My last post on Volunteered Personal Information only told half the story. It focused on the information individuals could actively volunteer, if they wanted to. The other half is the information we generate automatically, whether we like it or not.
Back in the industrial age, the customer was a stranger. The classic situation went as follows. An anonymous entity (you don’t know their name or address) walks into a shop, buys a product using an anonymising payment mechanism (cash), and walks out again. No information captured. Who this person was, why they did it, what else they did, all remained a mystery. The best you could do to gain any understanding was via statistical sample-based research.
Then, in the late 20th century, a new data gathering revolution began. It’s summed up by the barcode, which captured and crystallised information at the check-out – information that had previously evaporated as soon as it was generated. Then, some bright spark came up with the brilliant idea of connecting name and address information to shopping basket information (retail loyalty cards) and Hey Presto! the customer was no longer a stranger. You knew him and her, and you could talk to them using information you had about their activities and transactions.
For decades, this behavioural and transaction data has been the holy grail of marketing, especially direct marketing. It acts a bit like the silver trail left behind by slugs. Using it, you can track where they have been and what they’ve been up to.
Back then, customer slug trails were new and rare. But as the digital age progressed, they proliferated massively.
Your mobile phone generates its own slug trail: which numbers you called, when, for how long, and now with GPS where you were at the time. Payment mechanisms have become slug trail generators too: how much you spent, with whom, when and where.
Internet service providers know the slug trail of the web sites you visit. Digital media companies can track what you watch, when. Companies analyse the slug trails of the people who visit their web sites for the purposes of behavioural analytics. Wherever we look, new slug trails are being generated, and they’re getting richer and more detailed by the day.
At first glance, this seems to be the precise opposite of everything I’ve been talking about in terms of VPI. Far from being voluntary it’s involuntary, captured whether the customer likes it or not. And the data rests on the organisation’s side, not the individual’s.
But here we are reaching what a physicist would call a phase change, when ‘more of the same’ strangely ends up producing something entirely new and different – just as with more heat water turns into steam, or with more cold it turns into ice.
So what’s the phase change I’m talking about here?
The industrial age generated its own unique attitude towards personal data: that it is just another ‘resource’ like the fish in the sea. If you can catch it, it’s yours to do what you like with. Organisations undertook ‘data gathering’ exercises and customers have little or no control over how the resulting personal data is used. Often lots of personal data was collected, and sold, behind individuals’ backs, without their permission or knowledge. List broking, for example.
This was never a satisfactory arrangement. It generated deep concerns about privacy, which often resulted in legislation which cramped the marketer’s style – and which never really challenged the underlying attitude: that customer data is the organisation’s, not the customer’s. Organisations’ personal data gathering abilities have grown way beyond what most consumers realise – there’s a significant time lag here – but nevertheless, slowly and inexorably people’s awareness of database marketers’ slug trail feeding frenzy is growing. And with it, a new attitude is coalescing: “Hey! This is my data, not yours. Hands off!”.
Take Phorm as an example. Brilliant technology, but passed-its-sell-by-date mindset, embodying the old industrial age attitude towards personal data: basically, a strategy of furtive stalking that is brilliant at doing one thing – undermining trust.
In fact, looking back in retrospect, the industrial age approach was akin to walking up to somebody and slapping them in the face in terms of their privacy and respect for their personal data, and then turning round to them and saying “By the way, I know your name and address and lots more about you, and I want you to love me, be loyal to me and become my advocate.” Not the best way of building a relationship.
So here’s the thing. The richer and more ubiquitous slug trails become, what should have turned into the database marketer’s dream come true is steadily turning into a nightmare instead: an increasingly acrimonious and adversarial battleground over privacy.
The ideal, of course, would be to bring all those slug trails together: the mobile phone slug trail with the payment card slug trail with the internet surfing slug trail with the transaction data slug trail to create a complete, rounded view of the customer. There’s only three problems with this dream, however.
1) It’s almost certainly illegal (in the UK anyway)
2) Its Big Brother connotations are truly scary: a recipe for adversarial confrontation over privacy for years to come.
3) Even if it were possible to merge these slug trails together in one super God-like customer database, it would still end up with disappointing results, mainly because of all the bits of data it still doesn’t reach: such as what I plan to do next, why, and the context of all the other things that are happening in my life – the different types of VPI I talked about in my previous post.
What’s the upshot of all this? That slowly, surely, inexorably it will become accepted – it is already becoming accepted – that the digital slug trail generated by customers in their day-to-day activities is not the organisation’s, it is the customer’s. It is collected by the organisation with the customer’s permission, and increasingly, can only be used for purposes agreed by the customer. The ‘carrot’ bit of this is that if the organisation demonstrates its respect for the customer’s privacy, the customer may add other bits of volunteered data that were previously unavailable to the organisation, such as ‘my future purchasing plans’, or ‘my reasons why’. (If it plays fast and loose, however, it will be excluded from the new data-sharing ecosystem.)
In this way and perhaps counter-intuitively, behavioural and transaction data is on its way to becoming the second pillar of VPI.
Alan Mitchell www.ctrl-shift.co.uk