In the previous blog post I outlined why you should value data like a working skill. A report from Forrester states that top performing companies commercialize data. But what is data monetization and which monetization strategy have those companies adopted?
What are the technical ways to exchange data if you want to trade it through APIs? I will try to depict the field of possibilities.
Internal Monetization means that raw data or insights are primarily used internally, either to improve processes such as preventive maintenance or improve existing products. This participates indirectly in reducing costs or increasing revenue. Another alternative is to share data with some actors in the value chain so other developers can build adjacent services on top of existing data. Companies looking for this platform approach usually look for more stickiness of their services in the overall ecosystem they strive in.
Internal Monetization is usually the initial step you take before thinking about selling data externally.
It helps look at how it can directly impact the top line without exposing data assets externally.
External Monetization, on the contrary, is all about sharing data with external parties in exchange of value. This exchange of value can take the form of a payment, a free service or any other form of benefit. This data is either a stand-alone product or part of a bundled product with other existing offers.
For most people not familiar with the concept data monetization means selling data. This can be either selling raw data to established data brokers, data marketplaces, creating insight and offering data subscriptions or selling analytics solution. Data Selling is specifically the field that I know best. Let's look at the technical means to sell data.
When you have chosen this strategy, you can consider there are three main options:
o Data Base instance: It is practical when a lot of data needs to be shared at once with a customer. Providing access rights to customers to a database is the best way to have a solution up and running for a big amount of data at rest. For instance, some marketing agencies use the information from Equifax using big databases of historical data and/or information with a lot of attributes collected on individuals.
o File Sharing: It is used by market research companies or companies providing lists of leads that can be ingested in a CRM solution . It can also simply be a pdf document on market and data trends.
o APIs: Pipes to exchange information based on the understandable requirements of the buyer and what is available from the seller. This can be done with different architectural styles (REST/GraphQL/etc.)
I mapped out below drawbacks and advantages of the three options for data sellers and buyers:
It comes with no surprise that the most convenient and preferred way for companies to monetize and share data is exposing APIs. Programmable web is a library of referenced APIs for open APIs. There are already 21,000 APIs referenced online, a number growing exponentially.
Generally, buyers’ habits have changed as subscription is the by-default business relation that any SaaS start-up wants to establish with customers. The underlying cause is that buyers want to pay for value they get and not for ownership anymore. For sellers, subscription business models help to project future revenue and give the chance to offer additional services to existing customers.
Zuora, a subscription billing solution, states that 70% of the subscription business models’ revenue comes from renewals, cross sells and upsells. This is valid whatever your offer is (connected product, service or data). On top of understanding its contextual value, you need to understand how your data is queried. As you get your hands on how the things you are selling are used, you need to reconsider how you sell.
Now, you have the opportunity to bill all benefits that a customer can get from your data on a regular basis. You are not selling one-off products anymore but pricing the value someone gets from your data. Moving from ownership to subscription is not just about collecting data and changing business models. It requires to maintain a top-notch experience and relationship with your customers. However, do not default it to a one-size fits- all . Like it or not, your customers are different from one to another and the value they get is contextual.
In most cases, subscription applied to APIs is the best way to sell data.
Indeed, it looks like you just need to apply subscription business model on top of APIs and then you can start gold mining. The truth is that it needs hard work first.
You need to know how to capture a fair share of this value provided through data APIs. What are the key practical steps to understand the value provided and translate it into your pricing and subscription business model?
When designing products, configuration and bundling are more science than art so it requires processes and a clear path to maximize revenue. In the next blog posts, we will describe what could be the playbook to assess your “data value” and overall methodology to apply relevant subscription business models and maximizing revenue.