Procedures to improve the house list segment tests

An important aspect of direct marketing research focuses on developing and segmenting a house list (customer database) using various geographic, socioeconomic, and recency, frequency and monetary (RFM) measures. For a typical promotion, direct marketers may take a simple random sample from the house list as a test mailing to forecast the segment rollout response rates. Decisions about the final rollout are made in such a way that only the segments with response rates over the prespecified threshold or break-even response rate will be used. In this article, it is shown that the commonly used simple random sampling procedure may seriously underestimate the variability of the rollout response rates of segments with higher test response rates, overforecast the potential number of buyers from the rollout, and inflate forecast accuracy. Several procedures are proposed to improve the house list tests, and examples are used to compare the new procedures with the existing one. Results show that the proposed house list test procedures provide more statistically efficient, cost-effective, and reliable forecasts for segment response rates while improving the accuracy of forecasts generated.