Big Data Doesn’t Always Show the Big Picture
  • 4 min Read

Data has a brilliant way of communicating a story. It’s precise, succinct, and if you understand it, it can be very, very accurate. However, to make meaning from data, it must be relative to the objective at hand.

First, what data should you be using? That one is easy: all of it. Enterprise-wide data is the idea of taking data often housed in silos across the business and using it to create a comprehensive picture. Predictions suggest that the volume of enterprise data alone will increase by 650% between 2014 and 2019.

We all know businesses are working to adapt, but to remain sustainable, the comprehensive picture of the business must be fluid, actionable and profitable.

Look at how data from customers, operations, cross-department transactions and market perceptions are affecting your brand and ultimately, your bottom line. Unfortunately, once this data is gathered, 72% of business and analytics leaders aren’t satisfied with how long it takes to retrieve insights they need from data. Increasing blind-spots are costing organizations money and the data isn’t slowing down for us to catch up.

But don’t be intimidated: comprehensive enterprise data isn’t a complete reinvention of the wheel or a new service product, it’s simply reinventing the process of research. And despite the shift in approach, there is still a place for traditional research methodology. Creating original data using traditional survey methodology and focus groups

on an online platform can serve useful in benchmarking and getting a quick and dirty read on your objectives. We use this methodology to answer questions such as customer satisfaction, identifying key performance indicators within your business model, highlighting your competitive landscape, perceptions and opinions about your brand, and concept/marketing testing.

Secondly, consider taking the “stagnant” data you have within your organization (think: transaction data, client list data, loyalty program data, customer service data, problem data, internet of things data, etc.).  Although this initiative relies heavily on your industry and your goals, the general idea is to take your longitudinal data on your customer (your current or lapsed customers) and combine it with larger patterns on your customer base (e.g., purchase transactions, social media conversations, problem reports/resolutions, website traffic, etc.).

From here you look to even broader variables that affect your business, such as weather, demography, geography, etc. We recommend looking to identify where these variables intersect. The end result is one succinct storyline, not fragmented slices across your departments.

Third, utilize your online presence and streaming data as a qualitative tool. This particular piece adds a depth to reports, providing you with unstructured, unsolicited perspectives. Think of this forum as the world’s largest focus group about your brand, your product, and your organization.

Combined together, these three pieces take a once segmented process and begin to provide a comprehensive view of the state of your business. It’s not a new product in research, it’s simply a complete solution in a segmented industry. Next, we’ll talk about how to put that big data to work.