Time to next order
Outline
Welcome
In this module, you will learn about the Time to Next Order under Reports, how to use it and how to create custom reports.
After completing this module, you should be able to:
State the purpose of Predicted Time To Next Purchase report
Understand how the model work
Identify the use cases of reports
What is it? / Why use it?
The Predicted Time To Next Purchase report helps users identify and target specific customer cohorts based on their Order Likelihood and Days Until Next Order. This enables strategic allocation of resources to accelerate purchase timelines.
Understanding the Report's Data
The report combines two modeled attributes:
- Order Likelihood: The probability of a customer placing another order.
- Days Until Next Order: The predicted number of days until a customer's next purchase.
These attributes are derived from customer event data, revenue, order frequency, and average order value from the last 180 days, predicting data for the next 42 days. The models are custom-built for each data source, retrained monthly, and run nightly.
Read this article to get more information on how the report filters work.
Understand order likelihood and days until next order report filters
The Predicted Time To Next Purchase report is a combination of two different modeled attributes, Order Likelihood and Days Until Next Order. The models look at data from the last 180 days to predic...
Use cases
Typical uses for order likelihood include the following:
- Accelerate revenue among the Likely to buy customer cohort – Consider grouping with other always-on revenue acceleration campaigns like Browse Abandonment or Cart Abandonment and delivering a campaign to Very Likely or Likely to buy customers who are not actively shopping on the site.
- Find new customers who look like existing Ready to buy customers – Sync an audience of Extremely Likely to buy customers to Google or Facebook to find new customers who look like them but have not considered your brand yet.