Innovating in the content analysis models and across the market research lifecycle
Social media, through social networking resources such as Facebook and Twitter, offers unique opportunities for marketers to gain deep insight into the hearts and minds of consumers.
From a qualitative perspective, the natural language form of the consumer sentiment expressed on these content rich sites is exciting. As we know, ethnographic and anthropological related methodologies have grown in popularity in recent years driven by the need to get closer to the consumer by creating or recreating natural environments. These natural environments are designed and executed with the hope and expectation that they will yield as realistic as possible insights and observations around how consumers interact with brands, products and services. Social media marries the convenience of online research (no travel) with the authenticity and natural environmental setting of ethnographic studies. We should expect social media to yield natural, emotional and even visceral content. There is a very real opportunity for researchers to capture deep emotive consumer insight from both the immediate micro-blog rhythmic format of sources such as Twitter, and the more considered, in-depth (but no less useful) format of something like a consumer-driven product review site.
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Established models of social media measurement provide metric based information, but fall short when it comes to delivering directional insights. Many subscription based dashboards leave the insight up to the client, and I feel that misses the mark and is somewhat underwhelming. We can all “mine” or count what people are saying and how often, but what do they really mean and why should you care? What is the motivation behind the comment or “spike” in mentions of your brand? What is being said and shared about your competitors and how does this compare to what is being said about you? What is the next breaking story likely to be and why do you need to have it on your radar? Furthermore, it’s about more than positive or negative sentiment – surely we can to better that that!
Leveraging Social Media Content to Produce Multi-Layered Analysis
Let’s use the Super Bowl 44 ads this weekend as an example. Watching the ads trend on twitter (#brandbowl) in real time it was clear that the Doritos offering polarized and natural segments begin to emerge: some felt it was in bad taste that one ad in particular “House Rules” used an African American single mom and a child slapping his mom’s date (“The Offended” segment), others thought it was hilarious (the “Light hearts” segment), others again talked about the ad both in relation to the other Doritos ads and also in relation to the Super Bowl ad offering as a whole (the “analytic” segment). The Google ad on the other hand prompted deep emotive posts with men but especially with women – the simplistic, romantic feel good approach of their “Parisian Love” ad emerging as one of the Super Bowl favorites (“The romanticists”) and the simple, easy to follow no gimmicks format was also much appreciated (the “narrative lovers”). The language, sentiment and, perhaps most importantly, content and timing of these comments can be leveraged and organized into analytical models such as attribute or association groupings around: brand identity (“what it says about society”), gratification (“how it makes me feel”) and more surface level (“liked/didn’t like”) associations.
Applying specific, targeted, qualitative content analysis models to social media content allows us to leverage deep insights and provide specific recommendations around brands, products and services. From a rudimentary analysis like the one given above, we can compare emotive connections to the client’s goals and then give direction around whether or not the ads triggered the intended reaction.
Innovating Across the Market Research Lifecycle
Furthermore, an insight-driven, as opposed to a measurement-driven approach to social media can in some cases allow for resource efficiencies along the traditional primary market research lifecycle. Let’s use the questionnaire customer development process for a study on 15-17 year old girls in the CPG (consumer packaged goods) space as an example. Most of us have an idea, but can’t say with certainty, about what this particular group care about, and much less the language they use to express themselves (do these kids still say “awesome”?!). Generally, the content of a questionnaire around this topic would be informed by a series of primary qualitative research ( focus groups, one on one or online) in order to explore the dimensions of the issue, the salient points and the language used by the target group to express themselves. Through the smart analysis of the “right” social media content (in this case, the “right” content would be on high traffic/high influence websites for 15-17 year old girls) using a specific frame of reference (in this case “Questionnaire Development”) the need to conduct a series of focus groups to figure out what the issues are and how this particularly demographic group expressed themselves is diminished. This example could apply to any number of research audiences.
Perhaps the main draw for me around social media content is simply because it’s fun to work with. I love the raw immediacy of the content on their and I believe in the importance of listening to consumers and leveraging the powerful and ever improving resources we have that grant us access. I honestly believe that social media is the biggest game changer to the consumer insights model since the wide adoption of internet technologies.
About the Author
About the Author: Adam Henderson is the CEO and Founder of Henderson Insight (Denver, CO). Henderson Insight provides custom qualitative market research consulting solutions and also, through their proprietary Insight Genesis methodology, specializes in leveraging social media content to produce directional insights for their clients. www.hendersoninsight.com.
