The old-school way of capturing consumers insights — having people fill out an online survey, days after the activity has happened — simply won’t cut it anymore.
Note: This is the fifth article in a series of blog posts from our CEO & Founder, Matt Kleinschmit, exploring the principles of conversational research design. To get notified of new content from this series and for more best practices for market research and insight professionals, subscribe to our blog.
Back in 1992, Bruce Springsteen released a song called “57 Channels (and Nothin’ On)”— a fairly on-the-nose critique of what was then a relatively new and expanding cable TV universe. Of course, 57 channels seemed quaint just a couple years later — 57 quickly became 570 channels — and by the turn of the century, that universe would be swallowed whole by the Internet. Our sources of information and entertainment exploded, and the ways in which brands could reach — and analyze — consumers had expanded exponentially.
You could say that there are now about 57 billion data points to study — with more added each second: McKinsey reports that 75 percent of consumers have tried a new store, brand or different way of shopping since the pandemic started. Change is happening at breakneck speed, and today we are swimming in data — some might say drowning. But what does it all mean?
For brands to succeed in a post-pandemic world, they’ll need to move beyond the limitless data entrails — which help us see what’s happened in the past — to also capture the emotions and context driving these behaviors.
This “trifecta” of information — what I call “3-D Insights” — is a key benefit of mobile messaging-based conversational research design, blending a robust knowledge of behaviors along with a deep understanding of emotions and context. The end result? A more holistic view of why behaviors are happening and, more importantly, where the market is headed.
In the early months of the pandemic, we were asked by Tyson Foods — the multinational company behind popular brands such as Hillshire Farm, Sara Lee and Bosco’s — to explore that “why” question in depth. We did a series of studies with Tyson consumers on how their morning routines were changing and evolving. What breakfast looked like — how that ritual played out, in households across North America — had been severely disrupted by COVID: moms and dads weren’t commuting to work, and kids weren’t going to school. There were no quick bites of something as you waited for your train or sat idling in morning traffic.
Tyson could see the change happening in its sales numbers and knew that COVID was behind the trendlines. But they wanted to better understand the specific emotions and context driving that change. To help them, we developed a modern version of the consumer diary — engaging hundreds of consumers during their morning routines, both on weekdays and weekends. We asked them to capture these insights via a variety of mobile messaging-based techniques, including short text-based chat surveys, photos and videos.
Video feedback, in particular, was critical to capturing those elusive emotional elements. Using video selfies, Tyson consumers would talk to us while they prepared breakfast for their family. They could flip to their rear-facing cameras and show us what they were preparing. We could see the context of their decision-making and the meal-prep process: Who was in the room? What was in the fridge? What did the scene look like: was it peaceful or chaotic?
Leveraging artificial intelligence and machine learning, we ultimately were able to analyze hundreds of these videos to understand overall sentiment.
Pre-pandemic, morning routines were typically pretty harried in most households, with people rushing around and getting ready for the day before heading out the door. During the height of the pandemic lock-down, there was a different context — in many cases, a more peaceful and serene home environment — and that affects the kind of meals and food choices that consumers are making.
Through video we were able to see the emotions on consumers’ faces — whether it was a look of stress, a look of satisfaction or even a look of joy. And leveraging artificial intelligence and machine learning, we ultimately were able to analyze hundreds of these videos to understand overall sentiment, tapping into some of the emotional themes that were common among consumers.
We also used a variety of projective metaphor elicitation techniques to dive a little deeper. Rather than asking them directly, “How does this make you feel?” we presented various images to consumers as a part of their daily diary. “Thinking about your breakfast routine, which image best symbolizes what your meal preparation was like this morning?” We might show things like a brick wall or a maze or a sunrise to elicit those responses. We also presented consumer routines back to them and had them talk about it. “Why did you do this? Tell me more about what was happening here?”
This in-the-moment diary approach allowed us to capture a variety of consumption behaviors and breakfast-time activities — including “guilty indulgences” that consumers might not otherwise admit to. For Tyson, understanding those emotional decisions — and seeing the context those decisions were made in — has allowed them to develop a future innovation pipeline that better meets the needs of its consumers. It has also become an integral part of their brand positioning.
The old-school way of capturing consumers insights — having people fill out an online survey, days after the activity has happened — simply won’t cut it anymore. There are too many channels on; too much for consumers to remember and too easy to forget. As brands swim through this expanding sea of data, they need to remember to look around — to use that 3-D vision to see which way the currents are running, and to know how deep is the water.