Purchase Frequency
Purchase frequency is the average number of purchases a customer makes in a given period, calculated as total orders divided by unique customers over that period. Use a 12-month window unless your product has a shorter natural buying cycle. It is one of the three levers on revenue alongside average order value and customer count, and a direct input to customer lifetime value.
Also known as: order frequency, transaction frequency, buying frequency, average purchase frequency
Formula
Total Orders / Unique Customers
Why purchase frequency matters
Purchase frequency is one of the three primary levers for revenue growth - alongside average order value and total customer count. Increasing any one of these grows revenue, but purchase frequency is unique because it compounds: a customer who buys twice a year at $50 generates $100 annually, but if you increase their frequency to four times a year, revenue doubles to $200 without changing their spending per visit.
This metric also reveals the natural buying cycle for your product category and customer segments. Understanding that your average customer purchases every 45 days allows you to time your marketing communications, restock reminders, and promotional campaigns to coincide with natural repurchase windows.
Purchase frequency trends tell you whether your customer relationships are deepening or fading. Increasing frequency over time suggests growing customer engagement and loyalty. Decreasing frequency often precedes churn and signals that customers are finding alternatives or losing interest.
The newsletter
Join our KISS newsletter
One short read a week on what actually moves revenue, in a free email. Read by 10,000+ operators and founders.
No spam. Unsubscribe in one click.
How to calculate purchase frequency
Divide the total number of orders by the total number of unique customers over the same time period. Use a consistent period, typically 12 months, so seasonal peaks do not distort the result.
Worked example: 12,000 orders from 5,000 unique customers over a year gives a purchase frequency of 2.4 orders per customer per year, or one order roughly every 152 days. Feed that straight into LTV: at a $60 average order value and a 3-year average customer lifespan, LTV is 2.4 x $60 x 3 = $432.
For a sharper read, also calculate the median time between consecutive purchases for repeat customers. The mean is pulled around by one-time buyers and by a small number of very frequent ones; the median tells you when to actually send the reorder prompt.
Purchase Frequency Calculator
Total Orders / Unique Customers
Purchase Frequency examples
A pet supply store implements automatic reorder reminders based on estimated product consumption rates, increasing average purchase frequency from 4.2 to 5.8 times per year.
Benchmark: Consumables: 6-12 purchases/year; fashion: 3-6 purchases/year; electronics: 1-2 purchases/year
A SaaS credits marketplace where customers buy credits in bulk tracks purchase frequency and finds that customers who set up auto-reload purchase 8x per year vs. 3x for manual buyers.
How to Track in KISSmetrics
KISSmetrics tracks purchase frequency through its person-level People data. Each customer profile accumulates a full purchase history, so average and median frequency fall out of it directly. Use the Cohort report to compare frequency across acquisition groups, the Revenue report to tie frequency changes back to revenue, and Populations to hold segments such as "bought twice in 90 days" so campaigns can target them. If the metric does not exist in your account yet, describe it in the AI chat and it will build it, and the events behind it come from autocapture plus the setup pass that scans your site.
Common Mistakes
- -Using a time window that is too short relative to the natural purchase cycle, which makes frequency appear artificially low
- -Not accounting for customer tenure - including brand-new customers in the average drags down the frequency number
- -Confusing purchase frequency with visits - a customer may visit many times without purchasing
- -Ignoring seasonal patterns that make frequency appear to fluctuate when the underlying behavior is stable
Pro Tips
- +Calculate the average time between first and second purchase to optimize your post-purchase re-engagement timing
- +Segment purchase frequency by customer acquisition source to find which channels bring the most engaged buyers
- +Use predictive analytics to identify when each customer is likely to purchase next, and send timely reminders or offers
- +Create replenishment reminders for consumable products based on estimated usage rates, not arbitrary schedules
- +Reward frequency increases with loyalty program benefits that reinforce the behavior
Related Terms
Repeat Purchase Rate
Repeat purchase rate is the percentage of customers who make more than one purchase within a defined time period. It measures customer loyalty and the effectiveness of your retention and re-engagement strategies.
Customer Lifetime Value
Customer Lifetime Value (CLV or LTV) is the total revenue a business can expect from a single customer over the entire duration of their relationship. It is the most important metric for understanding long-term customer profitability.
Average Order Value
Average Order Value (AOV) is the average dollar amount spent each time a customer places an order. It is calculated by dividing total revenue by the number of orders in a given period.
Customer Retention Rate
Customer retention rate is the percentage of existing customers who remain active and continue purchasing over a specific time period. It measures a business's ability to keep customers coming back.
Average Revenue Per User
Average Revenue Per User (ARPU) is the mean revenue generated per active user over a specific time period. It measures the monetary value each user contributes to your business.
Further Reading
Customer Lifetime Value for E-commerce: How to Calculate and Increase LTV
Learn how to calculate customer lifetime value for e-commerce businesses. Covers LTV formulas, segmentation by customer cohort, and strategies to increase it.
E-commerce Cohort Analysis: Track Customer Behavior Over Time
Learn how to use cohort analysis for e-commerce to understand repeat purchase rates, customer retention by acquisition channel, and seasonal buying patterns.
Build your business intelligence layer for free.
Every order resolved to the person who placed it, so repeat rate, order value and what a channel is actually worth come out of the same events rather than three tools that disagree.