Last week I chaired the ESOMAR 3D event in Miami. Like most ESOMAR events it was awash in new thinking, innovative methods and lots of discussion, both formal and informal, about where the industry is headed. It was not just a breath of fresh air; it was the winds of change blowing hard in your face. In my summary at the end of the conference I noted that amongst all of the exciting talk about the methodological disruptions in MR there were at least small signs that rumors of the death of the survey are exaggerated. Or was I just seeing what I wanted to see? And so I was cheered to see Lenny Murphy's excellent interview with Seth Grimes, a genuine thought leader in the field of text analytics.
I've been involved with surveys in one capacity or another for over 30 years and one of the dreams has always been software that can analyze and make sense of unstructured text. And so there is a certain irony that a method (social media listening) that many claim will replace surveys both relies on and has given renewed emphasis to the problem of making sense of text. But as in many instances with what we are now calling "the NewMR" we're not there yet. Or to quote Seth, "The race is on, but we are a long way from the finish line."
As his last question Lenny asked the big one: paint a picture of the future of MR. Here I quote Seth's answer at length:
I heard a speaker say, earlier this year, that with a "culture of listening" there is "no need for surveys." . . . No, you need surveys. For customer-experience initiatives, for market research, you can't learn everything you need to know without systematically asking a set of directed questions to a known set of respondents. Text analytics, sentiment analysis: These technologies will help you do better surveys. . . We'll see even further linking of survey- and social-sourced insights with behavioral and psychographic profiles inferred from "big data" clickstream, location, service utilization, transactional, and other tracking data and mined from content. This triangulation — ensemble methods that coordinate and combine multiple models and approaches — is the way to go.