ABSTRACT
This work investigates under what circumstances a television campaign should be complemented with online advertising to increase combined reach. The authors first proposed probabilistic models to derive necessary and sufficient optimality conditions for the best media mix. They then relied on roughly 26,000 television campaigns to train classification models to decide whether a campaign should add online advertising. Linear and support vector regression models are used to predict optimal budget allocation, cost savings, and additional reach. The resulting meta-study yields simple, interpretable, and actionable rules that improve the understanding of media-mix advertising.
- © Copyright 2017 The ARF. All rights reserved.
ARF MEMBERS
If you are a member of the Advertising Research Foundation, you can access the content by logging in here
Log In
Pay Per Article - You may access this article (from the computer you are currently using) for 30 days for US$20.00
Regain Access - You can regain access to a recent Pay per Article purchase if your access period has not yet expired.
Log in using your username and password
Vol 57 Issue 3
