Data monetization begins at home

Data monetization begins at home

Giles Cottle, Fri 05 January 2018

Data monetization continued to generate hype in 2017. It's not hard to see why. Some customers we work with consider data monetization to be something quite close to money for old rope - generating new revenue from information that an organization already has sitting in a database somewhere. It's more complicated than this of course, and the processes needed to turn this into something valuable for third parties is non-trivial (more on this later), but it's easy to see why the C-Suite is getting excited about it.

What we often find when embarking on data monetization projects, is that we can make quicker and more substantial gains by taking that data sitting in a database somewhere, turning it into something usable for internal teams, and optimizing internal processes. In-house applications of data may not be as "sexy" as monetization but often delivers more on a dollars and cents basis.

At Dativa, we often talk about "big numbers" when referring to data monetization. Most businesses we work with have a couple of significant numbers that are top of mind among most senior executives. For MVPDs and other subscription video businesses, the benefits come from churn (the number of customers that an operator loses on a quarterly or annual basis), or the what the platform has spent on the NFL, EPL or whatever other sports content drives subs in their market.

For airlines, acquiring fleet is by far the most substantial use of CAPEX. From an operating perspective, labor and fuel are the most significant operating expenses (the latter not being something that an airline’s data science team can do a great deal about). But another crucial variable in running an airline is the proportion of time planes spend in the air, vs. on the ground. Airline profitability relies on planes being airborne for as long as possible, and not sitting on the ground, racking up airport fees.

In both these examples - and, in most businesses, we come across - even a fractional improvement in these core metrics will increase by millions of dollars of profitability.

For this reason, we always advise customers interested in data monetization also to starting by using data to improve their most important internal processes. Or to put it another way, be sure that everything possible is being done internally to use data to optimize whatever the key performance indicators are for their business.

So which businesses should be looking at data monetization first? There are probably sectors that have historically invested more in using data to solve internal processes for whom external monetization is a natural next step. Hundreds of millions of data science working hours have been expending trying to keep airplanes in the air and off the ground for as long as possible, while the TV industry has only started scratching the surface of addressing churn using data.

And there are some market size and positioning frameworks that can be used to understand whether data monetization is the right play to make for a company. Any company that is a market leader in its field (e.g., has access to a bulk of the transactions/customers/data in its industry), and where that area has no existing data offering, should probably be looking at data monetization regardless of how they use data internally. Companies, where the opposite is true, should think more carefully about external monetization.

But in reality, the concept of internal and external monetization being an either/or decision is a misnomer. Most companies are doing both concurrently. Quite apart from anything else, we find that the technical and data engineering aspects of both - the data pipeline, storage, and warehousing, is often the same for both internal and external usage.

If a marketing team in your organization wants to access data to optimize campaign planning, and a third party wants to obtain data to streamline some of their internal processes, both are customers of that data, and both will want broadly similar things. They will probably want same-day (or real-time) access to cleansed, accurate data, and to be able quickly to access the information they need. And both may wish to obtain one or a combination of raw data, a relational database or a dashboard, app or interface to do so. From the CIO’s point of view, any development in a company's data infrastructure should feed both these internal and external use cases.

Data monetization is rightly something that excites the industry, but we always encourage customers to check that they are also doing everything possible to maximize the internal value of their data first.

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Dativa is a global consulting firm providing data consulting and engineering services to companies that want to build and implement strategies to put data to work. We work with primary data generators, businesses harvesting their own internal data, data-centric service providers, data brokers, agencies, media buyers and media sellers.

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