The ‘big data’ revolution

In essence, big data is just another fancy term for managing your customer information, which is something that the vast majority of brokers want to do – but either don’t do, or do very poorly.

Everyone says that big data is the answer to you making more money from your existing client base. Well, in theory, this is completely true, but I’m often asked, “Do you need a big client base in order to take advantage of big data?” The answer is a resounding no. One of the most exciting areas for big data lies in the potential to create new income streams, and by analysing the information you can build an insight into customer intelligence and behaviours that you should be able to monetise very easily.

The vast majority of brokers don’t care about big data analytics and using its outcomes. The vast majority of brokers already know almost all of their clients’ information and know how and when they are going to be conducting their mortgage-related activities, so they see no value in buying into the big data movement – yet the vast majority of brokers want to keep their customers for life. How many transactions are the vast majority of brokers going to get from that lifelong customer? At best a mortgage refinance every four years, which is a long time between transactions.

Now consider how you can use your data to participate in another industry movement – the diversification of your services into other products. Again, the vast majority of brokers want to do it, but either don’t, or do it poorly. Without knowing more about your customers’ needs and behaviours, you can’t begin to develop any form of diversification strategy that takes advantage of your client data. Whether you have 100 or 1,000 customers, the exact same principals of data mining apply.

Here’s a simple exercise for any broker to undertake on an existing database to determine whether it’s worthwhile experimenting with big data: go through all your records and find how many clients have listed other debts at the time of their mortgage application. You should find that one in three clients have a car or personal loan. Now look at the age and size of each of those loans and ask yourself, “Should I call my client and offer to assist them in managing these debts?” How easy is it now to use this data to engage your clients again and talk debt consolidation into their current mortgage (the one you did for them) or offer to refinance for a cheaper car loan?

If you hadn’t used big data, then you could not have diversified into selling more. Are you seeing the correlation between these two movements? Big data and diversification equals more money in brokers’ pockets.