12 years ago
Measuring Marketing ROI Along the New Path-to-Purchase

The internet has reshaped the consumer’s path-to-purchase more than anything since Bulova aired the first television advertisement in 1941. Although online advertising has been around since Prodigy was promoting Sears’ products in the 1980s, measurement efforts have failed to keep up with the evolution of digital marketing and its impact on buyer behavior. The 21st-century consumer is more instrumented, interconnected, and informed than ever, and the “funnel” concept from 1898, used to describe the consumer decision journey, has been replaced by loops, mazes, and clouds!

New media have given consumers new opportunities to evaluate brands and to advocate on their behalf. In fact, the entire consumer decision-making process can be completed online from the time a need is triggered through the purchase and post-purchases stages when a buyer voices her (dis)satisfaction online. While the idea that this journey is no longer linear has been around for years, most efforts at incorporating digital marketing into marketing mix models fail to recognize this fact. Most of today’s applications of marketing response models are based on marketing science from the 1960s and 1970s.

Marketing science in the academic arena has evolved tremendously since the first application of marketing mix models in the late 1980s. There are more recently developed econometric and statistical techniques which must be utilized to properly measure the interdependencies among paid, owned, earned, and shared media and their impact on buyer behavior. In today’s multiscreen world, a television ad may send a consumer online to conduct a search for more information or directly to the company’s website. She could perhaps make the purchase online and then tell her friends about her purchase through her content-sharing service of choice. She might print a digital coupon at home to take to the store later or even receive a coupon on her smartphone while she’s in the store. When she returns from the store, she could search for a recipe to use the ingredients she just purchased on sale with the digital coupon she found online. She then hops back online to tell her friends about the dish she just prepared. All this activity was triggered by that initial television ad.

In order to give credit where credit is due, one must consider the direct, indirect, and feedback effects mentioned above. That simply can’t be accomplished in models that view the consumer decision journey as a linear process. It requires far more than simply adding digital measures alongside offline marketing activities into a single-equation model. With this revised role of marketing, traditional models are struggling to properly measure the impact of digital marketing. It’s time to “hit reboot” and to begin leveraging 21st-century analytics to measure marketing’s ROI along this new path-to-purchase.

Please feel free to contact me at estacey [at] stern [dot] nyu [dot] edu with questions or comments.

E. Craig Stacey, PhD
Research Director, NYU Stern Center for Measurable Marketing
Founding Partner, Marketing Productivity Group
E. Craig Stacey, Ph.D., is a recognized expert in the area of marketing productivity analysis with a special emphasis on marketing mix modeling and online versus offline marketing resource allocation. He guides The Center’s research direction, and identifies potential research projects. He is a founding partner of The Analytic Consulting Group and previously served as Analytics Director for MarketShare Partners. Prior to joining MSP, he was Managing Partner at ACG Solutions and Industry Liaison for Emory University’s Zyman Institute of Brand Science. He was previously employed as Director of Marketing Science for The Coca-Cola Company and as Vice President of Marketing Science at DemandTec. He has also served as Senior Vice President, Analytic Product Management and Development, at Information Resources, Inc. Craig received his Ph.D. in Marketing and Statistics from the University of Alabama, where he specialized in econometric applications of marketplace data. Craig has consulted on projects for many industries, including consumer products, entertainment, financial services, quick-service restaurants, telecommunications, and transportation. He has served as a faculty member at leading business schools, teaching marketing productivity analysis, pricing strategy and tactics, and marketing management. He has been a regular speaker at events sponsored by the Advertising Research Foundation, American Marketing Association, the Institute for Operations Research and the Management Sciences, and the Institute for International Research. Craig has served as a Trustee of the Marketing Science Institute and as a member of the Advisory Board for The University of Georgia’s Master of Marketing Research program.