Taking Smarter Risks to Monetise Your Data

At the core of business is an exchange of value. Companies create a product or service that adds new value for potential customers and then trades them that value for revenue. In order for a company to grow with data, it needs to continue to create new, transferable value from data that is desirable to customers. Often that new value comes in the form of removing a common pain point.

The right place for a company to start creating new value with their data is to understand their customer base and identify a problem that can be solved or a new benefit that can be created with the data they have. To be clear, when you build with data, you’re not selling data to the customers. You’re also not selling the new products you’re creating with that data. You’re selling outcomes. Your customers aren’t buying your features, they’re buying problems coming off their plate. They’re buying a shortcut to making difficult decisions. They’re buying opportunities for a return on their investment.

Once you’ve identified the monetizable value your data insights will create, you need to actually build a sellable good that delivers that value. This is the process of innovation.

The companies that are winning with data monetization are those that create scalable paths to each of the three types of innovation outlined here. No matter how high a business aims, there’s one extremely important step to take to pave the way to successful innovations: lower the cost to try.

Six steps to monetizing data-driven innovations

To help builders of all kinds with their data monetization strategies, I’ve broken the process down into six steps, each using data to achieve an outcome that is critical to business success.

1. Build a strong value proposition
Start by identifying the persona you will create value for and articulate the ROI that they will get from your product. Understand whether you’re changing their top or bottom line. Find a way to quantify that impact for your audience using the competitive landscape and set a timeline for delivering that return.

2. Consider value-based pricing
Once you know the buyer and you’ve quantified the return they’ll get from your product, it’s time to start thinking about the actual monetization part of your innovation — how much people will pay you for it. Look at your top- and bottom-line effects and consider a price of around 10-20% of that. For example, if you’ll provide $1M of new value, charge them between $100k–$200k.

3. Build an effective business case
It’s time to start treating your analytics innovations like new business units at your company. What does adoption look like? What is the forecast for orders, revenue, cost, etc.? A productive business case will have specific data for anticipated profit and loss and build toward an expected breakeven point. The data-based constraints of these targets are extremely important to keeping your innovation on track.

4. Prototype your product
The product that you eventually build and monetize has to reflect the value proposition that you aimed to build. It has to meet the requirements that you lined up, move through beta tests with users that look like your intended audience, and make a deployment deadline that fits your intended timeline.

5. Execute effective sales channel activation
It’s very important that your sales team is enabled to sell not just products and features like they’re used to, but to sell outcomes. The new value they’re selling is a different animal. Selling your data product well is going to take a significant amount of onboarding, training, and education upfront and then ongoing support throughout the lifecycle of your product.

6. Secure executive buy-in
This is a step that needs to happen all the way through the data monetization process, not just at the end, but it affects each of the other steps. It’s not easy to ask executives to invest in new products that are likely to commercially behave very differently from the core business. You need strong internal sponsorship to have the freedom to try new things, otherwise you’re doomed to fail. This mentality of data monetization via the creation of new products has to start at the top.

Your company has all the data you need to profitably build new things today. You can build new things that are faster, better, and cheaper or answer new questions. To transform that data into new revenue, you need to build an ecosystem that will reduce the cost of trying new things and then pave the way to use data at every step of your building process.