ABSTRACT: Data producers leveraging new data exchange technology to sell their data directly to consumers are transforming the world of data commerce.

In the last few years, the world of data commerce has begun a seismic shift. Thanks to waves of digital transformations, ordinary companies now sit on volumes of data once possessed only by businesses that specialized in trading data. At the same time, new technologies have made it easier for these organizations to monetize their data through direct sales to other businesses--ending the monopoly of traditional data brokers.

Old, Broker-based Model

In the past, most companies that profited off of selling data were dedicated data brokers. These organizations aggregated data, packaged it into subscription services, and sold it to corporations. The data in question might be licensed from other businesses, taken from public sources, or collected by the broker directly. If an organization wanted to monetize its data, the easiest way to do so was through a dedicated broker. They alone had the reach and technical capabilities to sell data profitably. From the days of mailed floppy-disks, until a few years ago, this model remained largely unchanged. Data brokers combined data generated by multiple entities into a fixed set of data products that they sold to data consumers. (See Figure 1.)

Figure 1. Data Broker Model of Data Commerce

The broker model left a lot to be desired. Third party data became notorious for its poor quality and data consumers struggled to use data products that didn’t really align with their use cases.  Businesses were unable to buy just the data relevant to them, and instead had to subscribe to expensive subscriptions that included vast quantities of extraneous data. In addition, data was ripped from its context, limiting companies’ ability to understand the numbers they were looking at. But with few options to acquire outside data, the broker regime persisted. 

New Model of Direct Data Commerce

The recent explosion in data generated by newly or natively digitized companies has shifted the balance of power. Now, creating a large enough data set to warrant selling no longer requires aggregating data from multiple entities. Between mobile devices, cloud applications, and IoT sensors, a single organization often has plenty of data that would be of interest to data consumers on its own. In addition, data marketplaces and other data commerce platforms that leverage new data exchange technology have lowered the bar for creating and distributing data products to third parties.

A few examples of companies taking this approach include:

• Fanatics, a sports merchandise retailer that sells multiple streams of customer data broken down by item category.

• Braze, a software-as-a-service (SaaS) marketing platform that sells anonymized data generated by its platform users to facilitate benchmarking in multiple industries.

• Medisafe, a healthcare technology company that sells de-identified and HIPAA-compliant data about consumer medicine consumption

These two market forces have led to a new model for data commerce. In this approach, data producers sell data products directly to data consumers, avoiding data brokers entirely. (See figure 2.)

Figure 2. Direct Data Commerce Model

Benefits for Data Consumers

This new model provides several advantages over the previous paradigm for data consumers:

• No middlemen and more competition result in lower prices.

• Data maintains its original context.

• Data producers can better answer questions about data than data aggregators.

• Data consumers have more options and can acquire products more closely tailored to their needs.

• Issues with data quality can be traced back to their source. 

Benefits for Data Producers

Data producers also benefit from the new model in multiple ways:

• More control over their data

  • When selling directly, producers can pick and choose customers to avoid helping their own competition.

  • Producers can decide exactly what to share and for how long.

• Ability to realize the full value of their data

  • Direct connections with data consumers help producers understand all the potential uses for their data. In turn, they can craft better data products and extract more value than if they presented their data as a commodity.

• Freedom to set their own pricing

Data Commerce Platforms

The direct data commerce model relies on data commerce platforms to play the role of brokers in facilitating distribution. At its core, a data commerce platform is essentially a monetized data exchange. Third-party data marketplaces such as those hosted by Snowflake or Amazon are one example. In using a data marketplace as a data commerce platform, data producers give up some of their power (and sometimes profit) to the host organization. They don’t have to worry about maintaining the exchange or attracting consumers to the platform, but neither do they have complete control over the exchange environment.

An alternative form of data commerce platform allows an individual producer to set up their own digital store, rather than maintaining a stall in a marketplace. Vendors such as Narrative, Harbr, and Dawex provide exchange technology that allows data producers to list and distribute their own products in an exclusive environment. Although discoverability presents a bigger challenge, producers have a greater ability to customize the data consumer experience.

Conclusion

As this trend continues, traditional data brokers are likely to lose further market share to data producers trying to monetize their data directly. Data brokers aren’t going away anytime soon, however. In fact, traditional data brokers are already pivoting to meet this new competition, listing their products on public data marketplaces and using the same data exchange technologies to improve customer experiences. But the pressure from the new vendors operating under a different model can only benefit data consumers as corporate appetites for third-party data grow.