CRM Growth
£13 million
of increased revenue and 50% of lapsed customers active 6 months later
The Ask
The DIY Retailer came to us with a problem, they didn't believe they were first choice for purchases by traders, and wanted to understand how to retain more trade customers.
Our Solution
Through thorough analysis of their data, we found that their definitions of a "lapsed" customer were too broad: the same thresholds were being applied to everybody.
We used machine learning to build a personalised lifecycle status analysis. Our tool looked at the history for each trade customer, and customers like them, to make individual predictions for when a customer was at risk of lapsing, or had already lapsed.
Impact
By using a triggered win-back incentive delivered by email to every customer at risk of lapsing, at the right moment for them, we delivered our client an incremental £13m of revenue, and 50% of lapsed customers were still active 6 months later.