Advertising is a major cost to many organizations. Marketers
face the task of justifying that their spend is substantial
enough to deliver on objectives, while ensuring that it is not
wasteful overadvertising of limited dollars better used elsewhere.
Despite the importance of the accountability of such
expenditure, there is a long-recognized paucity of evidencebased
budgeting approaches (Dean 1951), with relatively little
attention paid to the issue (Corfman and Lehmann 1994). In
censuses of articles from the first 25 years of the Journal of
Advertising, only 11 of 821 articles (1.3%) focused on budgeting
(Muncy and Eastman 1998).
More than 30 years ago it was suggested that much advertising
expenditure is overadvertising (Aaker and Carman
1982)—a problem that persists. Cheong, De Gregorio, and
Kim (2014) found over a 27-year period that 60% of top
advertisers overspent by an average of 34%. Knowledge about
how much to spend typically remains low, with evidencebased
budgeting far too rarely employed.
Varying methods have been proffered to help with advertising
budgeting (Bigne 1995; Riordan and Morgan 1979),
including marginal analysis, elasticities, and econometric and
game theory approaches (Basu and Batra 1988; Corfman and
Lehmann 1994). Nevertheless, the use of heuristics is still
common, which can be favorable for accurate forecasts (Green
and Armstrong 2015). One prevalent rule of thumb is to set
the advertising budget to a fixed percentage of sales (Piercy
1987; Prendergast, West, and Shi 2006; Sethuraman, Tellis,
and Briesch 2011). However, such methods are seen as unsophisticated
and suffer from theoretical drawbacks (Riordan
and Morgan, 1979). Setting budgets to a percentage of sales
stems from a problem of reverse causality, where advertising
expenditure becomes the effect of sales rather than a cause of
them. The approach also delegates budget determination externally
(though this may be a positive), rather than being derived
from internal objectives, capabilities, and costs. This approach
is insensitive to differences among brands, as each brand
would have a share of voice (SoV) equal to its share of market
(SoM). This is fairly uncontroversial: the bigger the brand, the
larger the advertising spend. Many researchers have documented
that setting advertising budgets in line with market
share, or market share expectations, is widespread (Danaher,
Bonfrer, and Dhar 2008; Jones 1990; Binet and Field 2007),
particularly in mature markets.