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For many enterprises, it seems like data is the new oil -- a valuable resource sitting untapped in the backyard, just waiting to be discovered and monetized.
IBM's recent acquisition of The Weather Co.'s data gathering infrastructure and Microsoft's recent purchase of LinkedIn reinforce the notion that a company's most valuable resource may not be its brand or its customer base, but rather the data it collects about those customers. In an era of declining margins and global financial uncertainty, many companies are looking for new ways to grow their business by monetizing data.
There are several distinct paradigms for data monetization. Any one of them can be a great starting point for your customers:
1. Use data internally to increase efficiency
For example, a paid TV broadcaster analyzes data collected from billing and customer service in order to identify customers who seem likely to cancel their subscription, based on increasingly late payments and increasingly harsh sentiments they express in service calls. The broadcaster's "hug squad" can proactively reach out to these wavering customers, offering discounts and additional services, thus reducing churn and increasing the top line.
2. Find new customers in new verticals for existing data
For example, a company that makes ticketing systems for public transportation -- think London's OysterCard or New York City's MetroCard -- collects a lot of data about riders' whereabouts and travel habits. This information would be worth a lot to:
- Urban planners seeking to build the next generation of public transportation routes.
- Navigation companies, like Google Maps and Moovit, that want to know about travel times and delays in public transit in real time.
- Advertising analytic companies, like LiveRamp and TAPAD, that want to know all devices owned by the same user (e.g., work PC, home PC, laptop, tablet, mobile phone), in order to provide a 360-degree view of the user's browsing habits. Information about where a person has travelled via public transportation would vastly increase the accuracy of these device graphs.
3. Sell the same data to smaller customers in existing verticals, so they can derive their own insights
For example, imagine a company that collects airline flight information. Suppose they have already taken the first step in monetizing data by selling customized reports about travel patterns to airlines and airport planners. Suppose each report costs $50K and requires three months of work. Well done, but there is an additional untapped market -- small and medium sized businesses (SMBs), such as hotels and rental car companies, that might be willing to pay for insights from your public transportation data, e.g., which customers frequently travel nearby and should be offered targeted discounts. Your current business model -- $50K per report -- is far too expensive for SMBs, and you cannot possibly scale your report development infrastructure to produce the vast number of distinct reports these SMBs will request.
The virtuous circle
Here's where we come to the virtuous circle of monetizing data. Rather than trying to provide customized analytic services for these customers, let your customers analyze a copy of the data themselves. Give them a nontechnical analytic tool (e.g., Tableau, QlikView) that doesn't require knowledge of programming or SQL. Whenever a customer discovers a useful analysis, give them an incentive to tell you (e.g., free access to the data for a year), so you can sell that analytic insight to your other customers.
The result is a virtuous circle, where your customers develop insights for you and your other customers. Companies that can get to this stage of monetizing data have -- at least figuratively -- struck oil in their own backyard.
About the author:
Moshe Kranc is CTO at Ness Digital Engineering, a provider of digital transformation and custom software product engineering services based in Teaneck, N.J.
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