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Understanding And Interpreting Gain And Lift Charts
Lift and Gain Charts are a useful way of visualizing how good a predictive model is. In SPSS, a typical gain chart appears as follows: In today's post, we will attempt to understand the logic behind generating a gain chart and then discuss how gain and lift charts are interpreted. To do this, we will use the example of a direct mailing company. Let us assume that based on experience, the company knows that the average response rate on its direct mail campaigns is 10%. Let us further make the following assumptions: * Cost per ad mailed = $1 * Return per response = $50 Additionally, let us assume that the company mails out ads in lots of 10,000. Based on these assumptions, if the company mails out 100,000 ads, a table summarizing the results it would obtain from this campaign is provided below: Now let us assume that the company uses SPSS Modeler to develop a predictive model using data from previous campaigns. "Response / No Response" is identified as the ...
Optimizing Direct Mail Campaigns
Direct Mail Campaigns (and their online equivalents) continue to be a popular method to promote a company's offer to potential customers. All of us have received letters from retail stores, financial institutions and other companies with special offers that prompt us to take speedy action to avail of a discount, a bonus or similar attractive proposition. In most cases, I tend to discard these letters without opening them and in rare cases I open them before deciding that they don't apply to me. My behavior is not unique; typical response rates for direct mail campaigns hover around 2% - 3% which means most folks who receive these direct mailers tend to discard them. For companies, this is obviously not good news. Each mailer costs them money (printing and postage) so it is in their best interest not to send out a direct mail to someone that is not likely to respond positively to a campaign. So for example, a company sends out 1,000,000 direct mailers ...
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