Turning Customer Data into Currency
According to InformationWeek, “90% of respondents use conventional databases as the primary means of handling data.” The data that companies are amassing today, however, is complex, diverse and continually growing, and they struggle to manage it effectively. Many lack the right expertise and tools to fully exploit the mass of data they are collecting. Collecting data then is only the beginning; what businesses do or don’t do with big data is critical to their revenue streams.
But it’s good to clarify two points about big data. First: 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. To that original definition, we add a fourth “V” – veracity (having trust in the information at hand).
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 website downloads.
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.
In order then for businesses to convert big data into currency, they cannot stop at mining data merely for research and development or product management initiatives. Businesses must attempt to dig deeper into their data to extract the exact piece of customer-specific nuggets at the exact moment CFPs need it to create personalized customer experiences. This is where true currency conversion begins.