Two weeks ago, we discussed ways to “monetize” company data – indirectly – by enhancing products or services, driving sales and marketing, reducing costs, improving productivity, expanding the user base, reducing risks and developing new products.
As noted, many businesses are sitting on enterprise data that could be a treasure trove, but they either do not know how to access the datasets or that they even exist in the first place. Operators who do not appreciate the value of their data are susceptible to competition and are leaving money on the table.
This article is intended to help operators think differently about data they have and can access. Instead of writing off data as merely a byproduct of their core business, operators should know that sophisticated business analytics tools exist that can help convert dormant datasets into valuable products and enhanced services.
The following are three business models operators can use to turn data into real money.*
Sell Raw Data: The first – and simplest – way businesses make money from existing datasets is to sell them in raw form. For example, GM sells the vast amount of data it collects from its OnStar onboard computers to insurance companies. Insurers then analyze the data for driving patterns and assess risk more intelligently. Ultimately, insurers use the data to develop new pricing bundles that more accurately reflect actual risk. Serving solely as a data provider, however, is the lowest value option because it minimizes the opportunity to provide enhanced services.
Process Data to Sell Insights: By processing data, operators can create applications that sit on top of the data, which help generate new value-added services and create platforms for data-driven transactions and the provision of insights. Customers purchase access to these insights, for example, to conduct predictive modeling or to understand better how segments of the population behave. For example, AirDNA acquires and processes raw rental property data from AirBNB and Vrbo. It uses the processed data to sell access to its product MarketMinder, which allows customers to investigate over 25 key short-term rental metrics and trends in over 80,000 cities worldwide.
Sell Tailored Transactions: The most lucrative data product is one where operators create a platform on which customers become part of a transactional ecosystem. Often, this requires platform users to provide data (e.g. location, interests, etc.) and consent to the application using the data to tailor and sell exclusive offers. For example, O2 is a mobile network operator that offers an application called Priority. O2 customers who download the app are served exclusive offers “that are nearby” the user’s location, including events, clothes and restaurants.
I encourage those who are interested in learning more about monetizing data to read this article published by Accenture. In addition to serving as a resource for this article, it contains a helpful infographic illustrating the dichotomy between “value” versus “volume” of data.
In a future Tech Talk, I will discuss the steps required to releasing your data product or service into the market.