Yesterday afternoon, GreenBook’s Leonard Murphy and I sat down with some colleagues to discuss “what’s hot, what’s not, and what’s just talk” in the world of emerging market research tools and techniques. It was the very first Communispace UNwebinar, meaning that instead of a forty-slide Powerpoint deck and predetermined talk track, we polled the audience about their thoughts on emerging consumer insights techniques and used field data to kickstart an open conversation. The result was a lively – and at times – provocative discussion that explored new market research methods from online communities and social media analytics to mobile and gamification.
Below is a tweet-by-tweet summary of some of the key takeaways. Don’t forget to watch the full webinar recording below for many more learnings and debates:
“Socio-technological disruption has led to an identity crisis in the market research world.” – @lennyism #dehypeMR #MRX #MR
Private online communities and social media analytics are leading the charge amongst emerging market research techniques #dehypeMR #MRX
Online communities offer an unmatched richness and intimate dialogue with consumers #dehypeMR #MRX
The dream of big data is to allow brands to anticipate consumer needs before consumers know they exist #dehypeMR #MRX
Siri is a big data platform – @lennyism #dehypeMR #MRX
IBM earmarked $15B – half of the entire market research industry spend – to acquire analytics companies #dehypeMR #MRX
Big data and social media analytics are kind of like Minority Report. They scare everybody, but are inevitable. #dehypeMR #MRX
Even when quantitative rigor is employed, 7/10 new products still fail. Qualitative insights are powerful #dehypeMR #MRX
Mobile in market research is more a “how” than a “what” – a mobile survey is still a survey #dehypeMR #MRX
Mobile networks like Shopkick, Gigwalk, TaskRabbit making inroads in mobile engagement, but their purpose is not consumer insights #dehypeMR #MRX
Language-based gamification – asking questions in a way that incorporates game-based models – fits with traditional #MR techniques #dehypeMR #MRX
Doing a survey in flash is NOT gamification. Adding awards badges to a #MR activity isn’t either. #dehypeMR #MRX
In prediction markets, respondents are given a certain amount of points to “invest” in what they think is going to happen #dehypeMR #MRX
The marriage between neuroscience, psychology, marketing, and economics is revolutionary in market research – @lennyism #dehypeMR #MRX
Part of the UNwebinar format included open access to our speakers, with many attendees submitting questions to be answered. While you can listen to all of these in the recording above, here are some topics that were brought up:
Q: Market researchers are traditionally indoctrinated on the principles of statistical significance. Many of these new methods seem to de-emphasize if not reject this requirement. What is the research market (the buyers) opinion on this shift?
A: I think it certainly is true that many of the methods we discussed do not demand statistical significance in order to yield valuable, actionable insights. In part that’s because many of them are fundamentally about discovering unmet needs, unconscious emotions, and about ideating new solutions. And in part, some of them, like Prediction Markets, generate reliable results with much smaller samples. However, as Lenny noted, recent concerns about respondent quality are eroding some buyers’ faith in traditional quantitative methods, even when the results are statistically significant. And given the 70-80% failure rate of new product introductions, along with the extremely niche-based and dynamic market, I think buyers have good reason to question at least some traditional principles.
Q: What are the limitations of the “Big Data” approach in market research?
A: Big Data is extremely powerful in capturing and even surfacing patterns in the what’s of shopper and consumer behavior — where are people going, what are they searching for, what are they buying, etc. But to continually innovate and maintain customer engagement and loyalty, you still need to understand the why’s, and Big Data is of limited value in that area.