A recent article in Research Live highlighted the re-branding of WPP's Insights Division from "Consumer Insights Division" to "Data Investment Management". CEO Sir Martin Sorrell explained the move as a way to bring the Insights and Media divisions closer toghether, thereby making it easier for Clients to manage and synthesize various data streams.
Makes sense – but why re-brand, removing the word "Insights" completely, with the new entity sounding more like a financial services offering?
Has Insights as a concept passed its zenith? Are we in a world of "data" where the hot topics of data-mining, predictive analytics and synthesis tools will dominate?
I hope not, but if WPP is doing things, we need to take note. Here's my take.
1. "Insights" Still Needs to Earn The Right to that Name
How many Researchers have really made the leap to a value-added, action-oriented professional?
A recent Linked In discussion suggested that the switch from "MR" to "Insights" was little more than a change in name, with no significant change in MR practices, no gear shift in heightened impact. This was from someone who had spent many years in a senior Insights role at a major fmcg company.
If Researchers are often still data-deliverers, re-branding Insights as "data investment" won't help much. Data Synthesis requires a higher level of consultancy skills and business understanding.
2. Analytics is a Sub-Segment of Insights, not Vice-Versa
Primary Market Research is on a polarised trajectory, with two clear growth trends.
One is disruption-driven – more research conducted across the organisation and expanding to new industries that previously couldn't afford research, using low-cost DIY tools, possibly in combination with in-house databases.
The other is the rise of more sophisticated techniques – biometrics, implicit questioning, techniques shaped by Neuro-Marketing and fuelled by Behavioural Economics – aimed to capture more accurately emotional/intuitive as well as rational response, often on a longitudinal basis as with MROCs.
Alongside these is "Analytics" – utilising data-mining tools to interrogate existing data to answer business issues.
Analytics is clearly hot at the moment; no doubt there will be an increasing number of well documented case studies over time about how this improves business efficiency and decision making. Many companies are currently in proof of concept mode, figuring out the ROI equation.
However, the most powerful insights are invariably simple ones. They don't require a major consultancy to identify them through a sophisticated algorithm. They sit just below or actually on the surface, but can (and do) get overlooked for various reasons – myopia, cultural bias, political pressures. Talking to employees will often give a good basic understanding of what both the challenges and likely solutions are to any given Company's problems.
Insights' task is to help ensure these simple but powerful consumer or employee-driven "facts" to be acted on – they're the ones that are likely to have the most impact.
Analytics can co-exist with Insights, become part of Insights toolkit perhaps – but Insights is the discipline that needs to ensure the right questions are asked rather than engaging on endless data-crunching with little real business impact.
3. Algorithms have Way To Go
Vision Critical's Ray Poynter recently pointed out some weaknesses in Big Data's (BD) ability to deliver – http://bit.ly/1810vLF - including the lack of people with BD skill sets, masses of meaningless noise as opposed to real nuggets (signals), no accepted models about how to treat BD.
Jannie Hofmeyer of Research giant TNS, on the other hand, warned recently at the MRMW 2013 Mobile Conference in London of the dangers of underestimating the power of machine intelligence when coupled with human expertise.
Both of them were touching on different aspects of the same theme: the ability of machines to replace humans. It's a core issue for Market Research – what will require our human skill sets in future, and what can machines simply do better?
My personal experience is that algorithms have way to go, as does machine intelligence.
I recently took a year's subscription to a high profile UK magazine. The "welcome" letter had clearly been written by a machine, even though it was apparently from a human. It was addressed to me, but then referred to me in the letter as if I was a third person. Plus – the singular slipped to the pural. I quote: "Dear Mr. Appleton … I can confirm that their subscriber number is …"
Hallo? Welcome? To what planet?
To continue my anecdotal evidence: my Facebook timeline has recently got peppered with very poorly targetted ads, from categories I have zero interest in. Amazon – surely a Big Data expert – often suggests I buy another CD from an artist I just bought one from. Duh. Cross-selling? It certainly has the potential to make me cross….
Overall, I see Market Research being sucked up into a fascination with numbers, predictive power, machine learning, quantified cities and the self to name just a few. Digital technology is driving change, and fascinating us in equal measure. Is this actually making us better problem solvers? Or are we simply getting side-tracked by a – predominantly male – fascination for technology, gadgets, machines?
My belief is that the closer we get to the microscopic, the contextual, the qualitative the better – regardless of where VC money is going in the Market Research world. We understand first hand what's really going in, in all its complexity.
Putting a percentage sign behind something doesn't make it either right or particularly useful.
Curious, as ever, as to others' views.