Martech and Adtech Company Data: What AI Labs Want
AITrainingDataBroker.com
Martech and Adtech
Company Data
AI Labs Want?
AI Labs Want?
What can be licensed, what is left out, and what to check first
Jimmy Lin
Martech and Adtech Company Data AI Labs Want?
Martech and adtech companies hold a lot of data, and the best-known part of it, the audience data, can not be licensed. So what can? Marketing technology and advertising technology companies, which people call martech and adtech, also keep years of everyday work that AI labs want to read. In this video I will show you what that work is, what we leave out of the license, and the checks to make first. We start with what an AI lab hears when it hears martech.
The video
Full script
Martech and adtech companies hold a lot of data, and the best-known part of it, the audience data, can not be licensed. So what can? Marketing technology and advertising technology companies, which people call martech and adtech, also keep years of everyday work that AI labs want to read. In this video I will show you what that work is, what we leave out of the license, and the checks to make first. We start with what an AI lab hears when it hears martech.
When an AI lab hears martech or adtech, it thinks of audience data about millions of people, and that is exactly the part we leave out of the license. The industry is huge, though. According to the Interactive Advertising Bureau, the industry group for online advertising, and the firm PwC, US internet advertising revenue reached $258.6 billion in 2024, so these companies run big teams and write a lot down. That written work is what this video is about. It is general information and not legal advice. First, let me tell you who I am.
I'm Jimmy. I have worked in data at Fortune 500 companies, as a data analyst, a data engineer and a software engineer, and I am trained in data science. I am also a Canadian military veteran, where I worked on data analysis and reporting.
If you want to sell your data, I am your broker and technical advisor. I bring your data to several AI companies, and I guide your team through the technical side, including compliance. You do not pay anything: AI companies pay my fee.
Already shopping your data around? Contact us anyway. We can still work through the terms with you and help you negotiate the best price.
If you are buying data for an AI lab, I find the right data and see it through to delivery, so you can focus on your research.
So what does a martech or adtech company hold besides audience data? 3 kinds of everyday work stand out. First, briefs and plans, the documents that show how a campaign or a feature went from an idea to a launch. Second, support tickets, where customers ask about reports and integrations and the team answers. Third, team chat, the threads where engineers and account teams work out why something broke. There are also test write-ups and onboarding notes, but these 3 give an AI lab the clearest view of how the work is done.
This is why an AI lab cares about the order of events. In one campaign the brief comes first, then the build, then the launch, and then, quite often, a fix when something does not deliver as planned. A ticket thread or a chat that follows all 4 steps shows a model how a team reasons when time is short. The more consistently it was written down, the more it shows, so a team that writes down the fix, and not only the launch, has the stronger set.
Now the line that matters most. On one side is information about people, such as device codes, browsing and audience groups. It belongs to a mix of the company, its clients and the people themselves, so it is never shared in any set. On the other side is the work about the product, such as the ticket, the question and the fix, and there we de-identify your data, which means we remove the names. For example, Marco at a client company shows up as Customer 63 in every ticket, so the story stays and the person does not.
Rules on tracking give a second reason to keep audience data out. Take California's privacy law, which people call the CPRA. It lets people opt out of the sale of their data, and also of the sharing of it for targeted ads, even when no money changes hands. Many other states and countries have their own rules, so the safe start is to treat all audience data as out, and to license only what describes the company's own work.
Client agreements come next. Many of them include a clause like this one, saying the client's material may be used only to provide the services. Where yours says that, the reports, the creative and the campaign results made for that client stay out, unless the client agrees. Platform and partner terms matter too, because they often limit what you can say about an integration, so we read those before any integration page goes on a list. Your counsel confirms what applies to you.
Put it together and you get 6 checks. The audience data is removed, the client agreements are read, and the partner and platform terms are read. The data is de-identified, which means the names of staff and customers are removed. Pricing and margin talk is set aside, and your team signs off. But the list will not hold up unless each check is written down, so keep a short record of what you checked and who decided.
Take an invented example, an ad measurement company with 60 employees and 8 years of history. It sorts its data into 10 kinds. 4 are audience data, so we leave them out of the license. 2 are client reports that wait for the client's yes. The other 4, the plans, the tickets, the team chat and the test write-ups, are listed. So 4 of the 10 can go in front of an AI lab, and the other 6 are handled one at a time.
Now turn this on your own company. Open each tool your team uses, from email and team chat to tickets, your wiki, your CRM and your shared drive. For each one, ask 2 questions: whose data is in here, and what does the contract say? Write the answers on one sheet, and you will know, probably within an afternoon, which tools hold your own work and which hold other people's.
When your sheet is ready, here is how I help with the deal. I show your cleaned sample to several AI companies and AI labs and bring back their offers, so you can set them side by side, and you make the final call. On the data side, I help your team with which exports to run, the file format, and how the data is de-identified. Contracts and insurance are between you and the AI lab and depend on the deal, so we start only after your team signs off.
A martech or adtech company does not have to give up its audience data to have something an AI lab wants to read.
If you run a company with 30 or more people, the data you already have could become a new revenue stream.
Want to find out?
You can check if yours qualifies, for free, at AITrainingDataBroker.com.
If you have further questions, leave them in the comments, and I will answer them in the next video.
Thank you for watching.
I will see you next time.
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