Shark tank winners, Groupsolver, on the future of our industry

By Rasto and Maros Ivanic, GroupSolver GroupSolver saw off some stiff challenges to win the Shark Tank Competition at the CASRO Tech & Innovation Conference in June. We invited the founders of the company to share their point of view on the future of our industry: We are research is at the crossroads. For decades, we have relied on tried and true techniques to extract customer insights. While the implementation of these techniques has evolved—paper surveys have given way to online surveys and qualitative research now draws on the insight from online communities—the research methods have remained reliably stable. However, technology has now been knocking on the door for some time and it is announcing itself with the arguments that cannot be easily dismissed. Exciting new methods such as facial recognition, eye-tracking, and semantic analysis have already established themselves as reliable ways to get deeper insights into consumer behavior. It is inevitable that rapid advancements in the natural language analysis, machine learning and generally faster and sophisticated computing capabilities are making it less necessary to ask customers to complete long and rigorously structured surveys or for market researchers to rely on surveys as the principal source of primary research. We believe that the future of market research lies in making the interaction of primary data (both quantitative and qualitative) with secondary data (big data, click-stream data, etc.) much more fluid and seamless. Our expectation is that primary research will become significantly less structured than we are used to seeing in online surveys. We expect that our ability to understand better the language of respondents, in real time, will allow us to ask more open-ended questions and to interact with their responses in real time. The lessons drawn from big data research and new purpose-built methods will make dealing with the ambiguity of unstructured responses a much simpler problem. Today, a key drawback of natural-language answers is the need to code the responses, which makes it a slow, expensive and relatively imprecise process. But the fast pace of innovation in semantic analysis, machine learning and artificial intelligence methods is starting to allow us to structure unstructured data faster and with more precision. These innovations will help researchers seamlessly merge qualitative insights from primary data with existing secondary data to discern customer insights without significant loss of validity and while preserving data quality. Perhaps all this sounds like a guess about the faraway future of market research. However, we would like to argue that seeing this future does not require a crystal ball. Instead, the future is close enough to be seen with a pair of open eyes. At GroupSolver, we have developed and deployed a methodology to capture consumer insights with a small number of open-ended questions. Without the need to code the answers, our methodology identifies the answers that represent the respondents’ consensus which can be statistically validated. We have shown that it is possible to build a dynamic customer insights tool that learns from respondents and focuses automatically on the important answers. If the future of market research is not here yet, it surely is marked in our calendars Rasto and Maros Ivanic are co-founders of GroupSolver – an innovative customer insights and market research platform. Before GroupSolver, Maros was a research economist with the World Bank, and Rasto was a management consultant with McKinsey & Company and a head of business development at Mendel Biotechnology. They both received their PhDs in Agricultural Economics from Purdue University.