As companies in many industries get increasingly good at managing and extracting value from Big Data, consumers need to stay alert if they are going to get a good deal.
A recent personal experience when renewing my family’s multi-car insurance policy (three cars, four drivers) brought this home to me.
Many of us who are consumers of insurance in the UK have learnt from experience that whenever we get an annual renewal reminder, with the lure of “Here is your premium for next year, we are giving you a great deal, if you are happy we will update your payments, saving you so much hassle…”, then the smart thing to do is to phone them back to complain that the new premium is unreasonably high.
Incidentally, the people I politely complain to are invariably charming, which reinforces my view that it’s all a big game. I actually now look forward to these annual calls.
In each of the last five years I have always ended up with a substantial reduction which is more than worth the hassle of making the call. There probably is a price I would accept to avoid the hassle, but I am waiting for my insurer to figure that out. After all, they are the ones who have the big data! But maybe they find that me and my friends are unusual, with most customers the bias towards “no hassle” is much greater.
The new realisation for me in the last two years has been that, when I make the call to see if they will give me a reduction in their quote, I am in danger of being in an unbalanced negotiation. The imbalance is in the amount of data at our fingertips. The insurer has loads of data on my premium history, but has chosen to reveal little of that to me.
To be specific, with a multi-car policy, the insurer will share with me the total premium I paid last year across all my cars, but not the premium per individual car. The individual amounts don’t appear in the policy documents. Thus when it comes to renewal, they give me verbal but not written information on their quotes per individual car, and then can easily bamboozle me with factors such as an increase in car thefts near my address which are impacting the quote – without of course sharing the algorithm.
Realising this, I have taken to keeping a scrap of paper where I write down the quotes for each individual car that they tell me over the phone. With now three years of this “Little Data”, I have found that I am suddenly in a much more effective negotiating position. I can now come back to the insurer with searching questions about proposed increases on each car individually, which generally produce the happy answer of “Ah yes sir, I see what you mean, let me find a way to make a further reduction in your quote”. David versus Goliath it might not quite be, but it has certainly persuaded me about the big value in Little Data.