Analyze time between purchases

The time between purchases report shows how often your customers make purchases. Use this insight to identify the best moment to target customers with personalized campaigns and improve your retention rate. This guide explains how to read the report data and how to create the analysis.

Prerequisites

To create this report, you'll need to be familiar with the following:

• Reports
• Segmentations
• Expressions

Overview

Why analyze time between purchases

Knowing when customers are most likely to make another purchase helps you target them with email campaigns or special offers within the right time frame. For example, if your customers typically make their third purchase between one and four months after their second one, you can target customers who have made two purchases within that time frame.

The ideal time between purchases varies across industries. A business selling seasonal equipment like skis has a different purchase cycle than an online drugstore. Compare your results to similar businesses to determine whether your retention rate meets industry standards.

Read the report data

Use the report data to identify patterns in your customers' purchasing behavior.

A typical time between purchases report shows the following insights:

• Most returning customers purchase between 30 days and four months after their previous purchase.
• Avoid sending communications to one-time buyers in the second, third, and fourth week after their purchase.
• If you don't reactivate active customers within a year of their purchase, you risk losing them.

Create a time between purchases report

Create the expression

Create an expression for the time between a customer's purchase and their previous purchase:

1. Go to Data & Assets > Data manager > Definitions > New definition > Expression.
2. Select Expression for event and select purchase.
3. Create a running aggregate last(purchase.timestamp) and subtract it from timestamp.
4. Divide the result by 86400 to convert the output to a day count.
5. Name the expression and save it.

Create the event segmentation

Create an event segmentation using the expression you created:

1. Start from the smallest time difference and increase incrementally.

2. Set the time limits according to your preferences. Use the following segments as a starting point:

   • Last 7 days (first segment)

   

• More than a year ago (last segment)

Create the final report

1. Create a new report and use the event segmentation you created in the rows.
2. For the columns, create a running aggregate showing the number of purchases.
3. Use a simple count of purchases in the metrics.

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Note

If your purchase event has a different name than purchase, you'll need to adjust the event name in the report, event segmentation, and expression.

Best practices

Break down data by attributes other than the number of previous purchases. Consider segmenting by gender, age, order value, shipping city, or total customer value to generate more granular insights.