Challenge
Harlequin is a leading publisher with a diverse portfolio spanning romance, mystery, inspirational, and general fiction titles. As a sophisticated direct marketer, Harlequin has built and refined a wide range of subscription and direct mail programs over decades, and continuously invests in smarter, data-driven ways to identify readers most likely to engage, subscribe, and remain loyal, long-term customers.
That strategic approach extended to a resource many brands overlook: the cancel file. Within its house file of cancelled subscribers sat readers who had once paid, engaged, and stayed loyal, but for one reason or another had let their subscription lapse.
The challenge was determining which former subscribers were most likely to return and become profitable customers again. Harlequin needed a more intelligent way to identify the individuals most likely to:
- Respond to a reactivation offer
- Continue making payments
- Remain active through multiple shipment cycles
- Reach profitability within acceptable business thresholds
Solution
Alliant partnered with Harlequin to develop a Custom Optimization Model built specifically from Harlequin's own house file. Rather than applying broad list selection criteria, the model evaluated cancelled subscribers based on their likelihood to respond, continue paying, and remain active over time.
Using historical customer performance and advanced predictive analytics, the model ranked the cancelled subscriber file into performance segments, allowing Harlequin to prioritize the audiences with the greatest potential for profitable reactivation.
The model was integrated into Harlequin's direct marketing strategy, providing a more data-driven framework for audience selection and campaign execution. By concentrating marketing investments on the highest-performing segments, Harlequin was able to improve campaign efficiency while increasing the likelihood of acquiring long-term subscribers.
Results
The model quickly demonstrated its value. By mailing the top 10 model segments, Harlequin achieved:
- An average break-even of just 8 months, 3x faster than the brand's 24-month break-even threshold
- A cumulative average response rate of 3.9% across the top 10 segments
By mining deeper into a file that had traditionally been treated as low priority, Harlequin uncovered a segment of former subscribers who converted faster and performed better than the brand's own benchmarks called for. The custom model gave Harlequin a repeatable way to identify its best-fit reactivation candidates and a clear framework for scaling the approach across future mailings.
