The Future of Research & Where We go From Here…

Steve King (CEO Black Swan Data) recently wrote an excellent piece in Forbes covering the new wave of tech-driven vs tech-enabled digital market research firms. Having spent time working at Black Swan and Streetbees, it made me think about the future (with my client hat on) and where we go from here. (link in the comments).

Undoubtedly the advantages of using behavioural data (what people do) vs claimed (what they say they will do) at scale marks a big step forward in certain research use cases. Digital crumbs leave clues around what people may do next.

Experienced researchers and strategists however know only too well that relying on a single source of the truth carries inherent biases and risks for making future bets.


Firstly, representation and diversity. These are perhaps two of the market research industry’s hottest topics at the moment and rightly so.

Ray Poynter‘s recent observation (ONS data quoted by The Guardian) that cites just 26% of people have been working from home is a great example of the perils of relying on a single (in this case media) narrative or source. Focusing on sub-groups of sub-groups of the population, no matter how good the analytics is, is akin to analysing an echo chamber.

Secondly, the world of consumer behaviour and culture is wonderfully diverse, messy and contradictory.

Consumers tell us their intentions in one place, and yet their subsequent behaviour, captured by another, often contradicts it. Context and emotion explain a lot of this discrepancy, but the mismatch is a challenge in building brand, marketing and channel strategies. What do you trust (as signal), and what do you ignore (as noise)?

Better, faster, cheaper has been the go-to phrase for the research industry for the last decade, largely driven by messaging from the tech-enabled propositions. Tech-driven methods are a clear step up, but to truly nail the “better” part, triangulation of multiple data sources, in my opinion, will be key.

In some ways it’s the difference between general (science-fiction) and narrow (almost all in use today) AI. Analytics and analysis of research data from one “pool” should be triangulated by a skilled researcher with others that complement it: e.g. internal data, raw ethnographic, and, where appropriate, qual. In the same way that equity analysts analyse companies from a range of data perspectives, so should we, the researchers and strategists, with people.

Brilliant researchers and research minds have never been more in demand. Humans (researchers!) are conscious, sentient and driven by emotion, narrow AI is not. Curiosity about culture and the need for creativity, experimentation and the blending of multiple sources, to help clients win, to me demonstrates just how important we (researchers) are and will continue to be.

What an exciting road ahead!

Mat Sloan

Head, Brand:lab