In the major motion picture “Field of Dreams”, the main character (Kevin Costner) hears a spooky voice telling him “Build it and they will come”, while he is taking care of his crops. After some persistence from the voice, Kevin Costner understands that he has to savage his fields to build a baseball diamond so that the legendary and deceased members of the Chicago Black Sox team can return and clear their tarnished reputation. Similarly, there are many persistent voices urging companies to take the plunge into the Big data hype now. The proponents argue that the slashed storage costs makes it possible to capture and analyze the explosion in data generated from more connected users and increased usage of social media and mobile devices. Even if it possible to store huge amounts of data that is beyond what we previously could imagine and manage, I will argue in this blog post that the big data will NOT generate new customers to the extent that it is worth sacrificing more traditional business intelligence approaches. Build it and they will come is a field of pipe dreams. The inside-out view that bigger amounts of data will generate better insights is flawed, especially considering the untapped potential to leverage existing data from customer channels to get a 360 degree view on the customer.
Peak of inflated expectations
Gartner has developed a model to describe the development of hypes, the hype cycle curve. The enormous buzz that we have seen on social media related to big data imply that we are getting closer to what Gartner calls the “peak of inflated expectations”. That is the turning point where some of the early adopters stumble into problems and understand that the benefits will not meet their expectations. The chart below presents how the interest in big data has skyrocket on Google lately. We have not seen the backlash yet, but it is evident that the expectations on big data are bullish and unbiased right now.
Let me be clear on that I do not argue against big data approaches. But I object to the inside-out approach where proponents say “let’s gather data, the more the better and see what insights we can get from it”. We have made those mistakes in the financial service sector before. The fact that some banks didn’t establish new data warehouses when their old ones were “hijacked” to ensure compliance to the Basel II-regulation indicate that the value of the old applications and reports were not worth the effort. I do not think that it will be easier to find the valuable “nuggets” merely by adding even more data.
Basic customer insight
Given the current compliance frenzy, it is not unlikely that the banks will be forced to make big data investments to prevent money laundering, stock price manipulation or tax evasion. But, I would recommend every bank to challenge big data investments that are based on top-line growth unless they have already picked the low hanging fruit. Please feel free to take the plunge into pool of data if you honestly can say that you have BI-solutions in place so that you can answer the following list with questions on basic customer insight:
- Do you know in what context the customer is contacting you/visiting your site? Is he/she considering buying a house, a car, etc…?
- What products/services have the customer shown interest in on your customer channels?
- Has the customer expressed that they are satisfied or dissatisfied with your services on social media?
- Given what you know about the customer, what is the next product to best cross-service the customer?
- Are there indications that the customer’s life situation and hence financial needs have changed?
- Can we offer information to customers on where their spending deviates from peers?
- What is the value of increased wallet share in price negotiations with a mortgage customer equipped with the latest quote from #sägdinränta ?
- What is our wallet share with our customers?
- What personas are we best at attracting and servicing? What is the potential to win new customers with the same profile? What is the potential in improving the service to less satisfied personas?
- What is the life time value of our customers?
- What campaigns have been the most successful? What was the conversion rate?
It is not an exhaustive list but I think that few, if any, financial institutions have the answers to all these questions. The good news is that most of you have all the data needed to answer these questions already. You do not need to capture all digital footprints of your customers to make the analysis. So, please, do not savage your crops and build big data diamonds in anticipation of new customers. They will not come in the real world.