1997Journal of Direct MarketingRequires access

Insights on ?selecting, evaluating, and updating prospects in direct mail marketing,? by Vithala Rao and Joel Steckel

Chaim Meyer Ehrman, Gerald M. Funk

Open publisher page 3 citations

Abstract

In their paper “Selecting, Evaluating, and Updating Prospects in Direct Mail Marketing,” Journal of Direct Marketing, Volume 9, Number 2, 1995, Vithala Rao and Joel Steckel introduced a probability modeling tool as an aid to certain direct market marketing decisions. In this comment we extend their model to include those cases where not everyone targeted by a direct mailing appeal actually read the mailing. We suggest that in direct marketing one should not interpret a nonresponse as lack of interest. Specifically, we add a variable to their model to describe the likelihood that a potential respondent reads third-class mail. We use this extended model to show that even when personal income is assumed to be positively related to the response variable for people on the entire mailing list, the response actually observed may be negatively associated with income.

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What this paper is about

In their paper “Selecting, Evaluating, and Updating Prospects in Direct Mail Marketing,” Journal of Direct Marketing, Volume 9, Number 2, 1995, Vithala Rao and Joel Steckel introduced a probability modeling tool as an aid to certain direct market marketing decisions. In this comment we extend their model to include those cases where not everyone targeted by a direct mailing appeal actually read the mailing. We suggest that in direct marketing one should not interpret a nonresponse as lack of interest. Specifically, we add a variable to their model to describe the likelihood that a potential respondent reads third-class mail. We use this extended model to show that even when personal income is assumed to be positively related to the response variable for people on the entire mailing list, the response actually observed may be negatively associated with income.

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Available abstract

In their paper “Selecting, Evaluating, and Updating Prospects in Direct Mail Marketing,” Journal of Direct Marketing, Volume 9, Number 2, 1995, Vithala Rao and Joel Steckel introduced a probability modeling tool as an aid to certain direct market marketing decisions. In this comment we extend their model to include those cases where not everyone targeted by a direct mailing appeal actually read the mailing. We suggest that in direct marketing one should not interpret a nonresponse as lack of interest. Specifically, we add a variable to their model to describe the likelihood that a potential respondent reads third-class mail. We use this extended model to show that even when personal income is assumed to be positively related to the response variable for people on the entire mailing list, the response actually observed may be negatively associated with income.

Key concepts: Direct marketing, Direct mail, Respondent, Variable (mathematics), Marketing, Computer science, Class (philosophy), Variables

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