Can a martech or adtech company license its data to AI companies?
Often yes, and not the part most people assume. The audience data, the profiles and the tracking logs are personal data and are not what is licensed. What a marketing or advertising technology company holds besides that is the record of how the product is built and supported: planning documents, tickets, internal chat and the write-ups of what worked.
What a martech or adtech company has that is licensable
| Product planning and design documents | Briefs, specifications and decision pages that show how a feature moved from an idea to a release, and what was dropped. |
| Support tickets from customers | Questions about campaigns, integrations and reports, with the answers. The customer details come out, and the problem and the fix stay. |
| Engineering and operations chat | Threads about outages, delivery problems and fixes. They show how a team diagnoses a fault in a system that moves fast. |
| Experiment and test write-ups | Summaries of tests the company ran on its own product, what was tried and what the result was. Useful where the reasoning was written down. |
| Customer success and onboarding notes | How accounts were set up and what went wrong in the first month, without the customers’ own campaign data. |
The line between your data and your users’ data
A company in this field handles information about people it never met: browsing, devices, purchases and audience segments. That data belongs to a mix of the company, its clients and the people themselves, and rules on consent and tracking are strict in many places. The sensible start is to treat all of it as out of scope and license only what describes the company’s own work.
Why the internal record is worth looking at
Few companies document how a data-heavy product is debugged in production. A series of tickets and chat threads that ends with a root cause and a fix is a training example of reasoning under pressure. The more consistently it was written down, the more it shows.
Client work needs its own check
Reports, creative and campaign results made for a client are usually the client’s, and agreements often limit how the company can use them. Anything that names a client or a campaign goes through the client review before it enters a set.
What stays out for a martech or adtech company
| Audience and tracking data | Profiles, device identifiers, segments and event logs about people stay out of every set. |
| Client campaign results and creative | Material made for or by a client stays out unless the client agrees. |
| Partner and platform terms | Integration agreements and platform confidentiality terms limit what can be shared, so those pages are checked first. |
| Pricing and margin discussions | Rate cards, bid strategies and margin talk are kept out unless the owner decides otherwise. |
An example, invented for illustration
Picture an email marketing platform with 85 employees and nine years of history. The owner selects the support tickets, the engineering incident chat and the product decision pages, and excludes the audience data and every client report. Customer names are replaced with stand-ins, staff names are replaced the same way, and the cleaned sample shows a ticket from a customer’s first complaint to the fix that closed it. The owner and the head of engineering approve the sample.
Questions owners ask about this
Is our audience data worth licensing?
It is personal data, usually governed by consent rules and client agreements, and it is not part of the general approach here. The sets described on this page leave it out.
Can campaign performance numbers be licensed?
Numbers about your own product can be, but results made for a client usually belong to that client, so those are checked against client agreements first.
We work with big platforms. Does that limit us?
It can. Platform and partner terms often restrict what you can share about integrations, so read them before listing any integration pages.
How old can the data be?
Older is fine when the product worked the same way. If the product changed completely, treat the periods as separate sets.
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Records to look at first
- Support tickets: The whole thread, wrong guesses included, with customers replaced by stand-ins.
- Team chat: Slack and Teams threads, where one person must stay one person and direct messages stay out.
- Project and task history: Jira, Asana, Linear, Monday, Trello, ClickUp and Airtable comments and status changes, not task titles.
Other industries
- Software companies: Tickets, postmortems and renewal threads; customers appear everywhere and code is a separate deal.