Monetizing Customer-Relevant Big Data

Continuing the “Big Data” discussion, I would like to touch on the area of monetizing customer-relevant big data.

Businesses of all sorts are accumulating data that does not easily lend itself to conventional database/data warehousing models. What they do and don’t do with this data can have a significant impact on their bottom-line business performance.

But it’s good to clarify two points about big data. First point: big data doesn’t just mean lots of data. According to the definition originally put forth by Gartner analyst Doug Laney in 2001, big data involves three attributes: volume, velocity (i.e. the speed at which it is accumulated and/or loses its freshness), and diversity of sources.

Second point: it’s not enough to simply “manage” your big data. You have to actively leverage it in a way that concretely impacts the performance of your business.

We can see from the first point that the customer-relevant data scattered across the typical enterprise today clearly fits the definition of big data—there’s a lot of it. Companies are relentlessly accumulating more of it with every customer interaction, every comment on Facebook, and every news story in every vertical market they service—which they need to know about and act upon sooner, rather than later. And customer-relevant data is definitely dispersed across an extremely diverse range of sources, ranging from Customer Relationship Management (CRM) databases to SharePoint documents.

From the second point, we can see that this data has to be instantly delivered where it will do the most good at any given moment. Sure, analytics and Business Intelligence (BI) can help companies make better long-term decisions about products and go-to-market strategies. But a lot of that work can be done using basic CRM and/or Enterprise Relationship Planning (ERP) data, and it can be done using conventional BI tools.

The real battle with the market takes place in the moment when a customer has a problem, challenge or need. And a Customer-Facing Professional (CFP) has to act or make a decision. This is also the biggest deficit at most companies. CFPs can’t find the information they need. Or they don’t even know that useful information exists. Or they don’t know that there is somebody in the company who knows more than anyone has ever put into any one document.

This is where customer-facing big data can have the greatest impact on business performance. It’s where you help the customer in a surprising way and it’s where you avoid making a big, stupid mistake. And, as a result, you retain your customers and increase your revenue from your existing accounts.

So when you think about monetizing big data, don’t make the mistake of just thinking about crunching lots of numbers to detect some trend that you might want your product management team to consider in their long-term roadmap. Think about getting the exact right piece of customer-relevant information to the right CFP at exactly the right time. That’s where the practical payoff is.