The Latency metric measures how long your customers wait before they make another purchase. This is a critical metric in predictive marketing and a powerful way to measure the effectiveness of your marketing. Use the date and segment filters at the top of the page to see how latency is influenced by specific campaigns and/or timeframes. (You can always download this data as a .csv file using the download icon.)
Using latency data to improve your marketing
Common questions about Latency
Answer: Use the segment selector at the top of the page to filter data using segments you've built with the Segment Builder.
Question: My latency seems higher than I think it should be. Why is that?
Answer: Latency is calculated based on when someone made a previous purchase. For example, you are looking at the last year's worth of data and the second time latency seems high. The data being used for this calculation is for all customers who made their second purchase in the last year and not their first and second purchase in the last year. So, someone’s first purchase could be outside of the year time frame. This can cause your latency numbers to seem higher, but it’s the true reflection of what your data reflects.
Question: Can you give me an examples of how I can analyze/use Latency data?
Answer: Here are two examples of how you can use latency data:
- Build a segment to understand what the latency and buying habits of your best customers looks like. Compare that with the buying habits of customers overall, and look for patterns among your most loyal or highest-spending customers—possibly by season or by product. Use that information to help identify your best customers early on, and create a campaign to help new customers become best customers.
- Look for spikes in latency and work to change them. If four-time buyers are taking longer than three- or five+-time buyers, dig in and figure out why. Give extra attention to those customers; get creative trying to resolve the delay!