When contemplating the utility of “Big Data”, many small and medium sized business owners perceive the processing of perhaps millions of data points to drive different strategies to be a lot like drinking water from a fire hose. For many SMB owners, all the talk about how Big Data can revolutionize initiatives across the full scope of a business is very reminiscent of how CRM software was marketed in its early stages; that processing a bunch of data points would reveal exactly what customers want.
Admittedly, Big Data has made some headlines, including statistician Nate Silver’s use of massive numbers of data points to accurately predict the Presidential and Congressional races in 2012. While the impressive accuracy of Mr. Silver’s predictions put himself and Big Data in the spotlight, he was quick to acknowledge that processing massive amounts of data to anticipate future events/actions was not an end-all solution and that it was subject to a variety of limitations including the proliferation of meaningless and/or inaccurate data and that some things are simply not predictable due to statistical anomalies.
Cast in this light, SMBs trying to get a handle on the signals being sent in the form of Big Data are unlikely to find competitive advantages there and are compounding the problem by ignoring something far more valuable; relevant data. This migration away from Big Data carries a bit of irony in that one of the best resources for collecting relevant data, especially for smaller companies, is the customer-specific information that can be derived from a targeted CRM program. The focus on customer-specific information accomplishes three things that can increase the accuracy of resulting assumptions:
- The data has a high likelihood of being accurate – Tracking the interactions between a customer and the company doesn’t lend itself to a lot of interpretation. In these situations, the signals provided by the customer such as purchases, for example, are both highly specific and accurate.
- Direct application – Information that applies directly to the customer avoids the inaccuracies that can occur when one set of data points is used to hypothesize an outcome on an unrelated subject.
- The absence of noisy data – The collection of relevant data eliminates ancillary information that can corrupt accurate intelligence.
SMBs will gain far more value and traction by leaving the processing of Big Data to others. Instead, by focusing on relevant data that applies directly to customers, preferences, and actions the results of company initiatives can be forecasted with high accuracy.