Data is king, in case you happened to be sleeping under a rock for the last 12 months. The meteoric rise of Big Data and Data Analytics in the past year was both exhilarating and overwhelming. New technologies (mobile, social, digital, etc.) continue to transform the very world we live in. The power shift from corporations to consumers is nearly complete. The age of the customer, as Forrester defines it, is upon us.
There is no debate that capitalizing on the surplus of today’s business data can help a company drive sales, enhance customer satisfaction, and boost loyalty. How you “capitalize on that data” depends on whom you talk to.
What we’ve learned after talking to countless customers, reading in-depth analyst reports and closely studying the traditional data analytics process is that the current, de-facto data analytics process is inherently flawed. Does it work? Sure. But it takes inordinately long and is wildly expensive.
In order to make responsive business decisions, backed by fresh and accurate data, the process by which a company collects and uses said data must fundamentally change.
Today a customer’s interaction with a business will likely span multiple touch points. The more options a company gives the customer to interact with its business, the more likely they won’t miss out on potential business. Brick-and-mortar store. Website. Mobile application. Corporate phone number. Out of 100 customers, I’m certain each channel will be a preference for at least one customer. And that’s all it takes. One customer.
According to a 2013 McKinsey study, more than 50% of customer interactions happen during a multi-event, multi-channel journey. Some of the touch points within these journeys have existed for 20+ years and some are much newer. Paying your electric bill or transferring money from a mobile application was simply not an option 10 years ago today.
According to Forrester, customers will actively shun businesses that lack mobile applications designed to enrich their experiences. In most cases, these touch points are all built on completely different systems and don’t communicate very well together (if at all).
This untamed complexity, not all too uncommon (even in modern IT environments), is a formidable culprit when it comes to making sense of incoming data. It can require millions of dollars and years to decipher (the great irony being the intelligence is no longer timely or valid). Simply put, the traditional data analytics process makes it nearly impossible to get a real time picture of a customer’s behavior as they interact with the business.
So what’s the answer? How do you rectify this problem? A new school of thought around data analytics has some promising ambitions. This new approach to data analytics requires an entirely new way of thinking. Naturally, a majority of companies are reluctant to embrace a new approach that has yet to become mainstream. And that’s exactly why companies willing to take a risk and delve into the new world of data analytics stand to reap massive benefits.
To learn more about how new data analytics technologies are drastically streamlining the traditional analytics process, check out some of our more recent research.
