purchase sequence — an automated series of messages triggered after a first purchase, designed to build trust and create the conditions for a second purchase before the replenishment window closes.
Cohort analysis — grouping customers by a shared attribute and tracking behavior over time. Reveals which segments have the highest and lowest RPR.
Customer lifetime value (CLV) — the total revenue a customer is expected to generate across all future purchases. Every improvement in RPR compounds directly into CLV.
Win-back campaign — a re-engagement campaign targeting customers who have already stopped purchasing. Higher cost and lower conversion than early intervention. Use as a last resort, not a primary strategy.

The bottom line

Repeat purchase rate is the most direct measure of whether your post-purchase experience is working.

A low number does not mean your product is bad. It almost always means the timing is off, the data is fragmented, or you are applying the wrong fix to the wrong segment.

Start this week by calculating RPR by acquisition channel. That one breakdown will tell you more than your overall number ever could. Then find your trigger window and move your re-engagement timing to match it.

Want to see exactly where your repurchase lifecycle is leaking? Run a free Growth Audit with Intempt — we map every lifecycle drop-off point and show you precisely where the revenue is going.