When we started EIP, we were pretty confident that deep consumer research done by independent 3rd parties would go a long way towards accelerating and enabling great license deals. The idea was that in the absence of data (fact), opinion rules and the incumbent's opinion is always more important than yours. Ergo, unless we got lucky and found a kindred opinion, we were DOA. So, the strategy was to create data to overcome opinion and grease the wheels of a transaction -- in the presence of data, one's willingness to extrapolate from opinion is superceded by facts.
The jury remains out on the effect of 3rd party research data on our deals -- there is no question we've gotten many more meetings as a result of our data than we would have gotten without data; however, it's not yet clear if research data sufficiently overcomes inertia to accelerate decision-making (several companies have either concluded they disagree with the data (which cracks us up when they have no conflicting data, just their opinion) or they've decided to re-test anyway).
So we recently decided to do an experiment. One of our projects is a product that was taken to market in a small community last year. Sales were disappointing, but the product works and is highly innovative. Our analysis was that the sales numbers were a result of the classic startup problem -- due to lack of capital, there was no advertising/marketing and only minimal distribution. All the effort goes into sourcing and packaging the product, and no money/effort is really expended on awareness and distribution.
As a result, we've decided to try a different approach to acquiring data. Rather than doing a research experience using a concept test and asking consumers whether they'd buy the product, we're going to spend north of $30k creating and running television ads on the local cable system. We're buying ads across some 10 cable networks, aimed at our target demo, and running for roughly 6 weeks (over 1000 spots in all). This should drive awareness up to the 50%-60% range we use for volumetric forecasting. Furthermore, we're going to push very hard on expanding distribution to see if we can get up to the 50%-60% distribution that we also use in our modeling (last year the product was not in Food, Drug and Mass stores -- so they're our key target). The experiment is essentially a test market -- simulating awareness and distribution and seeing how high we can drive sales volume. We'll also get some good insights on customer satisfaction and repurchase intent.
After a 3-month test, we'll know if we have a winner or a dud. Assuming we have a winner in terms of sales, we're going to see how different the response is from the target licensees when they see real sales data vs. forecasted sales data.
It's been a blast so far and I'll keep you posted!