Returning to the question of forecasting: And just to be clear I'm not talking about a product upgrade or line extension. Not another detergent which you inject into the fabric of clothes for a really deep clean or a new high-energy bar including micro-particles extracted from clouds above the Baltic Sea. The rules on line extensions are pretty clear. And you usually have the package goods machinery to back you up: the concept tests and volumetric projections and prototype usability tests to go on.
But we all know the limited usefulness of concept testing something that doesn’t yet exist. Consumers are famously unable to predict their interest in something they haven’t seen before. I think the most useless focus group question in existence is: “Would you like that?” Sure, why not? Right? But that’s not the topic at hand.
The topic at hand is what do we do when we’ve got nothing: On the conceptual level, you can retreat to the trusty war-horses: “best cases” and arguing from analogy. You turn to Facebook or Wikipedia or reach further back to Amazon. But if you’re used to building conclusions from multiple data sources in specific categories it can feel very flaky indeed to fill up slides with borrowed data, especially when you are staring at a bunch of engineers or VC’s.
Another option is scenario-planning. That way, you don’t feel like you’re predicting exactly what will happen so much as detailing the consequences of a range of outcomes. It enables some conceptual framework and doesn’t feel like an all or nothing bet. Of course, even this involves some prediction. You still have imagine a range of outcomes. And as Societe Generale recently found it: it’s not always easy to imagine what can happen. Scenario planning is best on the big picture. But it’s less useful for helping define the details.
So far I’ve gotten the most traction by retreating to my comfort zone: consumer behavior. Any new product, no matter how advanced, has to be tapping into some existing consumer behavior, generally among early adopters. In the example in the previous post—real-time gastro-intestinal observation—it might be people with serious conditions or people who think they do. Or maybe it’s people with a thing for medical imagery.
In any case, the strategic question becomes how far out does a brand want to lead consumer behavior. The brand can build the consumer base by serving the core behavior of the early adopters and hope there is enough of them or their freaky intense involvement catches on. Or you can identify the mainstream behavior that is likely to see GI imagery has the logical next step in their personal journeys to perfect digestion. It might be Prevention subscribers it might be people with regularity issues.
In any case, they both have risks. If you bet on the early adopters, your position could quickly get marginalized by a fast follower with easier technology. The bet on mainstreaming is a big opportunity but might never come to pass. But in this scheme, you can turn to real consumer data and some attempt to size the market to guide your decision.