Time Between Purchases

CRM & Retention

Also: Purchase Frequency Cycle · Interpurchase Time · Repurchase Interval

Time Between Purchases = Average gap in days between one order and the next, per customer

What it measuresGap between orders

FormulaTotal days between orders / number of repeat orders

Watch forAverages hide two very different customers

Feeds intoLifetime value and churn timing

Quick definition

Time between purchases is the average number of days a customer takes between one order and the next. It's used to understand purchase frequency, predict when a customer is likely to buy again, and set the timing for retention campaigns like win-back emails.

Run the numbers

Total days between all repeat orders

days

Number of repeat orders

Average time between purchases45.00 days

Segment this by first-time versus loyal customers before you trust it. The two groups almost always have very different intervals.

How it varies across Australia

Time between purchases varies enormously by category. Fast-moving consumer categories like coffee or supplements sit at a much shorter interval than considered categories like furniture or mattresses. The number only becomes useful once it's segmented by customer type, not averaged across the whole base.

Explore retention benchmarks across Australian industries →

What it actually means

Time between purchases answers a simple question with a complicated average buried inside it. On any given day, some customers are due to buy again and some aren't due for months. The average collapses all of that into one number, which is useful for planning but dangerous for diagnosis.

This metric matters because it sets the clock for retention. If you know a customer typically reorders every 45 days, day 50 with no order is a signal worth acting on. Day 20 with no order means nothing. Without this baseline, churn detection and win-back campaigns are guesswork dressed up as strategy.

It also feeds directly into lifetime value. Purchase frequency multiplied by average order value, multiplied by customer lifespan, is the backbone of most lifetime value models. Get the frequency wrong and everything downstream is wrong too. Retention rate and time between purchases are two sides of the same coin, one measures whether customers come back, the other measures how long they take to do it.

The trap is treating one company-wide average as gospel. A single number smooths over the customers who buy weekly and the ones who buy annually, and the business decisions built on that smoothed number end up serving neither group well.

The average time between purchases is a fiction two different customers agreed to share.

How to calculate it

Time Between Purchases = Total days between consecutive orders ÷ Number of repeat orders

Worked example. A customer places orders on 1 January, 15 February and 30 March. That's 45 days between the first two orders and 43 days between the second two. Average gap = (45 + 43) ÷ 2 = 44 days. Run this across your repeat customer base and average the individual gaps to get your overall figure.

The Australian context

Australian ecommerce sees a seasonal skew that distorts this metric more than most markets. The gap between an order placed before Christmas and the next one in late January often looks like a slowdown when it's actually just the summer holiday period. Businesses that calculate time between purchases on a rolling twelve-month basis avoid mistaking seasonality for churn.

Where people get this wrong

Using one average across the entire customer base.New customers, loyal customers and lapsed-then-returned customers all have different intervals. Blending them produces a number nobody's campaign can actually use.

Setting win-back triggers based on gut feel instead of this number.Retention campaigns fire too early or too late when they're not anchored to the customer's actual reorder rhythm, wasting the send and annoying customers who weren't due yet.

Ignoring first purchase to second purchase as a distinct metric.The gap from first to second order is usually the riskiest window in the whole relationship and behaves differently to the gap between later repeat orders. Averaging it in with mature repeat behaviour hides where you're actually losing people.

Common questions

How do I calculate time between purchases for my business?

Take every customer with two or more orders, calculate the days between each pair of consecutive orders, then average those gaps. Doing this per cohort or per product category gives you a far more useful number than one figure for the whole customer base.

What's a good time between purchases?

There's no universal good number. It depends entirely on the category. A consumable product might have a healthy gap measured in weeks, while a considered purchase like furniture might have a healthy gap measured in years. Compare against your own historical baseline, not a generic benchmark.

How does this relate to lifetime value?

Purchase frequency, which time between purchases measures the inverse of, is one of the three core inputs into most lifetime value calculations alongside average order value and customer lifespan. A shorter time between purchases generally means a higher purchase frequency and a higher lifetime value, all else being equal.

When should I trigger a win-back email based on this metric?

Set the trigger slightly before the customer's typical reorder gap ends, not after. If a customer usually buys every 30 days, a win-back message at day 25 to 28 reaches them while they're still likely receptive, rather than after they've already found an alternative.

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About New Rebellion

New Rebellion is a marketing intelligence consultancy. We build tools, score Australian businesses on how their marketing actually performs, and publish Debrief every day. This dictionary is part of how we work in the open.

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