A Very Tasty Focus Group
This week, I – along with another 100 or so people – paid Dinner Lab $70 each to be part of a focus group. And we enjoyed it. If you’ve not heard of them, Dinner Lab “…is a social dining experiment that unites undiscovered chefs with adventurous diners who are looking for something different from the conventional restaurant experience.”
In practical terms, they create pop-up restaurants in major cities around the U.S., often in quirky locations with menu items you’d expect to see in trendy restaurants where you pay $18 for an appetizer the size of your thumb.
Seated farm style, my wife and I quickly became friends with our companions. A typical cross-section of San Franciscans, we dined with a radiologist, the HR director for a venture-backed startup, and software engineers from Yahoo and Dropbox.
As much fun as I had, this article is about how Dinner Lab has turned their customer discovery process into a central pillar of their product offering, with marketing research and customer experience design principals baked into their business model.
Wisdom of the crowd: Real-time customer feedback informs product and experience design
According to a New York Times article, Dinner Lab “brings the wisdom of crowds to haute cuisine.” Each diner is presented with a pencil and a card on which they’re expected to rate the quality and originality of various dishes and drink pairings as they eat – one course at a time, on a scale of 1 (poor) to 5 (great).
At each phase of our six course meal (Course 1: Marinated – and peeled (!) – heirloom tomatoes, with fig, pickled grape, pine nuts and melon oil), we and our companions happily debated the merits of each aspect of the meal, comparing notes and ratings. Though customer research is a central part of our customer experience consulting business, this was the first time I’ve heard participants debate their interpretation of rating scales.
One diner insisted the only fair scale was based on whether or not he would pay typical prices for a dish in a restaurant. (Note – since portions are walnut-to-golf-ball sized, he rated pretty low). Another was all about “the initial taste, and the finish.” Her scores were pretty high. For four of the six courses, my wife and I rated things high because they were just SO damn good.
When I came to work yesterday morning, I was greeted with a follow-up survey on the overall experience, where I was able to provide feedback on location (interesting), portion size (small), service (indifferent), and food (awesome).
What Dinner lab does that’s so brilliant is making the process of customer feedback central to the experience itself. This feedback further informs product and experience design, providing the company a real-time lab for creating the perfect dining experience.
Applying customer insights and data to product, service and customer experience design innovation.
Dinner Lab plans to use all this customer data to move from pop-up to physical restaurants, choosing the chefs who will helm and the food they’ll serve based on a crystal-clear idea of what their customers do and don’t like.
As they expand their research-driven foodie empire, they’ll continue to learn and, I suspect, thrive, because they truly “get” what so many established firms don’t: Listen to your customers, understand what they want and need, and give it to them. And use the data that surrounds your customers to actually benefit your customers.
I haven’t yet figured out how to apply the Dinner Lab concepts of getting paid by their customers to provide feedback to some of our other clients. After all, innovation isn’t just something we plan for others, we’re continually learning and evolving ourselves as markets and customers change. I’m guessing enterprise software and bank customers are a bit less likely to take that bait. But we do have a couple global consumer products clients whose customers just might be a fit.
In the meantime, I’ll continue to suffer through my research process (Course 5: Cabernet braised short rib with roasted shallot, date, and mascarpone coffee). After all, someone has to suffer through it. It might as well be me.