Advertising adstock is a term coined by Simon Broadbent to describe the prolonged or lagged effect of advertising on consumer purchase behavior. It is also known as 'advertising carry-over'. Adstock is an important component of marketing-mix models.
Adstock is a model of how response to advertising builds and decays in consumer markets.
Advertising tries to expand consumption in two ways; it both reminds and teaches. It reminds in-the-market consumers in order to influence their immediate brand choice and teaches to increase brand awareness and salience, which makes it easier for future advertising to influence brand choice. Adstock is the mathematical manifestation of this behavioral process.
The adstock theory hinges on the assumption that exposure to television advertising builds awareness in the minds of the consumers, influencing their purchase decision. Each new exposure to advertising builds awareness and this awareness will be higher if there have been recent exposures and lower if there have not been. In the absence of further exposures adstock eventually decays to negligible levels.
Measuring and determining adstock, especially when developing a marketing-mix model is a key component of determining marketing effectiveness.
There are two dimensions to advertising adstock:
- decay or lagged effect.
- saturation or diminishing returns effect.
Advertising lag: decay effect
The lagged or decay component of advertising adstock can be mathematically modelled and is usually expressed in terms of the 'half-life' of the ad copy, modeled using TV gross rating point (GRP). A 'two-week half-life' means that it takes two weeks for the awareness of a copy to decay to half its present level. Every ad copy is assumed to have a unique half-life. Some academic studies have suggested half-life range around 7–12 weeks. Other academic studies find shorter half-lives of approximately four weeks, and industry practitioners typically report half-lives between 2–5 weeks, with the average for Fast Moving Consumer Goods (FMCG) Brands at 2.5 weeks.
The copy in the above graph has a half-life of 2.5 weeks.
Advertising saturation: diminishing returns effect
Increasing the amount of advertising increases the percent of the audience reached by the advertising, hence increases demand, but a linear increase in the advertising exposure doesn’t have a similar linear effect on demand. Typically each incremental amount of advertising causes a progressively lesser effect on demand increase. This is advertising saturation. Saturation only occurs above a threshold level that can be determined by Adstock Analysis.
For e.g. for the ad copy in the above graph, saturation only kicks in above 110 GRPs per week.
Adstock can be transformed to an appropriate nonlinear form like the logistic or negative exponential distribution, depending upon the type of diminishing returns or ‘saturation’ effect the response function is believed to follow.
Measuring the advertising half-life enables brand managers to efficiently space advertising schedules to maximize the effect of each advertising exposure. Measuring the advertising saturation indicates if current levels of advertising are too high or too low, helping brand managers determine if more or less investment is needed to make advertising more effective.
- Broadbent, S. (1979) "One Way TV Advertisements Work", Journal of the Market Research Society Vol. 23 no.3.
- Leone, R.P. (1995) "Generalizing what is known about temporal aggregation and advertising carry-over", Marketing Science, 14, G141-G150.
- Newstead, K., Taylor, J., Kennedy, R. and Sharp, B., 2009. Single source data: how do findings from individual-level analysis converge with aggregate level advertising experiments? Journal of Advertising Research 49 (2).
- "Understanding Adstock Transformations".
4. Broadbent, S. (1997) Accountable Advertising: Handbook for Managers and Analysts 5. Powell, Guy R., Marketing Calculator: Measure and manage your return on marketing investment (2008) John Wiley and Sons. ISBN 978-0-470-82395-8