I saw an excellent programme on TV last night: The History of Now. It’s a series about 2000-2009, and it helped me to put my finger on things that had been vaguely lurking in my head.
One of the things it mentioned was Mosaic – the postcode-based classifcation of people so that shops and, more recently, politicans can target particular things to particular people. It divides society up into 16 or so categories, and then says what category is most common in each postcode.
It made me think of a book I’m reading for work: Competing on Analytics. It has all kinds of interesting and scary things about how companies are storing information about customers and their behaviour, and then using this behaviour to make more money. Things like store loyalty cards, online accounts, using search engines and so on.
Apparently the industry average rate for people actually using money-off coupons is about 2%. Tesco can use its vast knowledge of its customers to tailor its coupons so that they are more relevant, and so get 20-50%. (So people buy e.g. cat food in Tesco rather than anywhere else.) It issues about 7 million targetted variations of product coupons a year, and has given away Clubcard points worth about £1 billion pounds. (Don’t feel sorry for Tesco, the points keep you with them rather than going elsewhere.)
It’s taken a while for me to realise what makes the weird feeling in all this, and I think it’s two main things (there might be more, but these are it for now). The first is that Tesco etc. know so much about me from a distance i.e. without properly knowing me. In the past, in the days before people left such a rich digital trail in their wake, to do this sort of thing you’d need to go through the rubbish in someone’s bins, tap their phones, intercept their post etc. In short, you’d be spying on them. We (at least, people my age or older) haven’t adjusted our social expectations to move this kind of knowledge gathering into the Acceptable category.
The second thing that’s behind the weird feeling is the imbalance in the relationship. You know so much about me, but I know so little about you. In fact, I don’t even know which “you” I’m dealing with much of the time – I see the shop workers, but the marketing departments, IT operations departments and other backroom boys and girls who shepherd all this data are people I will never meet. Just as a thought experiment, I imagined what it would be like if when I hand over my clubcard in Tesco (and give them yet more data) I got a little book with details of all the Tesco staff who will touch my data – their names, addresses, a photo maybe, what they typically buy in Tesco etc. ‘Cos that’s what I’m giving them.
While this rant has built up a head of steam, I’ll grumble about a particularly unpleasant version of all this. On Facebook there are occasionally adverts that say “Aged X-Y?” where X and Y just happen to bracket my age, or even “Are you a man aged X?” where X is exactly my age. I’m fairly sure that Facebook gives its advertisers that information about me i.e. the advertisers know exactly my age and sex, so they could just as easily say “Seeing as you’re a man aged X…” Putting it as a question makes it look like they just happen to have an offer on at the moment that just happens to suit me (according to them) and so I would be foolish to let such a brilliant offer pass me by. At least Tesco are honest about their omniscience (although they don’t go out of their way to help people realise quite how much data they have). While I’m in the area, there’s an interesting blog about someone trying to get Tesco to show him what they hold about him.
Of course, in some ways, there’s a choice in all this. We choose to exchange this information in return for convenience and, possibly, lower prices. Although the choice is more and more being made for us. In order to leave no digital trail you’d have to work really quite hard – as films like Terminator 3 and The Bourne Identity (and many others) show.
What provoked a wry smile is the following passage of the Competing on Analytics book. Bear in mind it was written in 2007:
Of course, any quantitative analysis relies upon a series of assumptions. When the conditions behind the assumptions no longer apply, the analyses should no longer be employed. For example, Capital One [an example in the book of a company succeeding through analytics] and other credit card companies make analytical predictions about customers’ willingness to repay their balances under conditions of general economic prosperity. If the economy took a sharp downturn, the predictions would no longer apply, and it would be dangerous to continue using them.