Market Research Needs to Change. so what?

Posted by: David Rabjohns
  • November 29, 2016
  • 2

market-research-needs-to-change-so-what-455x290The way people buy has changed, and market research needs to evolve as a result. Sorry, but it is true. Think about the last time you bought a phone or a car or even a new pair of winter boots.  What is the first thing you do? Google it. And when you Google things, you come across other people like you who are wrestling with the same question. You also come across a few people who really took the time to figure out the best answer.

I recently started a search for winter boots, and I was considering Sorel. My favorite Google-it phrase is “vs,” so I typed “Sorel vs.”  I found an online conversation between a few people that got me rethinking a brand in my consideration set.

Person #1, “Trying to decide on Sorel vs. L.L. Bean boots. Any recommendations?”

Person #2, “I think its common opinion that Sorel was a great company BEFORE they switched production to China. Now they are make inferior products in China.”

Person #3, “This explains a lot. I have a pair I’ve had for 15 years and are still great. My wife bought a pair last year and they got a tear in them within half a year.”

The brand manager for Sorel must wrestle with the impact of the thousands of conversations about Sorel happening in various nooks and crannies of the Internet about their products and service. To make sense of the online comments, she needs to quantify the data; the brand manager needs market research. Yet traditional approaches likely won’t uncover what may be influencing consumers along the path to purchase which, in the case of my search, includes how big of a deal the “Made in China” issue is.

So as researchers and marketers, it’s clear we need new approaches. We don’t want to give up on the rigor of traditional research analytics, and we must now extract valuable insights from the wealth of new customer data available as a result of these online conversations.

One such approach is Deep Listening, a form of online anthropology in which we use software to lay a digital blanket over all of the conversations. We can use it to supercharge innovations by discovering white space and unmet needs. We can discover new customer segments, by understanding how people actually use products. We can use it to discern the extent to which Made in China is impacting the Sorel brand, if at all. We can quantify the results, but instead of asking questions of respondents, we are listening to the questions they are asking each other.

Traditionalists will cry out, “Is it representative? How do I know these crazy people online matter?” Well first off, the crazy people online are no less crazy than the crazy people that show up to focus groups or answer surveys. More importantly, we have found, in collaboration with Northwestern University, that their online recommendations are a direct predictor of offline sales (more on that in another post). So while it might be different, it is as representative as any form of research and also predictive, in most categories, of sales.

The way we buy has changed. This means that the way we research needs to change. We can ask, but we must also listen to avoid gaping holes in your understanding of your customers, categories, and brands. Listening adds a super-rich sea of insights and new approaches which, when combined with asking research, make insights better, richer and more actionable. If you are still in doubt, Google it.

  • David Rabjohns
    December 8, 2016
    Chris, you are right that there is a lot of very poor data out there, just as there are a lot of very poor respondents out there. The trick is to get quality, reliable, de-spammed data before you start analysis. That is why we collect and clean all of our own data. The off the shelf pickings are slim. Good watch out.
  • Chris Robinson
    December 7, 2016
    The biggest problem with online data is you just cannot trust it. I am not talking about the Yelp posts from competitors, or spoofed comments from Facebook users looking to develop a huge follower base, I mean completely fake posts generated by paid for services. You may well find that LL Bean post was a paid for initiative. I would be very careful recommending social media sources as anything more than interesting, but be careful.

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