Modeled New Mover Agency
Agency Increases Client’s Revenue by $24 Million and Store Traffic by 45% Using Modeled New Movers
Approximately 1.1 million households relocate annually within the trade areas of a national soft goods retailer. These high-spending movers provide an excellent opportunity for the retailer to acquire new customers, generate foot traffic, and increase its market share of this lucrative audience (who, on average, spend $8,500 with three months of relocating).
The retailer’s agency managed an ongoing direct mail program that targeted new movers relocating into the stores’ trade areas with a 20% discount offer. However, monthly fluctuations in marketing budgets impacted the retailer’s ability to achieve revenue goals on a consistent basis. The client wanted a way to optimize response rates and other program metrics in order to achieve revenue goals.
The agency worked with Speedeon Data to develop a predictive response model to maximize the return-on-investment for the client’s mover program. The model ranked movers based on their likelihood to respond. The agency mailed a “Percent Off” postcard to the first 50% of the mail file, which contained nearly 61% of the “most responsive” new movers.
Nearly 12% of new movers responded to the discount offer. Compared to a control group:
- Response rate increased by 45%.
- Cart size increased by 8%.
- Revenue per mail piece increased 56%.
The agency used the predictive model to continually optimize the client’s program performance, which, on an annualized basis, generated:
- 165,500 additional new mover responders
- $24.3 million in incremental revenue