This year the theme of the conference was “Marketing in the age of data”. Needless to say, Big Data was one very hot topic with very interesting sessions on privacy and recommendation engines, and remarkable keynotes.
In two keynote speeches on 26 May, Prof. Michel Wedel (University of Maryland, USA) and Prof. Koen Pauwels (Ozyegin University, Turkey) presented a worrying situation for marketing academics. Maybe for the first time, academics lay behind practitioners in the field of Big Data. The tools academics use are being abandoned by the industry, the samples and methods they use don’t reflect current practices. Distributed computing for instance is not used in academic research; technologies and languages specific to Big Data are also unknown (Hadoop, Spark, Kafka, …).
With such a gap between scientific marketing and the industry, one may wonder how academic marketing can still make a contribution beyond the mere theory ?
Too often for instance the models proposed are of little use for the industry. I attended a session on recommendation engines where a model with a dozen constructs was proposed, each construct based on 5 to 10 variables. Besides the mere intellectual challenge, how could such a model be useful? Most (if not all) constructs are impossible to measure in an actual business setting (can you imagine asking each person in your database to answer a 100-question survey?).
In theory, academics should think about the managerial implications of their research. Most of the time however, what I saw were simplistic or even contradictory managerial implications, which revealed the lack of practical knowledge of their author(s).
This situation is worrying because companies need more than ever to strengthen their competitive advantages with top-notch results from academia. Unfortunately, the methods, tools, or models developed by academics rarely cope with current business trends and needs.