Predicting the Risk of Customer Loss
Are you a retail business with hundreds of transactions a week? Maybe you’re a university wanting to increase student retention, or you’re a credit union needing to retain account holders. Possibly you’re a pro sports team wanting to keep season ticket holders. No matter who you are, you have a common goal. You want to keep your customers. We won’t go into the “why” of that in this article. Instead, let’s focus on the “how.”
Track the Transitions
For any companies that have a database of their customers with even the slightest bit of information on those clients, you already have a great tool available. Download at least the last 4 years of data on your customers, so you can note three “transitions” of one year to the next. Look at these transitions to determine which of the customers you had in Year 1 were not customers in Year 2, and continue through the Year 3/Year 4 transition.
Paint a Picture of Lost Customers
Next, look at the data that you have on those lost customers such as how long they’ve been a customer, their purchase/participation level, their demographics, and the results of surveys you’ve done with them. Then assess the characteristics of all the customers you lost from one year to the next, and compare that to the characteristics of all those you retained. What’s different? What indicators seemed to highlight the probability that that customer was at-risk of leaving? At this point, you’ve created a profile of at-risk customers.
Apply Profiles of Yesterday to Today
The next step is to apply the analysis of yesterday’s data to today’s customers. Apply this at-risk criteria to today’s database. Which customers have several of the at-risk indicators? Those are most likely your customers most at-risk of loss this year. Target them for communications, for research, and for retention efforts.
By looking at the data of the past, you can find those most at-risk of leaving in the future.