Or how data based on behaviour delivers better customer experience than data based on what customers tell you
Versions of this have appeared via Zone's weekly Digital Distractions email and the The Wall blog
“If I had asked people what they wanted, they would have said faster horses’’ Henry Ford (allegedly)
History is littered with examples of how actually talking to customers about what they want has resulted in shall we say less than productive outcomes for organisations. Malcolm Gladwell’s book Blink cites numerous and entertaining examples of how consumer research lets us down.
This boils down to many factors and in fact doesn’t mean we shouldn’t listen to customers, but try to understand the context in which they are making those decisions or providing us with that information. I wonder how many restaurants collect information from customers signing up for discounts who tell them that Aberdeen, Aberaeron, Abingdon or Acton is there favourite restaurant; how many retailers see people who register for an account who have their birthday on January 1st; or market research companies have questionnaires completed by individuals who claim their annual income is one range higher than it actually is.
You could argue that all data is made equal, but some more equal than others.
In general I have a rule of thumb that Demographic data is less reliable than Profile data is less reliable than Behavioural data is less reliable than Transactional data.
Demographic data – Does my postcode really flag me as being similar to my neighbour
Profile Data – Even if accurate when I gave it to you, that was 12 months ago
Behavioural Data – Yes, I told you I was interested in Politics but the funny pages online are so damn appealing. Anecdotally I’ve heard that Film Four audiences in research groups told them they should be running French art house films and it turns out everyone just tuned into Dumb and Dumber 2
Transactional Data – Ok, so now I’ve put my money where my mouse is
But of course context is important and that can often be the most important factor that needs to be considered. Amazon were great at suggesting products similar to the cake boxes we recently bought for our daughters christening. But to be then bombarded with emails and given amazon.com recommendations all about cake boxes and related products doesn’t really work when I’d rather be getting recommendations based on the constant stream of comedy DVDs and CDs I’ve bought over the last few years and watch on Amazon Prime.
It’s confusing isn’t it. And that’s before we start talking about how customer behaviour might give us a clue to future spend. I hear that Homebase can predict that a major home project is on the cards based on your purchase of a random packet of bird seeds when in one of their stores.
All of this data can be useful, but perhaps it’s the changes in a customers behaviour or transactions that matter the most. I may be constantly engaged with your content and with your products but what does it mean when I start to show a decline in watching your TV programmes or eating your pizzas?. Is that an indication of future churn?
Conversely what happens over a period of time if I become even more engaged with your content? Is that the real time to deliver a member get member offer rather than just running it to everyone who currently has an engagement score of 8. It’s the rapid movement from a score of 5 to 8 that might offer more insight
Stringing together data and the customer journey both off and online can be a powerful tool but a journey that can be quite heroic . Don’t believe me? Check out this ad by software company Thunderhead