Data Into Dollars: Can You Turn Your Data Into Revenue?

Every organization desires a positive return on its investments in data. Forrester data shows that advanced insights-driven businesses (IDBs) are 8.5 times more likely than beginners to report at least 20% revenue growth in 2021. It pays off to become an insights-driven business. Vendors and the media trumpet the success stories of companies that build their businesses around selling their data. If you are a data leader under pressure to turn your data into dollars, read on.

We all hear the terms monetization, commercialization, and data as a product. Let’s get clear on what these mean.

• Data monetization: The process of leveraging your data to produce insights and decisions that grow revenue and improve your business. For example, a retailer creating a personalized experience on their e-commerce website monetizes their data when the customer accepts a product recommendation.
• Data commercialization: The act of creating a data product through packaging, pricing, and selling your data to other organizations. For example, a transportation and logistics organization sells location and business data to organizations seeking to enrich their customer and business information. This category also includes well-established data players such as Nielsen in the media space or Experian for consumer financial data.
• Data as a product: A set of data components combined to deliver a business outcome that can be monetized or commercialized. A telecommunications company monetizes data with a churn model made up of data, transformations, algorithms, and APIs to reduce customer attrition. A financial services company commercializes a REST API made up of protected customer information and purchases that are sold to merchants to improve customer targeting.

For most companies, the best option in the short term to medium term is monetization. Get moving with monetization by leaning into DataOps and investing in core analytics capabilities. Catalog your data and assess its quality, establish a solid governance foundation, and come up with a process for evaluating and prioritizing your business questions. Embed insights-driven decision-making into your business by defining key priorities, ensuring that you have the right staffing, pursuing a coherent data engineering agenda, developing a process for generating insights from data, and establishing a feedback loop of continual improvement. See Forrester’s guidance for building a maturity-based case for your data and analytics investments.

If you choose to pursue data commercialization, the obvious starting place is in defining a value proposition (why would someone buy your data?) and defining a delivery model (what you will offer and how you will deliver it to customers). Don’t underestimate the challenge of pricing, however, and make sure you set expectations early about the resources you need to develop, launch, sell, market, service, and maintain your product.

The original article by Forrester's vice president and research director Aaron Katz and vice presidents and principal analysts Boris Evelson and Michele Goetz, is here.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/:SpicyTruffel