Suppose an advertiser constructs an advertising campaign by placing k advertisements in a magazine. He now estimates the proportion of the population which sees none, one, or up to all k advertisements (called the exposure distribution). Several criteria for evaluating the effectiveness of the campaign can be obtained directly from the exposure distribution. Two of them are reach, the proportion of the population which is exposed to at least one of the advertisements and effective reach, the mean of the exposure distribution. / We develop three exposure distribution models for the cases where advertising campaigns are comprised of one, two, or three or more magazines. The models build on each other in that the model for one magazine is used to improve the fit of the model for two magazines and the model for two magazines is used to estimate the parameters of the model for three or more magazines. / A thorough empirical test, using the AGB:McNair "National Media Survey", shows that each of our models out-performs the best currently-available models. In addition, the three models are proved to have optimal asymptotic properties. / The models are used to select a media schedule which maximizes either reach or effective reach subject to a budget constraint. A monotonicity property of reach and effective reach yields an algorithm for optimizing both reach and effective reach that greatly reduces computation time over conventional methods used to solve integer programming problems. / It is more useful to estimate the proportion of the population which sees the advertisements in a magazine rather than the proportion which sees the magazine. Often, however, no advertisement recall data is available so we are forced to estimate the proportion which is exposed to just the magazines. If advertisement recall data is available we give a natural and simple adjustment of the original magazine exposure data to get advertisement exposure data. Our models also give an excellent fit to these adjusted exposure data. / Source: Dissertation Abstracts International, Volume: 48-07, Section: B, page: 2021. / Thesis (Ph.D.)--The Florida State University, 1987.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76140 |
| Contributors | DANAHER, PETER JOSEPH., Florida State University |
| Source Sets | Florida State University |
| Detected Language | English |
| Type | Text |
| Format | 107 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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