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 

Understanding the latency period in your customer purchasing cycle can help you determine the best time to send emails to reconnect with your customers. These messages should include relevant recommendations and (where necessary) incentives offered at the optimal time. Instead of bombarding customers with “Buy more now!” messaging three days after they make a first purchase, latency data helps you create more strategic campaigns that are timed to drive purchasing behavior sooner and more often. For example, WhatCount’s Win Back Automators are informed by Latency data help to bring back the customers that are the highest churn risk based on their Latency score.

Common questions about Latency 

Question: How can I view specific group’s 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:

  1. 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. 
  2. 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!
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