Maximizing New Mover Revenue

A Major Retailer Increased Revenue by $24 Million and Foot Traffic by 45% Partnering with Speedeon Data


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The Opportunity

Approximately 1.1 million households relocate annually within the trade areas of a leading soft goods retailer. These high-spending new movers provide an excellent opportunity for the retail chain to acquire new customers, minimize existing customer churn, 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 managed an on-going direct mail program that targeted new movers relocating into respective 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 retailer wanted a way to optimize response rates and other program metrics in order to achieve revenue goals.


The Solution

The retailer worked with Speedeon Data to develop a predictive response model, to maximize the return-on-investment on the mover program. The model ranked movers based on their likelihood to respond. The retailer 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 retailer used the predictive model to continually optimize program performance, which on an annualized basis generated:

  • 165,500 additional new mover responders
  • $24.3 million in incremental revenue