Effectiveness, ROI, metrics… are you doing the maths?
As any marketer worth their salt knows, your marketing is only as effective as your understanding of your audience.
Back in the early Madison Avenue days, this understanding was mainly based on gut feeling and anecdotal observation. Type of person X is likely to buy type of product Y. Message A will appeal to audience B.
Whether it was creative gut instinct or an instinct as to where and when to buy media, it was the human brain making connections based on observed information over a lifetime of experience. It required intelligent, well-read, well-travelled people who understood high and low culture and everything in between. (I think it still does!)
Then came the science – and the marketing industry has been grappling with that science ever since. Effectiveness and ROI (return on investment) is the holy grail, and we measure the living hell out of everything we do to ensure we’re getting the absolute best bang for our marketing buck – and that our marketing is ‘working’.
So, quantitative and qualitative measures were brought into play. Surveys. Focus groups. Net promoter scores. Readership and ratings figures. And of course latterly, with the proliferation of access to the internet, all of the available web metrics and their manifold meanings and the inferences we make from them.
Access to the internet, all of the available web metrics and their manifold meanings and the inferences we make from them.
Trouble is, we’re still not very good at saying exactly what effect pulling one marketing lever (say, getting people to read a branded lifestyle article online) will have on another down the line (say, propensity to purchase a product). Sure, we can hypothesise and we can put together fancy equations, but it’s hard to be sure – because there are so many steps to audience ‘journeys’ nowadays, and so many possible variations of that journey.
Which is where two great hopes of the marketing world come in.
Big data is pretty simple, despite all the hogwash surrounding it. It simply means holding enough data on your audience that you can make deep chains of connections between events and behaviour.
Of course, having lots of data is the starting point. Having a framework that allows you to utilize it is something completely different. And really big data is not just about single databases – it’s about sharing and overlaying lots of databases into a single, massive infrastructure of consumer data.
In terms of promotion, big data should mean that not only do I get targeted banner ads when my browser notices that I’ve looked at a new TV online recently, but that it stops showing them to me when I purchase a TV. It should mean geo-location targeted messages, so if I walk into a General Pants store and approach the shirt section I get a push message from the Top Man app on my smartphone with shirt offers.
Big data will also have a huge effect on the ‘Product’ bit of the four Ps of marketing. I recently wrote on this blog about personal data – the phenomenon of individuals starting to measure all kinds of data on themselves.
Imagine if everyone in the population measured exactly the amount of exercise that they took, every day, and exactly what they ate every day – and they couldn’t cheat. Now imagine that an insurance company could access all of that data – but also cross check it against medical databases – family and personal medical history for example. An insurance outfit could, at any given moment, predict your chances of becoming ill – which could lead to premiums being changed on a monthly or six-monthly basis as your behaviour changes.
And back to one of the other Ps, promotion: If Nike knows how many miles you’ve run in the last month, it surely should be able to tell you when you need a new pair of running shoes, right?
So – in a nutshell, big data should enable brands to both react to and predict consumer behaviour. Cool, huh?
All this talk of predicting behaviour brings us nicely on to neuroscience and its sibling, neuromarketing. Neuromarketing is still in its infancy. Whilst firms like NeuroFocus use electrodes (EEG) and magnetic scanners (fMRI), prompting hysterical headlines about ad men and brain scanners, many academics like Dr David Stillwell are skeptical of the real learnings they deliver.
In this article, Stillwell rubbishes EEG – the familiar electrode covered cap – as ineffective and inaccurate. He has more time for fMRI – using the MRI machine familiar to anyone who has ever seen an episode of House. Apparently, using MRI, his team have worked out that people who prefer Nike to Adidas have a higher IQ and are more inclined to working alone. PSYCHO ALERT! STAY AWAY FROM THE NIKE WEARERS!
In all seriousness, whilst we’ve not yet perfected the art of measuring people’s reactions to advertising stimuli, we have been able to gather neural data enabling us to make certain behavioural predictions – but they are still pretty basic. (Having said all that, apparently it IS possible to spot a murderer’s brain in a line-up.)
I’ve probably set up a bit of a false dichotomy here. Neuromarketing is so much in its infancy at present that it’s not really capable of providing us with the kind of insights that can really change the game, and in reality it just generates more data. And that data, if added to the massive data infrastructure that I fantasized about earlier, could contribute to our ability to communicate more effectively and cheaply with audiences.
I’m just not sure that any of it really beats good old gut feel.
View the discussion thread.
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