Modeled New Mover Agency

Agency Increases Client’s Revenue by $24 Million and Store Traffic by 45% Using Modeled New Movers

 

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The Opportunity

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 Problem

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 Solution

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.

 

The Results

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