Warc, 14 July 2014
NEW YORK: Summertime is budget-setting season for many
marketers, and a study in the current issue of the Journal of Advertising
Research adds a new twist to this annual exercise.
Landing on an advertising budget should not simply be a
number-crunching experience, contend Douglas West (King's College London), John
B. Ford (Old Dominion University) and Paul W. Farris (University of Virginia
Darden School of Business).
In How Corporate Cultures Drive Advertising and Promotion
Budgets: Best Practices Combine Heuristics and Algorithmic Tools, they divide
budgeting methods into two broad forms.
One involves using heuristics, like making choices based on
market share, what a rival is spending, a percentage of absolute sales and
simply was is "felt" to be necessary.
The other depends on algorithmic methods, based on
contributors like quantitative models, incremental testing, objective tasks and
return on investment.
A combination of both can lead to more reliable (and flexible)
marketing-spend allocation, and to an end result that reflects not just the
culture of the marketing department, but the entire organisation.
"The results clearly showed that the greater the
participation of the marketing personnel, the more likely algorithmic methods
would be used to augment, but not totally replace, heuristic methods," the
authors suggest.
"What appears to be the case is that marketers
preferred logic and probability; when their participation was more diluted by
other functional areas, the likelihood of using heuristics increased."
And the authors support their discussion with an analogy
drawn from the great American pastime.
"What the baseball player will do is run toward the
ball, constantly adjusting his speed to maintain as constant an angle as
possible. A series of adjustments are made as the forward progress advances.
The catch is made largely because of the outfielder responding to a series of
heuristic," they write.
"It is the contention in this study that managers
should think of heuristic budgetary processes in similar ways and have
confidence in their value in conjunction with algorithmic techniques."
Data sourced from Warc
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