Advertising Budgeting, Wearout and Copy Replacement

Pekelman, Dov; Sethi, Suresh

doi:10.2307/3009842

Cited by 5 publications

(8 citation statements)

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“…It is important to recognize the distinction between the effects of advertising wearout and those due to forgetting. Advertising wearout lowers the effectiveness of advertising copy (e.g., Pekelman and Sethi 1978), whereas forgetting leads to a decrease in aggregate brand awareness (e.g., Mahajan, Muller, and Sharma 1984). Thus, wearout refers to the effects of advertising when it is exposed, while forgetting refers to the degree of decline of the memory of advertising when the advertising is not being exposed.…”

Section: Advertising Wearoutmentioning

confidence: 99%

“…Other research on media scheduling has been largely theoretical in nature with the focus on identifying conditions under which different types of dynamic media scheduling strategies are optimal. Curiously, except for Pekelman and Sethi (1978), none of these models has discussed or included advertising wearout (see, e.g., Feichtinger, Hartl, and Sethi 1994). 2 It has been shown that a continuous spending strategy is optimal when brand awareness or sales is a concave function of advertising spending, while a very rapid switching between "on" and "off" advertising (termed a chattering strategy) is optimal when the function has an S shape (e.g., Sasieni 1971;Mahajan and Muller 1986).…”

Section: Media Scheduling Modelsmentioning

confidence: 99%

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Planning Media Schedules in the Presence of Dynamic Advertising Quality

1998

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A key task of advertising media planners is to determine the best media schedule of advertising exposures for a certain budget. Conceptually, the planner could choose to do continuous advertising (i.e., schedule ad exposures evenly over all weeks) or follow a strategy of pulsing (i.e., advertise in some weeks of the year and not at other times). Previous theoretical analyses have shown that continuous advertising is optimal for nearly all situations. However, pulsing schedules are very common in practice. Either the practice of pulsing is inappropriate or extant models have not adequately conceptualized the effects of advertising spending over time. This paper offers a model that shows pulsing strategies can generate greater total awareness than the continuous advertising when the effectiveness of advertisement (i.e., ad quality) varies over time. Specifically, ad quality declines because of advertising wearout during periods of continuous advertising and it restores, due to forgetting effects, during periods of no advertising. Such dynamics make it worth-while for advertisers to stop advertising when ad quality becomes very low and wait for ad quality to restore before starting the next “burst” again, as is common in practice. Based on the extensive behavioral research on advertising repetition and advertising wearout, we extend the classical Nerlove and Arrow (1962) model by incorporating the notions of repetition wearout, copy wearout, and ad quality restoration. is a result of excessive frequency because ad viewers perceive that there is nothing new to be gained from processing the ad, they withdraw their attention, or they become unmotivated to react to advertising information. refers to the decline in ad quality due to passage of time independent of the level of frequency. is the enhancement of ad quality during media hiatus as a consequence of viewers forgetting the details of the advertised messages, thus making ads appear “like new” when reintroduced later. The proposed model has the property that, when wearout effects are present, a strategy of pulsing is superior to continuous advertising even when the advertising response function is concave. This is illustrated by a numerical example that compares the total awareness generated by a single concentrated pulse of varying duration (blitz schedules) and continuous advertising (the even schedule). This property can be explained by the tension between the pressure to spend the fixed media budget quickly to avoid copy wearout and the opposing pressure to spread out the media spending over time to mitigate repetition wearout. The proposed model is empirically tested by using brand-level data from two advertising awareness tracking studies that also include the actual spending schedules. The first data set is for a major cereal brand, while the other is for a brand of milk chocolate. Such advertising tracking studies are now a common and popular means for evaluating advertising effectiveness in many markets (e.g., Millward Brown, MarketMind). In the empirical ...

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Section: Advertising Wearoutmentioning

confidence: 99%

Section: Media Scheduling Modelsmentioning

confidence: 99%

Planning Media Schedules in the Presence of Dynamic Advertising Quality

1998

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“…To this end, we first transform the noisy data (signal plus noise) into a set of numbers called the wavelet coefficients. This property is especially useful in the context of advertising data because media spending patterns are like square waves of onand-off pulses (e.g., Mahajan and Muller 1986;Winer 1993), awareness patterns exhibit periodic rise and fall (Zielske 1959), and advertising copy replacement induces sharp jumps (Pekelman and Sethi 1978). By applying a thresholding scheme that "kills" (sets to zero) the small wavelet coefficients (noise), it is possible to recover the noise-free signal.…”

Section: Dls Estimatormentioning

confidence: 99%

Controlling Measurement Errors in Models of Advertising Competition

Naik

Tsai

2000

Journal of Marketing Research

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Commercial market research firms provide information on advertising variables of interest, such as brand awareness or gross rating points, that are likely to contain measurement errors. This unreliability of measured variables induces bias in the estimated parameters of dynamic models of advertising. Consequently, advertisers either under- or overspend on advertising to maintain a desired level of brand awareness. Monte Carlo studies show that the magnitude of bias can be serious when conventional estimation methods, such as ordinary least squares and errors in variables, are employed to obtain parameter estimates. Therefore, the authors have developed two new approaches that either reduce or eliminate parameter bias. Using these methods, advertisers can determine an unbiased optimal advertising budget, even if advertising variables are measured with error. The application of these methods to estimate the extent of measurement noise in empirical advertising data is illustrated.

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“…The most typical example is the problem of optimal maintenance and replacement of a machine; see Rapp (1974) and Pierskalla and Voelker (1976). Other examples occm' in forest management such as in Naslimd (1969), Clark (1976), and Heaps (1984), and in advertising copy management as in Pekelman and Sethi (1978).…”

Section: Maintenance and Replacementmentioning

confidence: 99%

Optimal Control Theory

2000

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Advertising Budgeting, Wearout and Copy Replacement

Cited by 5 publications

References 0 publications

Planning Media Schedules in the Presence of Dynamic Advertising Quality

Planning Media Schedules in the Presence of Dynamic Advertising Quality

Controlling Measurement Errors in Models of Advertising Competition

Optimal Control Theory

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