Big Data is a subject we have explored often on this blog because it’s an area where IBA has extensive experience and knowledge, but it is often difficult to explain. How big does a database need to be before it can be considered ‘Big Data’ and why do we need this separate terminology to refer to manipulating and analysing this data when relational databases have been in use for decades?
One example that goes a long way to answering these questions is the way that customer service is changing – especially for retailers. Products used to have a phone number and email address that customers could use to reach the manufacturer or retailer – usually to complain after a purchase.
Now, customers use online forums, review sites, Twitter, Facebook as well as the more traditional and direct channels such as online chat, emails, or a voice call. Customers are not always directly contacting a brand when they comment on a product, yet they usually expect a response.
Exploring this mass of information is a classic Big Data example. The retailers want to connect together all these communication channels into an ‘omnichannel’, yet this is impossible when they are considered to be regular databases.
If a customer emails a complaint, then tweets about the problem because their email is not answered and then finally calls because neither tweet nor email has been answered then the ideal situation for a retailer is that the agent on the phone knows about the earlier email and tweet.
But to make this work is not easy. The company has no control over Facebook or Twitter – it’s not internal data. And how can comments on a tweet be connected to a customer on the telephone?
All this is feasible, if you have enough information from various sources and you can analyse it quickly enough. Every company that interacts with their customers is now exploring this problem so maybe Big Data is about to hit the headlines again.