Tesco famously has ‘segments of one’. Which is lovely of course – but they had to buy a data company just to make sense of the data so they could get there. Most of us don’t have that luxury. But it doesn’t mean we can or should ignore Big Data, even if it looks like it might become unwieldy.
Some brands haven’t yet realised that the power in a brand/customer relationship has shifted from the marketer to the marketee. Clearly however social media and the ability to share every thought, spoken or unspoken, with friends and peers and even the whole wide world means that the brand perception is out in the wild. It’s been let loose. No longer is the way your brand is represented in your control. It’s in the expressions of passion, ire, indifference and ephemerality of the digital ecosystem: Facebook, Pinterest, Snapchat, Twitter, Vine, even email. It’s transmitted by mobile, stored on the web, and available to the world.
Your job as a marketer is to understand that this revolution has already happened. And to take advantage of it. If you can do it successfully you can catch up with the wild thing your brand has become, and even gain competitive advantage while your peers wrestle with boards who just don’t get that they’re no longer in control.
So what do you need to do in order to flip the situation around? Well, part of the problem is the notion that we can regain control. I don’t think we can. What we can do however is map how consumers behave, and indeed how their attitudes will shape how they behave in the future. By going down this route rather than trying to gather the brand in, you can extend the brand into the customer’s territory, give them more control by enabling free interpretation of the brand’s essence. And that takes not only courage, but data too.
Customer insight is the product of data. The three dimensions of segmentation (what we call 3D Segmentation) are:
- Demographic – who the customer is;
- Behavioural – what they do and have done;
- Motivation – why they do it.
Demography is slow moving, so we use it as a kind of snapshot to describe people. It means we can target them accurately. Behaviour is retrospective, but we can observe behaviours and trends and make extrapolations based on probability and this gives us propensity models. This means we can target them efficiently. The final dimension is about motivations, attitudes and ‘need states’. Sports brand ASICS leverages this in its MyASICS loyalty programme: by understanding why a runner runs, we can talk to them in terms that resonate… the desire to be fitter, or to win, or to raise money for a cause. By talking to its customers about those things that address their motivation, ASICS creates extreme loyalty, increasing sales. Worldwide. And MyASICS is served by a website, and emails, and mobile. All of which feed back data so we can hone the programme.
These days the various digital channels are so well established that the mechanisms that allow you to track a customer in their journey in one can easily be joined with the mechanism in all the others. It means we can effectively create a joined-up process to track a customer across all digital channels as they weave about their daily lives. This ability extends even to the real world – we work with clients who have incorporated data from electronic point of sale (EPoS) systems into their customer view, so we can attribute till sales to pay per click (PPC) campaigns and journeys via every imaginable digital touch-point.
And it’s not that difficult, and you don’t need to buy a DunnHumby or a data team to do it. The concept of rapid prototyping has been very successfully applied to creating online customer labs and pilot programmes. For instance, brands like Bupa have used it incredibly effectively to build online communities at very low cost before making decisions about major investment (my agency, Underwired, created Bupa’s Carewell using this rapid prototyping approach – saving the client around £150,000).
Forget the Single Customer View and its squillions in Capital Expenditure; rope together several separate systems based only on those components you actually require to do the job of proving return on investment (ROI) and use it to monitor customer behaviour in response to the insights you generate from simple data analysis. In my experience six or seven segments gets the job done – segments of one are for when you’re already at the outer extremes of wringing profit from data and not when you’re mid-shift towards putting your customers at the centre of the brand universe.