Direct or Indirect Data Monetization, That is the Question

Last Thursday I was attending the DataMoney Conference organized by Outsell, Inc. in New York, and the day before I was in Nashville invited to participate in a panel discussion at InSage's 2nd Data Monetization Workshop. Two very focused events in two days, wow! And in both cases rooms were packed, mostly with C-suite executives: the business of data has definitely become a central piece of the executive's agenda.

The conversation about data has clearly shifted from technical to business.

Gartner is confirming this observation. Its latest data and analytics strategy predictions through 2021 are not focused at all on technology, but rather on the drivers of behaviour behind organizations monetizing, managing and measuring the increasing wealth of information assets available. The report indicates among other points that over 30% of organizations are directly monetizing information assets by bartering with them, trading them or licensing them outright. It predicts that many organizations will become either sellers or buyers of data via formal online data marketplaces. It also says that companies’ data and analytics capabilities are starting to become of material interest to institutional investors and equity analysts.

What we observe on the field with Dawex confirms the trend

I couldn't agree more with these observations. I work with Dawex, a two-sided B2B data marketplace acting as a trusted third-party between buyers and sellers of data (actually we should say licensees and licensors), and every day we observe the same growing interest from companies in data monetization issues.

It is a very diverse group of companies - in terms of size, data maturity or strategy - that are embarking in data monetization activities.

The chart below summarizes the main use cases that we have observed so far on Dawex marketplace. It makes a distinction between direct and indirect data monetization workflows, as well as between acquiring (licensing in) and selling (licensing out) data, plus some additional preparation steps :

Behaviours are mostly driven by the organization's data maturity

The most data mature organizations will generally approach the data monetization business opportunity by primarily leveraging their business and data skills to build insights, that can be turned into actions for better serving their customers, optimizing internal capabilities or even using data as the foundation for new products or services. We can talk here of Indirect Monetization. Data used in that process come from various internal sources i.e. the legacy systems (ERP, legacy CRM, logistic and manufacturing systems, …), digital systems (digital CRM, digital marketing, e-Commerce platforms, social platforms, …) and systems of automation (IoT, …). Notwithstanding the vast amount of internal data that large and mature organizations produce, they're still generally not enough. Creating a 360° view of the customer or building a hyper-personalized and highly contextual customer experience generally require enriching internal data sets or streams with data acquired from external sources, i.e. from professional data providers, open source data exchanges, and more and more often from companies who see an opportunity in licensing out their data directly.

Data marketplaces are essential building blocks for making these monetization scenarios possible, by creating market liquidity, building trust between buyers and sellers, streamlining and securing data transactions.

Data mature organizations (such as banks, insurance companies, hedge funds, energy firms, research & consulting organizations, and other large organizations …) generally prefer licensing in external data in raw formats (possibly cleaned, aggregated and/or anonymized) as they tend to have all the resources and skills in-house that are needed to refine the licensed data, map them with other data sources and do the analytics. Acquiring the data from the original producer is also an important criteria for the buyer. Knowing who you are licensing data from is key to assess quality and avoid bias.

Who is selling its data? who are those licensors? Actually there is no specific seller profile: we see any type of company, from small to large, from "data novices" testing how valuable their data sets can be with potential acquirers, to highly mature organizations who find in the direct monetization of their data, some additional and recurrent sources of revenue that complement their potential indirect monetization strategies and contribute to better ROIs.

Direct or indirect data monetization, that is the question

Some may say that direct licensing of data is a less interesting route to take when embarking in data monetization initiatives, that more “noble” indirect ways exist to create value from the data. Well, we shouldn’t oppose those two monetization approaches since they complement each other very well. Indirect monetization use cases generally require integrating external data sources to the existing internal ones, and the most interesting data sets or streams will often come from companies who have opted for direct licensing of their data. The circulation of data between companies of all sizes and industries is the cornerstone of a growing data economy that will eventually create massive combined value. Two-sided data marketplaces are key enablers in this movement, as they remove the friction by making it easier to buy, sell or trade data directly, securely within trusted and compliant environments. 

To know more about acquiring and monetizing data on Dawex marketplace, visit our website