How to identify the best innovation ideas
When most people think about innovation, they think about novelty and growth and birth and ideas.
In fact, innovation is just the opposite.
Innovation is 80% killing ideas and 20% making them work. Shouldn’t it be the other way around?
If you have a big idea, or maybe just a little idea, the chances of that idea finding its way to launch are slim to none.
Why is that? Part of the answer is in the way innovation processes are designed in organizations. Teams select an area of potential market opportunity for exploration. Interviews, focus groups, surveys, and competitor research take place. The team comes together, and ideas—often lots of ideas—are generated in what is still an early phase of the innovation cycle. What happens to these ideas?
Innovation ideas are put through the wringer. Sometimes it’s a scorecard. Sometimes it’s a committee. Either way, 20 ideas quickly become two. This whittling process is pragmatic: team capacity and development budgets are finite, after all.
But are great ideas being left behind? Are the right ideas being pursued? And does the value of knowing the answer exceed its cost?
Many of the costs of starting a new business, especially a digital business, have declined. The arrival of the cloud massively reduced infrastructure cost. Platforms for product design, community, and app development have popped up, making early prototyping inexpensive. Rent as a percent of startup expense has declined, thanks to the advent of work-from-home.
But average seed rounds have increased over the last few years (at least through 1H 2022), suggesting that the overall cost of launching something new has grown. That’s a good reason to narrow a pool of ideas for innovation to just a few.
But what’s the right way to narrow? And where is all the money going?
According to Bridgewater Associates, 60% of early stage venture funding is spent on team and cloud; the other 40% goes to customer acquisition. That 40% is presumably all about finding product-market fit, a critical step at the early stage. So, in larger organizations, shouldn't the single most important innovation hurdle be understanding as much as possible about an idea’s product-market fit? If no one responds to your product idea, why move forward?
Heat-testing is a method for quick-testing product concepts to assess product-market fit. It uses advertising as a market research medium to measure interest in and demand for new ideas by target audience. (You can read more about Spark No. 9’s heat-testing methodology in the Harvard Business Review.)
Heat-testing has a number of advantages in innovation winnowing processes:
1. Brings concepts to life. Concept descriptions can be a little, um, thin. Visualizing new products shows differences in how people define a concept. Product mocks, ads, and landing pages put strategic meat on the bones of a theoretical concept.
2. Assesses ideas in parallel. Heat-testing tests hypotheses about a product’s appeal, including how it’s positioned and to whom. A single heat-testing exercise can test many product ideas in parallel to get an apples-to-apples read on customer demand.
3. Generates behavioral data. Heat-testing uses real, live ad campaigns. If someone clicks on an ad, that’s data. If they leave an email address to learn more on a landing page, that’s data. It’s a far better way to validate interest (or lack thereof) than a survey or focus group, because it removes the bias almost always present in traditional market research.
4. Delivers learnings quickly. Heat-testing usually delivers initial insights within a few weeks.
5. Cuts through politics. Too many great ideas perish at the altar of gut feel. There’s nothing like an empirical approach to cut to the chase.
6. Is affordable. Running ad campaigns to test a new product idea costs a lot less than building an MVP.
So tell your innovator friends: heat-testing is a much better way to identify potential winners in a collection of ideas than whatever they are doing now. Instead of focusing on a couple of ideas, why not test a dozen and prioritize the pipeline based on data, not opinion?
Want to learn how to heat-test? Check out Spark’s new bootcamp.