Data Monetization: 9 Key Questions Exchanges Should Ask Before Building a Data Distribution Platform

Sales of data and analytics have emerged as an important revenue generator for exchanges and execution venues, which create valuable datasets as part of their core activities. For organizations looking to improve their data distribution and monetization , the first decision point is often whether to attempt to fit the new requirements to their legacy platforms and processes, build their own internal platform, or buy a commercial solution.

Those pursuing either of the first two options quickly learn that in order to realize the potential value of their expanded datasets it’s imperative to put in place a modern platform for packaging, selling and distributing data.

This kind of platform needs to have tools and modules for designing highly granular data products, scenario testing of different pricing and business models, and access to billing systems. It needs to feature support ways of accessing the data like Snowflake Share, Databricks Delta Sharing and S3 Transfers, Rest APIs for querying data, and more traditional data distribution mechanisms like SFTP and direct web download. And it needs to provide delivery capability for core datasets and data products, as well as connectivity and compatibility with existing third-party data marketplaces.

Taking the ‘buy’ as opposed to ‘build’ route is compelling for many exchanges, in part because most in-house data management solutions are built from a mix of legacy technologies, often resulting in a cumbersome and expensive infrastructure that only provides basic features.

Build Vs. Buy

Those considering building their own should ask themselves the following key questions:

1. Can your customers pull up a web interface that shows all the data products available? Making prospective consumers aware of your entire range of data services is a fundamental way of ensuring clients get access to all the data they need.
2. How easily can they fill out their shopping cart and finalize a transaction? Today’s online retail shopping environment has lifted consumer expectations of ease of use. It’s essential that your data sales process is not tripped up by substandard e-commerce capabilities.
3. Can your customers choose how to access the data? Giving clients choice on how they access the data they purchase helps encourage usage and boost customer satisfaction, driving future sales.
4. How quickly do your customers get their data and updates? Again, the digital consumer experience has raised expectations of immediate access to services. It’s important not to be left behind; your platform needs to be optimized for data discovery and orchestrate a better distribution of data.
5. How quickly can you add a data product to the store? Can you do it without involving specialized staff? (Data Engineer, Software Developer, Data Scientist, Market Specialist…) As with any business, time to market is a vital factor in the success of a new product. The ability to add new capabilities without the need for expensive resources and time-consuming processes gives you the flexibility to rapidly address emerging client demand.
6. Can you mix data together or use analytics to create new products? Commingling disparate datasets allows you to create unique products that can be targeted at specific types of customers.
7. Has your in-house solution reached capacity? Can you support thousands of data products representing Petabytes of data? How many customers can you service? The ability to scale your platform is important, as system downtime creates client frustration and can damage your brand.
8. Is your solution architected to get the most of Cloud-based infrastructure at the lowest cost? Shifting essential processes off-site and into hosted environments, often in the public Cloud, is becoming a mantra among financial technologists – and with good reason. Cloud offers flexibility and scale at appropriate cost points, giving you the headroom you need, when you need it, to provide your clients with exceptional delivery and service.
9. Is your infrastructure reliable enough? (High Availability and Disaster Recovery Plan) Again, spotty performance can damage reputations. It’s essential to put in place a robust infrastructure to ensure clients can enjoy the reliability and uptime they are accustomed to.

Exchanges that have implemented the TickSmith Enterprise Data Web Store – many of them deeply experienced in selling their real-time data to vendor redistributors and financial institutions – have typically replaced internal systems or abandoned plans to build bespoke solutions, usually due to the complexity involved.

For these exchanges, deployment of the TickSmith Enterprise Data Web Store resulted in tangible benefits compared with an in-house build, including cost savings, accelerated time to market, the ability to scale and grow the business using a proven platform, and the option to build on top of the platform using APIs.

The TickSmith Enterprise Data Web Store provides all the functions needed to rapidly design and bring to market new, granular data products, in support of a viable and sustainable data sales business.

Building a ‘Private’ Marketplace

The private marketplace concept can transform exchanges’ approach to monetizing their broader datasets. The approach effectively allows them to make their data available everywhere but manage all aspects of data packaging, sales and distribution from a single platform.

TickSmith’s Data Catalog capability allows exchanges both to support and operate their own data marketplaces while making their individual data products available through others’ marketplaces. As a result, exchange clients benefit from the simplicity of a single point for setting up data products, as well as for licensing and selling these products while enjoying the visibility and exposure afforded by third-party marketplaces, be it Snowflake, AWS Data Exchange or some other independent data marketplace operator. In this way, TickSmith’s clients have seen value in getting exposure in various marketplaces while being able to set up and manage all their products and have billing centralized in one place.

At the same time, they can add in third-party datasets to augment their own data products available through their own marketplaces. For example, CME Group uses TickSmith Enterprise Data Web Store to power its DataMine storefront for its own data products, but also to ‘stock’ other exchange operators’ datasets, such as data from the Johannesburg Stock Exchange, as well as an extensive inventory of alternative data sourced from third-party data providers. All of these combined bring the total amount of data products on CME DataMine to more than 75,000 targeting different segments and personas.

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Exchanges are Becoming Data Marketplaces
Building New Audiences and Promoting Trading Products

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In conclusion, exchanges need to consider a few key elements as they design their data offerings. They need to build in the flexibility to allow packaging of data to reach different client types and market segments. They need a technology approach that supports interoperability with other datasets and technology platforms, thereby allowing the commingling of data to create useful and valuable insights. Finally, they need to understand how clients use their data, a capability built into the TickSmith powered Data Web Store no matter where the data is ultimately sold.

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