Three ways to monetize data — but you only need one

May 1, 2020  

The article by Barbara Wixom and Jeanne Ross was important to my learning about data strategy. They identified the three ways to monetize data.

When someone realizes they are sitting on data that could be an asset, it is like an explosion of ideas and possibilities. I love seeing an executive go through this transformation of thought. They see literally dozens of opportunities to create value using the data their company owns or has access to use.

The three ways to monetize data are:

Sell it

If you are gathering a lot of data specific to your niche, there are probably people that want like to analyze it. The stock exchanges are a recognizable example. They have transactional information about buys, sells, options, etc. A single transaction is quite boring, but in aggregate they become powerful. This is proven by just how commonplace reporting on financial news is, and how ubiquitous stock price charts are.

Your niche is not as globally interesting as that, but it is probably even more interesting to your customers, partners, and industry analysts.

This is a natural place for branstorming to go, and an idea that comes up almost every time. It seems so easy on the surface. Unfortunately, it is the least accessible. It requires a completely different business model than what you are already in–including different buyers, different sales processes, and different support and delivery mechanisms.

Internal efficiency

Managers who have accurate metrics of their operations and a convenient way to evaluate what is actually happening on the ground make much better decisions than otherwise. They know what should be happening, and having data to indicate what is actually happening empowers them to effectively manage. Alternatively, they manage to the squeaky wheel, by what they can directly observe, or by gut feel.

It’s not hard to see how this could make things more efficient and reduce waste and costs. This is also the most familiar territory, and business intelligence and its host of products and vendors have made this commonplace.

This is a great place to start. The downside is that it isn’t directly monetizing data. It’s ROI is usually in incremental improvements to processes already in place. So there is a limit to the cost savings you could expect to see–only so much juice you can squeeze from that orange.

Customer-facing analytics

To me, this is the most exciting and most accessible way to monetize data. Companies that get this right have reported being able to close more deals, grow key accounts, and improve retention.

Customer-facing analytics can come in many forms. Providing a dashboard within your web app or web site is nice and straightforward. This can inform the customer about the use of your services, or even benchmark their use against the rest of your customers in aggregate.

You could produce simple reports for sales teams that enable them to have more meaningful conversations with their buyers and even get access to strategic roles in their target accounts.

One thing I caution against is immediately charging a fee for your first foray into customer-facing analytics. Although this is easy to stick in a spreadsheet and show how much money you’ll make, customers rarely respond by pulling out their credit card for a feature they didn’t ask for. A better strategy is to differentiate your core offerings and use that differentiation in the sales process.

I like that these three categories cover pretty much any monetization strategy you can come up with. You know your customers and you know your market. Any of these monetization strategies have been proven to create value. If you want to impact top-line revenue, start by adding customer-facing analytics into your core product. If you want to focus more on efficiency, start with internal analytics.

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Adam Roderick

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About the Author

Adam's tech career spans startups to global firms, touching finance, tourism, e-commerce, and consulting. Spotting a way to give small- and medium-sized companies an advantage with data, he founded Datateer to democratize analytics. He values relentless progress, simplifying complexity, and putting people first.

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