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Do Market Researchers Get Prickly About Social Web Data?

 

 

By Jason Brownlee

Consumers around the world generate an avalanche of social media chatter every day. Much of this material takes the form of unstructured text feedback about brands and reaction to traditional ‘off-line’ media content.

Most advertisers and media owners recognize this trend and consequently invest a lot of money in social web ‘listening’ platforms.

As this trend unfolds it appears the market research industry is being pushed, perhaps against its will, from a classic “consumer research” model into a new era of “consumer feedback”.

This new era is characterized by client demands to integrate social media feedback into brand development processes, business strategy and marcomms evaluation.

This presents a dilemma for classically trained market researchers, who could be said to have a prickly relationship with social media feedback.

This may be due to a healthy respect for classic principles of statistical science, structured sample design, controlled recruitment and ethical interviewing practices etc. Professionals steeped in classic market research (MR) discipline can be forgiven for harboring grave reservations about unstructured social web data.

However, I believe the MR community can and should take the lead in developing rigorous methods for integrating social web feedback into the unfolding picture of contemporary brand and media relationships.

We should not fear social web feedback as a dangerous rival to, or replacement for, structured MR practices. Indeed, a more rigorous approach to harnessing the value of social media can yield real benefits for MR professionals and their organizations.

For instance, social media captures feedback from consumer groups that are becoming harder (and more expensive) for conventional research techniques to reach.

In additional, such feedback is often spontaneous and sincere; it’s also very rich and colorful. It offers qualitative insights at quantitative scales (sometimes I think of it as ‘mega qual’).

Perhaps most interestingly, when consumers freely choose to express topics of personal interest in a manner that suits themselves, it overcomes the tendency of classic research to ‘frame’ audience responses. In other words, sometimes we only get answers to the questions we ask.

Throughout my career I’ve commissioned small ‘quick and dirty’ focus group projects prior to quant studies in order to guard against this problem. Now I think social media feedback gives me the basis for a more robust solution to this challenge.

Perhaps only the classically trained MR community has the skill-set needed to safely embrace Social Media feedback as a powerful compliment to classic audience research.

As the MR industry moves forward from a classic model of ‘consumer research’ to a new era of ‘consumer feedback’, MR professional can take control of their destiny by developing the rigorous techniques clients need to safely integrate rich social media feedback into existing consumer research and data analysis processes.

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9 responses to “Do Market Researchers Get Prickly About Social Web Data?

  1. I love social media data and have been working with it (in unstructured and structured ways) for a dozen years – it’s endlessly fascinating and very useful.

    But while it is often spontaneous and usually sincere, it’s also subject to plenty of framing itself. The choice to post something on social media has a context like any other – an intended audience, a purpose, the norms and social conventions of the format, and so on. What we’re really doing is exchanging a frame we think we control (the question) for a frame we can’t see. And so we tell ourselves it isn’t there.

  2. A great article and a great comment from Tom. What I always tell my training students is that this is now part of the tool chest–but we need to apply the vigilance and rigor to social media feedback that we do to more “conventional” research methods. For example, when we don’t have demographic data as context, we need to be very careful about how we draw and report our “key findings.”

  3. Have to say I’m not sure I like the term ‘feedback’ – it isn’t strictly feedback because, while there may be an agenda to posting, social data is seldom posted as a response to a direct question. That’s the whole point of it, as Tom explains, it’s unstructured. Generated entirely out of a research environement. Organic conversations. Far richer and more potent than feedback.

    If interpreted like this, we can see that the insights we can glean from social data extend far beyond ‘brand’ or ‘product’. We can use social insights to build a richer understanding of how people feel and talk about the issues affecting society and entire industries.

    This approach means we don’t need to worry about demographics. Typical demographics is ‘old research’. Age. Gender. Socio economics – don’t play out on social media. People connect and communicate based on dispositions and preferences. People create and join communities for more emotional and human reasons than where they happen to live.

    Yes we have to apply conventional research rigor. Absolutely. But social media research shouldn’t be seen as a better alternative to a quick and dirty focus group (even though it is). There is a type and depth of insight that is utterly unique to social content and which, therefor, is perfectly suited to meet certain research needs. It is has a rightful place amidst the research mix. No better but certainly no worse.

  4. Interestingly some of us have been applying the rigor of Market research to social data for many years. Our company, MotiveQuest, is a social market research company launched in 2003. We won a Ogilvy last year for a case that relied entirely on rigorous analysis of social data for insights. Cheers

    David

  5. Very intersting discussion. I agree with Dan.
    I’ve realized that when the brand is enough strong, it is posible to scrap and structure an amount of data, and then just order the pieces into similar projective exercises we do in traditional focus groups.
    The problem of knowing the context depends on you: go back and forward in time is possible, and to read the complete voice of selected people too. Even you can choose the geography of your sample (how many km around any city).
    Finally, wou should do manual analisys, and then you will realize the real power of social media. What I propose is a artisan work. Sorry for my english.

  6. Tom A: it depends if you count blogs as part of “social media”. They started in the late 90s, Blogger was open public in 2000 – I had my first meeting about understanding consumer-generated material for business info purposes (including blog entries) in May or June that year. So, a dozen.

    Communities are much older obviously, personal profiles also older – networked profiles (a la FB) date from the late 90s but only sporadically took off before FriendsReunites/Classmates. The first “social network analysis” project I worked on was in 2001 – for networked phone profiles in Japan. I did a crap job mind you – didn’t have the tools or indeed the theory! But “social media” data and research goes way back.

  7. The MR community can leapfrog the nascent social media monitoring and measurement industry by acquiring some of these start-ups, applying the best stats and models, and going beyond simply ‘Like’ counting.
    Social media, the social web as it were, is the world’s largest focus group. Albeit an unstructured and fragmented focus group. MR professionals and companies have the ability to structure and tame the beast.

  8. Good discussion. I agree with Dean. I think the MR community has the opportunity to really frame the discussion of what it means to have a Like or to have X number of followers and what is trending. However, new tools need to be leveraged to frame this discussion in a real-time way. The reason the marketing world likes social listening is it is in real time. They won’t put up with latent methodologies to understand what it all means. The MR community will need to leverage real-time tools to structure and tame the beast as Dean points out.

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Jason Brownlee

Chief Executive Officer, Dollywagon Media Sciences

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