EFFECTIVE ADVERTISING

             It is easy to see that in most cases, advertising works. While the most popular marker to see if advertising works is sales, this is not the only one- increases in awareness, market share, consumer responses, etc. all imply that advertising works (White, 2000) But how much of those increases can be credited solely to advertising?
             Years ago, researchers used to do a 'Correlation analysis' for the purpose of establishing a direct/indirect relationship among two variables (for example, advertising and sales), but this method was proven quite incorrect, as correlation coefficients are symmetric (correlation between variable A and variable B is the same as the correlation between variable B and variable A) (Kernan, 1964). For example, one could analyze the correlation between advertising and sales- as advertising increases, as will sales. This correlation between advertising and sales is the same as the correlation between sales and advertising, making the correlation symmetric- as sales increase, so does the advertising, but at the same time, as advertising increases, so does sales. With this method flawed, it was seen quite difficult to measure advertising effectiveness (McWilliams, 1997).
             Today, there are many other methods of attempting to measure ad effectiveness, some of which very similar to the correlation analysis.
             With a variety of measuring tools available- retail-based measures, single-source data, ad-tracking, or even an econometric model, why is it so difficult to measure advertising effectiveness?
             Measuring the effectiveness of advertising has proven quite difficult, because advertisements function in an environment made up of many uncontrollable variables that may influence factors such as sales- advertising is only one part of the marketing mix. (White, 2000) To say that Mr. X purchased a certain brand based solely on the advertisement he just saw, and disregard factors such as price, product design, b...

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