Researching the unresearchable: consumer research in predicting success of new tech products
As a market research group that conducts a lot of research in the new emerging technologies space, we often get asked about our view on the fact that Steve Jobs famously ‘didn’t believe in market research’. As stated in his biography, Steve Jobs by Walter Isaacson, Jobs has been quoted as stating: “People don’t know what they want until you show it to them. That’s why I never rely on market research.”
The interesting point here is that most market researchers would, on the whole, agree with him. Consumers often can’t articulate what they want, but they can respond passionately (positively or negatively) to a proposition put in front of them. They will embrace ideas or products that ultimately will make their lives easier, or better, or save them time, or save them money… and Steve Jobs knew this.
Every decent market researcher knows you should never start a research study by asking consumers what they want. Various approaches should be used to explore how consumers are living their lives, interacting with technology and other products and interacting with others in society. This observation, exploration and analysis is used to develop an understanding of consumer pain points and joy points in order to identify the opportunities available for new innovations.
Similarly, when it comes to researching any ideas or propositions that have been developed, it is essential that the new technology is articulated in consumer-friendly language otherwise consumers can’t relate that technology to their current lives. While consumers may struggle to understand the particulars of the technology, the approach we take in researching new technologies is to focus on ensuring consumers understand the end-benefit. How will the new technology better meet their needs than what is currently available?
In researching innovative technologies, common pitfalls are at polar ends of the spectrum, that is, either providing consumers with too much education as part of the research stimuli, causing confusion, or not providing enough education, particularly in focusing too much on the platform and not its execution.
The goal of stimuli should be to get individuals to the level of education they will have at the time of purchase. This stimuli can include multimedia if that best explains the applications and benefits. And it often incorporates ‘future state conditioning’. That is, describing the scenario as a future state and putting consumers into this context – how they would use the innovation and the benefit of the innovation at some fixed point in the future.
There are other important principles to keep in mind, based on our extensive research and database of tests conducted over the last 25 years:
- Trends that are starting to pass their peak test well, but don’t necessarily perform in market well, due to high levels of familiarity. When I say ‘test well’ I mean against the usual simple purchase intent type scoring mechanisms,
- incremental line extensions test well, but don’t necessarily perform well in market – once again, familiar consumer territory, and
- products a little ahead of their time often do well in market, but don’t test well (on straight purchase intent).
Therefore go/no go decisions on whether to progress the innovation should not be as simplistic as thresholds of ‘top two box’ (definitely would buy/probably would buy) purchase interest, as can be best illustrated by an example of R&D work we undertook (below). The results make no sense and bear no relationship to what happened in the real world. The things that scored highest were a little smaller and a little faster to come and go.
We consistently see this for Purchase Intent, Interest Ratings, Rankings of Idea and comparison to controls which means that the most commonly used ways to prioritise ideas in research are flawed.
Our 25 years of experience researching technology innovations means we have seen it all. We’ve seen breakthrough ‘headed for the moon’ successes and terrible ‘never stood a chance’ failures. But most innovations lie somewhere in between. Most are products that have every chance at success in market if you understand what type of innovation it is (broad appeal versus niche, breakthrough, premium, unconvincing etc.) and, therefore, how best to guide it to market.
So, back to Steve Jobs. His approach was to show people what he believed he knew they wanted, and get their reactions, which is exactly what good research should do.