Measuring the Effectiveness of Image and Linkage Advertising: The Nitty-Gritty of Maxi-Marketing

Measuring the Effectiveness of Image and Linkage Advertising: The Nitty-Gritty of Maxi-Marketing

Measuring the Effectiveness of Image and Linkage Advertising: The Nitty-Gritty of Maxi-Marketing

Measuring the Effectiveness of Image and Linkage Advertising: The Nitty-Gritty of Maxi-Marketing

Synopsis

Dr. Woodside picks up where other books on "maxi-marketing" leave off, to prove that the effectiveness of image and linkage advertising can be measured, and to show advertising professionals how to do it. Readable and in detail, with carefully culled examples that go beyond simple case studies, Dr. Woodside provides a 20-step process model of how low and high involvement advertising work, and shows how to use top-of-mind-awareness measures and benefit-to-brand retrieval to assess advertising impact. His book also covers the details of evaluating the effectiveness of competing advertising media and ways to do useful advertising-to-sales conversion studies, within budget and in a timely manner. Well illustrated with tables and figures, and drawing upon important practical and academic research, Dr. Woodside's book will be essential reading for advertising, marketing, and sales executives and their colleagues in the academic community.

Excerpt

Much scientific evidence is available to put to rest the myth that we cannot measure the effectiveness of advertising in promoting customer brand awareness, knowledge, and purchase behavior. The myth is based on the false premise that because many factors may cause increases in the outcome, we cannot isolate any single influence, such as the influence of advertising, to determine its effect--for example, how many additional sales occurred due strictly to the advertising.

GOOD NEWS! VALID BUT SOMEWHAT EXPENSIVE WAYS TO MEASURE EFFECTIVENESS

Wonderful books are available on the details of how to go about usefully and validly measuring the effectiveness of advertising and other marketing variables, on increasing customer brand awareness/knowledge and purchases, and on the bottom-line effect of advertising on net profit. For example, the best basic text on how to estimate the amount of increase in sales caused by changing one or more advertising elements is John Caples (1974) book, in which he demonstrates the method and results of using split-run tests of two or more versions of an ad. While the book now in your hands is not focused on split-run testing, devoting the next few paragraphs to the method is worthwhile.

Split-run ad testing is a scientific method of dividing a population of customers into two or more groups so that the groups are equal and then exposing one group to one version of an ad and a second group to another version; a third group might be exposed to no ad. Then inquiries, purchases, and net profits are measured for each group.

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