In this age of rapid innovation, the market is becoming less and less certain. As innovators, we aim to introduce truly disruptive ideas, not simply line extensions, which by nature are more uncertain. This uncertainty means that our traditional arsenal of research tools is less and less accurate. So, what now? We propose a different approach. Let’s shift our thinking from “research” to “iterative learning” on Minimum Viable Products that we develop as we learn.
What is MVP and why does it matter? The idea of Minimum Viable Products comes out of the startup world and it means, at the simplest level, developing the bare bones model of an idea, and quickly and iteratively learning in order to pivot, optimize or stop pursuing the idea. IN place of “research”, we leverage an iterative learning approach. And, we lean toward behavioral metrics (actual purchase/commitment — “click here to buy” or “enter your billing address here”) instead of claimed metrics (“how likely would you be to buy this?”).
What’s the difference compared to traditional research? We recently worked on a project for a new service. Instead of asking research participants whether would be interested in signing up for the program, what they liked about the idea, and what they didn’t like about the idea, we gave them a mocked up signup form for the program, complete with a place to write their billing address and sign up on the spot. The ensuing conversation was undoubtedly more robust:
What, in particular, convinced you to sign up?
What questions did you have?
If you didn’t sign up, what kept you from signing up?
Why should innovators and researchers care? Testing assumptions through actual behavior enables participants to experience all of the tensions around purchase decisions, instead of imagining themselves there. Therefore, it can be more reliable and actionable when it comes to learning about consumer interest in breakthrough innovations in an uncertain market.
Implications. Iterative learning on MVPs takes a truly customized approach rather than a one-size-fits-all process. We need to head into real retail environments, create A/B tested websites, use mocked up apps and generally think outside the box. In essence, researchers must be agile.
The Garage Group helps corporate teams to innovate and grow like startups, with startup-inspired iterative learning approaches.
