Monetizing Big Data / Analytics

A Look Back...

Last year we published a report summarizing both quantitative and qualitative research that explored the benefits, risks, and challenges of monetizing data and analytics. We found companies in nearly every industry that were moving beyond using data for efficiency gains and improved customer experience; they aspired to achieve market and revenue expansion.

More than 200 organizations from 12 industries were surveyed (along with 20 in depth interviews), split almost evenly between those who were in the early stages of assessing expansion opportunities and those which had entered market with an offering.

'Analysis paralysis' occurs when an individual becomes so lost in the process of examining and evaluating various points of data or factors for a problem that they are unable to make a decision with it.

-Investopedia

Most organizations acknowledged the importance of starting by inventorying data assets and assessing the market opportunity. However, almost all interviewees cited the risk of ‘analysis paralysis’ and were embarking on a First of a Kind (FOAK) approach to quickly launch and test new offerings.

Look Before You Leap...

Now a year on, we wanted to see how these early attempts at crossing the chasm were working out. We revisited a subset of the organizations to see what progress they were making against their key metrics: revenue & profit, customer acquisition & retention, and market expansion. We also inquired about early indicators of market traction such as references, account penetration, and opportunity pipeline.

What we found was that, many of these early offerings missed the mark on achieving some key metrics—specifically achieving revenue / profit targets and penetrating new markets. Not surprisingly, the ‘if you build it, they will come’ approach is also ineffective for offerings based on data & analytics.

The successes we found employed the First-of-a-Kind approach but prefaced it with sound market management to establish value, opportunity, and feasibility. Most importantly, they embraced a market validation strategy to gain direct insights into their customers’ priorities. In-depth customer needs discussions also provided unique discoveries that were often overlooked in the absence of direct customer feedback.

We found three key common ingredients in the market validation work employed by these successful data and analytics pioneers:

Establishing Customer Wants & Needs

So, the key question any business leader considering launching a new innovative data & analytic based offering needs to ask is, “Have we done our homework to really understand what our customers want & need and are we delivering it in a manner that will enable them to achieve their objectives while we achieve ours?”