To Understand Consumer Data, Think Like an Anthropologist
November 27, 2013 Editor 0
It was hardly what you’d call an “adequate sample size” for market research, but the results were nevertheless eye-opening for the maker of a pain-relief ointment: A single consumer posted an online photo showing how he placed foil over the ointment to prevent it from staining his pants.
Despite years of consumer research, the pharmaceutical firm hadn’t known about the staining problem. That photo prompted the company to change the product and its communications about the ointment, creating significant value for the firm.
The beauty of listening to social-media chatter is that one picture or one comment can have an outsized impact on your consumer knowledge and, as a consequence, your profitability. But a lot of people in business don’t appreciate that.
Corporate social-listening efforts are typically driven by econometricians, computer scientists, and IT technicians—the people who are expert in database management. They understand digital information, but they don’t always understand how to get from information to meaning. So they boil the data down to percentages, treating random comments (and pictures of people with foil on their legs) as noise.
But if you want meaning, you have to think like an anthropologist. You have to understand that social-listening data is inherently qualitative. That means learning to appreciate the value of the stray remark and synthesizing bits of information into a higher-order sense of what’s going on. That’s how you make the most of social media as a tool for peering inside people’s lives as they’re being lived and discovering what consumers are really thinking and doing.
“Sure, sure,” the numbers-oriented marketing executives may say. Social listening is great for “exploratory” research, but only as a precursor to “real” research that will determine the truth of what’s being said online. What’s needed, they’ll tell you, is broad-based consumer research using representative samples and adequate sample sizes.
Querying a representative sample is great for testing a hypothesis or finding a statistical relationship between known concepts. But often, in marketing, you’re dealing with multiple unknowns. Social listening doesn’t presuppose anything. It has no constraints. Although qualitative information won’t give you a simple equation or statistic that you can show the CEO, it can provide answers to questions you didn’t even know you had.
And comments from a non-representative sample can be highly illuminating. For example, in tech markets, think of the users who regularly post to discussion groups focused on tech products. These knowledgeable netizens provide critical knowledge about product uptake and issues around quality or perception. The same can be said of fan groups and user groups in a variety of fields.
An important player in the electric-shaver category discovered this. Before the launch of a high-end shaver that was to be priced at more than $500 and was encased in brushed aluminum, an Australian retailer posted pictures and specifications of the product online. Almost immediately, consumers began commenting about the product’s “plastic aesthetic” and “cheap look and feel.” The manufacturer took prompt action, posting a new photo series highlighting the quality manufacturing process and construction, neutralizing the negative sentiment spreading online.
Successfully disseminating the results of social listening requires skill at seeing stories and developing insights from messy data. It also requires a penchant for simplicity.
One company we worked with had gone a bit overboard on purchasing tools for integrating social-listening data into its business processes. It had no fewer than 19 dashboards for looking at market and customer behavior, yet none of them were really working. Rather than advise the company to implement yet another new tool, we suggested that an email go out daily, illuminating the most interesting positive and negative statements gleaned that day from customers. The result was that the company acquired a deeper understanding of its customers and drew more insights from the data.
Our work with social listening often makes us think of the comment by futurist Roy Amara that people tend to overestimate the effect of a technology in the short run and underestimate its effect in the long run. Amara’s Law seems perfectly apt when it comes to social-media listening. At first, marketers were ecstatic about social listening’s potential; then, influenced by the numbers people, their enthusiasm cooled. But they haven’t yet fully appreciated its long-term strategic potential. They don’t yet see that social listening can redefine the way managers approach marketing and that social-listening competency may well define competitive advantage in the digital age.
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