What's useful
- Database and warehouse schemas, with realistic (de-identified) data.
- Analytics code: dbt models, SQL, notebooks and dashboards, with their history.
- Product event data showing how customers use your product.
- Data team documentation: metric definitions, data contracts and incident write-ups.
What qualifies
The listing is for SaaS and subscription companies of roughly 50 to 1,000 employees that have a data team and a working warehouse.
What to check first
- Customer data you process for customers. Under UK GDPR, if you process customer data on their behalf, you're their processor and can only use it on their instructions. Using it for anything else, including licensing, generally isn't allowed. Your data processing agreements will say the same.
- Data about your own business. Your own product usage analytics, billing data and internal metrics are usually yours as controller, but still need personal data removing or protecting.
- Code and schemas. Usually the clearest to license, once secrets and customer data are stripped out.
- Customer contracts. Some contracts restrict aggregate or anonymised uses too. Check your standard terms.
What it's worth
Mercor lists potential company earnings of $55kâ$350k for SaaS and subscription companies, depending on what's in scope. That is Mercor's own figure, not a promise or guarantee from us.
Could synthetic data replace customer data?
Sometimes. Schemas and code with realistic synthetic data can still be valuable. Raise it during scoping.
Does our dbt project count without the data?
It can. Well-documented analytics code with real history is useful in its own right.