The reason to become a data provider is simple, even if we're all a tad trepidatious to say so, money. Data is valuable and providers aim to deal their users into the value creation.
Data providers present users compensation offers (aka rewards) in-exchange for the legal licensing of user data. Licensed data is aggregated and merged across all providers to create unique data sets purchased by companies for uses like AI model training, quantitative trading, and marketing measurement. As data is purchased, compensation flows back upstream to providers and users. This opens up new economic models for providers that users are eager to participate in.
- Monthly cash rewards for users that continue to come back and use the app over and over.
- Turning an existing coupon program into data licensing to increase margin.
- Paying or partially paying for premium features with data.
- Trading data for access to a new game level or weapons upgrade.
- Issuing in-app currency or loyalty points for participating in data licensing.
85% of shoppers are willing to trade data for coupons.
Data monetization doesn't have to be shady — people appreciate being treated fairly. Before we get too into the weeds on cash compensation, legal compliance, and technical implementation, let's make sure your business meets some basic criteria.
- A strong user base — the rough rule of thumb is over 100k MAUs (monthly active users). This is a rough rule of thumb because really unique data sets and user bases can be monetarily significant in smaller quantities.
- A way to compensate users — this is not necessarily cash. For example, you might offer users coupons, discounts, or in-app rewards with the cash payout yours to keep.
- A web or mobile application — we currently don't support brick and mortar or point-of-sale systems. Maybe you can convince us it's worth adding.
As you're reading through the rest of the documentation in this section, please note that the information contained is meant to be educational, to explain how our platform works. For the majority of customer use cases, implementation is abstracted and greatly simplified. To skip the lecture and jump in, head to our Getting Started guide.
- Data Licensing — how data licenses work and differences between zero and first-party data.
- Data Provenance — the chronology of data ownership and our compliance audit trail.
- Data Rewards — the requirements for offering data rewards to users.
- Data Publishing — the basics of submitting data to the platform for monetization.