Two weeks ago, I spoke at the Qual360 conference in Atlanta, hosted by the Merlien Institute. If you follow this blog, you’ll know that I typically fold qualitative insight into a diverse research mix, so I went to the conference with a broad view of market research methodologies. But after connecting with qualitative researchers, marketers, academics, and thought leaders from around the globe, I left Qual360 with a renewed appreciation for the fundamental importance of qualitative insight, its deep impact on key business decisions, and its differentiated value in today’s data-driven culture. Here are a few of my takeaways from Qual360:
In a world where everything is getting faster, qualitative research must go slower. As Anita Watkins from TNS and Emily Williams of Newell Rubbermaid put it, qualitative research is not about testing, it is about illuminating context and understanding evolving beliefs. That means qualitative insight can’t be commoditized and sold with the promise of fast, bite-size deliveries. The true value of qualitative insight lies not in the verbatim data but in the accurate analysis of those words in the context of social, environmental, psychological, and emotional depth.
Last week, I had the pleasure of attending the Insight Innovation Exchange conference in Philadelphia. There were many vendors that offered solutions to many common challenges that market researchers face. One common theme I noticed was the challenge for market researchers to make sense of big data. Yes, big data has become something of a buzzword, but consumers are creating a lot more data and market researchers can thrive if they embrace it.
For some time now, Forrester has been writing about the importance of incorporating behavioral tracking insights to marketer researchers’ research mix. Don’t get me wrong — survey research is and will continue to be incredibly important for companies to gain insights on consumers. A survey can capture a variety of consumer behaviors, sentiments, and attitudes. In one survey, marketers can assess their market share and find out the profile of their customers and what they want. And survey research can help provide insight into the “why” — the reasoning behind the choices that consumers make — something that is not possible with behavioral data. However, survey research cannot detail granular activities due to respondent recall. Enter big data, and with it many possibilities for behavioral tracking. Yes, this is nothing new for customer intelligence professionals, who analyze customer transactions, online web tracking, and other consumer behaviors. But by combining survey and behavioral data, marketers get the best of both worlds: They get consumer profiles and psychographics, brand health metrics, and a detailed record of the actions that those consumers actually do.
I am now back from attending this year’s The Market Research Event (TMRE) in beautiful Boca Raton, Florida. As always, TMRE produced a content-packed program that addressed a multitude of different topics, ranging from mobile and technology to shopper insights to ROI and measurement and even data analytics and big data. While I attended my fair share of talks focused on emerging and innovative methodologies, I was really interested in the consultative skill development track. This was a track that focused on discussing what client-side Market Insights (MI) Professionals have learned are the best practices for storytelling and data visualization.
One of the talks that I really enjoyed was by Brett Townsend of PepsiCo, whose talk title was aptly named “Treat Your Clients Like Your Kids — Tell Them A Story.” While this isn’t a new idea for MI Professionals — and he discussed well-known takeaways such as “If we can’t tell a story in 20 minutes, then you don’t have a story to tell” — one comment really struck me: Conflict is the engine that drives the story. Our primary goal as MI Professionals is to understand the conflict that consumers are experiencing in their daily lives and to understand what that means to the company or brand.
To focus on the conflict, Brett broke down the story-building process as if we were in the movie business and we were writers writing a script. For each project you work on, you need to understand the following factors:
· Who is the hero? For our purposes, it will always be the consumer.
Companies adopt advanced analytics tools and techniques to convert data into intelligence and drive key customer-facing business decisions. We see that customer intelligence (CI) professionals involved in customer analytics broadly perform three activities:
Generate analytics: Create and produce analytical insights using analytical tools and technologies.
Apply analytics: Choose the appropriate analytical methodology for the business problem and apply it to the context of the customer lifecycle.
Activate analytics: Use analytical output and insights to optimize customer experiences and to drive customer growth, share of wallet, retention, and lifetime value.