Was it the number seven by any chance?
Probably not, but it was the best I could do. According to a stack of earlier experiments, seven is the most picked number, with just over 20 per cent of selections, so, as I said, I did as well as I could under the circumstances. But that still means that of the 130,000 people that read this column, only about 28,000 were pleasantly surprised in paragraph two.
If I was going to get a better result, I would need more information. I would need to know each reader individually and what number they plumped for every time someone had previously asked them to pick a number.
Clearly, I am not a party to that kind of information so I will settle for my one-in-five success ratio. More organisations, however, are moving beyond those odds and playing the guessing game with increasing degrees of certainty. They have the repeat interactions, the big data skills and the customer relationship management granularity to identify individual customers. All that enables them to enter a zone of market orientation few firms ever dreamed possible – prediction.
Take the American company Target. Over the past decade, a team at the Minneapolis-based retailer’s headquarters has combed through literally billions of transactions and millions of individual customer records in order to achieve one of the most vital acts of market segmentation – identifying pregnant women. Of all the potential segments a marketer can chase, a pregnant woman (and the man that usually comes with her) is a veritable Aladdin’s Cave of new purchases and price insensitivity. Little wonder, then, that thousands of brands battle it out over new mothers every year. But Target went one stage further and used purchase data, demographic information and complex analytical tools to predict who was pregnant before they had given birth and, on occasion, before the woman in question herself knew she was expecting.
You have probably experienced something similar if you run Google on your mobile phone. Those cards it throws up at the bottom of the screen are another example of predictive modelling. Google has access to your texts, emails and calendar. Thanks to the GPS on your phone it also knows where you are. Google’s Now software adds it all up and then suggests useful information like how far from the airport you are or the fact that your next meeting will start slightly later because your colleague will be delayed on the M6.
Tesco is up to it too. For several years, the supermarket giant has used a combination of climate data and scanner data from its UK network of stores to predict shopper behaviour and change its supply orders. If the weather data predicts a warmer than expected first week of September, Tesco orders more cordial and crisps to the Wigan store because its data shows a spike in demand for them when the temperature rises at that time of year.
The latest predictive genius is Amazon. One of the few strategic disadvantages it faces versus high street rivals is the frustrating delay between purchase and product arrival. Not surprisingly, Amazon has heavily invested in its supply chain to reduce this wait time exponentially. But now the Seattle-based company has gone one better and filed a patent for what it is calling ‘anticipatory shipping’. Using previous orders and past product searches, Amazon is apparently capable of guessing not only what you are interested in and whether you will buy it but also specifically when you will place the order. That knowledge allows Amazon to ‘pre-ship’ the product to a nearby depot so that it is effectively waiting for you before you even click on the purchase button or work out you need it in the first place. Right now in a depot in Slough there is an inflatable sex toy with your name on it waiting for you to realise you need it. And Amazon knows that on Tuesday, the moment will come.
This is probably all too much for many of you. Most British companies don’t even know who bought their products last year let alone who will buy them in the future. Market orientation for most companies in my experience is non-existent.
For the select few, however, it means not only knowing the consumer’s mind but knowing it better than they do. That’s one hell of a competitive advantage.
But you already knew I was going to say that. Right?