Recap of the German ESOMAR Career Day 2020

For the third year in a row, the international market research association ESOMAR cooperated with Pforzheim University of Applied Sciences on the national “Career Event”, a compact event format which informs students of business administration about current research trends in market research under the heading “Industry meets Talents”. It also gives students the opportunity to get in touch with potential employers, seasoned market researchers, but also the high potentials of the industry. Christa Wehner, head of the study programme Market Research and Consumer Psychology, together with her co-organisers from the association side, the national ESOMAR representatives Dirk Frank and Christoph Welter, welcomed about 70 participants in the online conference room on 29 October. After a brief introduction of the goals and focus of work of ESOMAR and the “Young ESOMAR Society” (YES), the young people’s organisation for students, by Dirk Frank, who also teaches market research as an honorary professor in the course of studies, it went into medias res.

This year’s winners of the YES Award, the international ESOMAR award for the best research work from the young researchers, started with an enthusiastic presentation on an old problem of market researchers: Can one expect trustworthy information when asking consumers directly about their salary in studies? Speaking from Hong Kong and Singapore, Vardhini Ramesh and Joleen Chan, both Global Business Graduates of Kantar, presented an innovative approach called “Time to destroy the online facade”, which enables a more reliable income estimation by using a series of indicator questions. Over one hundred potential wealth indicators were tested in three countries to determine how well they predict a person’s real wealth and income without unduly skewing the results from social desirability or other response tendencies. The research result is a standardised set of questions which is used playfully during the course of a survey to reveal another facet of the true self through the consumer’s “facade”. The young researchers concluded with a fiery appeal to their student audience to start their careers with unflagging curiosity and courageously question familiar practices.

In sharp contrast to the solution of concrete research problems, the second lecture was about a view from a helicopter of an industry in transition. Christoph Welter, Managing Director of Point Blank, together with David Smith, Director of DVL Smith Ltd., presented a study by ESOMAR entitled “Demonstrating the value of investing in customer insights”. David Smith, a veteran of the industry, former ESOMAR Vice President and winner of numerous research awards, is one of the authors of the study. The study deals with the question of what added value market research can and must make in and for companies in order to be able to prove its relevance: Is company market research experienced by other stakeholders as a pure cost centre or as an important “value creator”? In order to meet the ever-increasing demands, the students were given a concrete picture of the skills that the members of an “Insight Team” on the customer side must have. Christoph Welter emphasised the challenges that a “faster, cheaper and better” paradigm means for market research training: Both communication and storytelling skills are required, the ability to contribute to business growth through creative input and not just passive risk reduction, and knowing when quick answers are sufficient and where deep insight needs justify a slower approach. Last, but not least, the omni-availability of data requires the market researcher’s ability to integrate data from a wide range of sources and make it usable to the corporate context.

The possibilities of modern data science applications using pharmaceutical research as an example were illustrated by Thomas Heil, Vice President Consumer Health at IQVIA, in an exciting presentation (“How artificial intelligence and machine learning are changing market research in healthcare”). IQVIA is a global company with over 67,000 employees and focuses on analytics, technology solutions and clinical contract research. Using the concrete example of the current influence of the Covid-19 pandemic on prescription redemption in the pharmacy and the number of patient visits to general practitioners, modern reporting and analysis tools were introduced. The application of machine learning algorithms was clearly demonstrated using pharmacy sales data. First of all, the differences in the “shopping baskets” of pharmacies whose data are available in the panel are explained in the best possible way by socio-demographic, micro-geographic (e.g. location of the pharmacy) or pharmacy-related data (e.g. number of employees) using random-forrest algorithms, in order to then forecast the shopping baskets of the pharmacies that cannot be represented in the panel, and thus the overall market, using the application of the ML algorithm.

The brilliant conclusion of the afternoon of presentations was provided by a collective of authors, consisting of the market researchers of a well-known brand manufacturer, represented by Marco Walter, Senior Research Consultant at Tchibo, and a start-up, represented by the founders of Cauliflower, Lukas Waidelich and Gianluca-Daniel Speranza. Under the title “Finding the 80% rotten apples in your innovation pipeline. How AI-based semantic analysis brought the break-through in early-stage product testing”, the authors presented a research approach that had already received much attention at the global ESOMAR conference a few weeks earlier: Tchibo’s diverse and rapidly changing range of non-food products requires equally fast decisions. Which articles will be successful, which will flop? What is being sold through which operating channel and what quantities must be purchased from which product? Using historical data, Cauliflower developed a prediction model based on open consumer ratings to predict the flop rate. The basis is an automated procedure which learns the connection between sales success and consumer evaluation via a deep learning model/neural networks. In the subsequent prognostic application, the AI used reacts to the respondent’s answers by asking targeted questions, applies the semantic prognosis algorithm to the new text data and can thus predict the prospects of success for new Tchibo products with 80% certainty.

The usual end of the event with a drink and a snack fell victim to the Covid-19 situation. Instead, the students were able to deepen the topics in virtual break-out sessions with the moderators and speakers and inquire in more detail about one or the other career entry opportunity.