Journal of Marketing Behavior > Vol 2 > Issue 2–3

Marketers' Intuitions about the Sales Effectiveness of Advertisements

Nicole Hartnett, University of South Australia, Australia, Rachel Kennedy, University of South Australia, Australia, Byron Sharp, University of South Australia, Australia, Luke Greenacre, University of South Australia, Australia,
Suggested Citation
Nicole Hartnett, Rachel Kennedy, Byron Sharp and Luke Greenacre (2016), "Marketers' Intuitions about the Sales Effectiveness of Advertisements", Journal of Marketing Behavior: Vol. 2: No. 2–3, pp 177-194.

Published: 29 Dec 2016
© 2016 N. Hartnett, R. Kennedy, B. Byron, and L. Greenacre
Individual Decision Making,  Marketing Decisions Models,  Marketing Information Systems
AdvertisingConsumer packaged goodsTelevisionCreativityIndividual Decision MakingMarketing Decisions ModelsMarketing Information Systems

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In this article:
Importance of Choosing Quality Ads
How Good Are Marketers at Predicting More Effective Ads?
Intuition and Decision-making
Intuition and Decision-making in Advertising
Research Objectives


Advertisements vary enormously in their sales effectiveness, so choosing the more effective advertisements to air is an important marketing task. Such decisions are often made intuitively. This study assesses the intuitive predictions made by a global sample of marketers regarding which television ads are more or less sales effective. The findings show that marketers’ predictions were correct no more often than random chance. Multivariate analysis suggests that those with category experience and those in marketing or consumer insights roles make slightly better predictions. Aside from who makes better predictions, further research is needed on how to improve advertising decisions, including use of evidence-based decision support systems and team decision-making.




Commentary Submitted By: Ville Satopää, INSEAD. Date Accepted: 1/2/2017

  • The correct reference for Ungar et al. 2012 is: Lyle Ungar, Barb Mellors, Ville Satopää, Jon Baron, Phil Tetlock, Jaime Ramos, and Sam Swift (2012), “The Good Judgment Project: A Large Scale Test of Different Methods of Combining Expert Predictions,” in AAAI Technical Report FS-12-06, Machine Aggregation of Human Judgment. Philadelphia: University of Pennsylvania.


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