Direct buyers vs brokers vs data marketplaces
There are three basic ways to sell or license company data:
- Go directly to a buyer.
- Hire a broker or seller-side advisor to find and negotiate with buyers.
- List the data on a marketplace.
The difference is mostly about who finds the buyer, who does the work, and how much control you keep.
The short answer
Go direct when you already know who wants your data.
Use a broker or seller-side advisor when you need help finding buyers, understanding what the opportunity may be worth, or negotiating the deal.
Use a marketplace when your data already works like a product that you can package, deliver, update, and sell repeatedly.
There is no universally best route. They solve different problems.
Most importantly, do not compare headline prices alone. Compare the rights you are giving up, the work required, and the actual economics of the deal.
Comparison at a glance
| Seller question | Direct buyer | Broker or seller-side advisor | Data marketplace |
|---|---|---|---|
| Who creates demand? | The buyer already has a current need. | The intermediary finds and approaches possible buyers. | The marketplace provides discovery, but buyers still need to want the data. |
| Who is across the table? | The organization buying or licensing the data. | One or more buyers introduced through the intermediary. | A customer or subscriber using the marketplace. |
| Who defines the asset? | Usually you and the buyer together, based on what the buyer needs. | Usually the seller and advisor before or during outreach. | Usually the seller, within the marketplace's listing rules. |
| Who sets the terms? | You negotiate directly with the buyer. | You negotiate with buyers, with the intermediary helping structure and compare proposals. | The seller works within the marketplace's pricing and contracting options. |
| How much market feedback do you get? | Usually one buyer's view unless you speak with others. | Potentially several buyers' views. | Potentially a wider audience, but a listing does not guarantee demand. |
| How much preparation is required? | It varies. Some buyers handle substantial preparation themselves. | It depends on the engagement and what buyers require. | Usually more, because the data needs to function like a maintained product. |
| How are fees handled? | Through the economics of the negotiated deal. | Retainer, success fee, buyer fee, or some combination. | Platform, storage, fulfillment, payment, or transaction fees may apply. |
| Best fit | You have a clear match with an active buyer. | You may have valuable data but need help finding buyers or structuring the deal. | You have a repeatable data product that can support ongoing customers. |
These categories can overlap.
A marketplace may support private negotiated deals. An advisor may also operate a platform. A direct buyer may package or sublicense data to other customers.
The label matters less than the agreement you actually sign.
1. Direct buyers
A direct buyer is an organization already looking for a particular kind of data.
Handshake AI says it licenses company data, works with sellers to determine what is useful, de-identifies and prepares the records, and supplies them to authorized AI labs under contract. See Mercor vs Handshake AI for how its program compares.
Scale AI describes ongoing data partnerships built around structured, de-identified operational records. See micro1 vs Scale AI for how its program compares.
Those are examples of active buying programs. They are not evidence that every company or dataset will qualify.
When going direct makes sense
Go direct when your data clearly matches something a buyer already wants.
The main advantage is speed. A buyer can usually tell you early what it needs, how the data should be prepared, and whether there is enough interest to keep talking.
That can save you from spending time packaging data nobody currently wants.
The tradeoff is that one buyer's offer only tells you what that buyer is willing to pay and what rights it wants in return.
A fast deal is not automatically a good deal.
If the buyer wants exclusivity, future data, broad usage rights, sublicensing rights, or long retention periods, those terms may matter as much as the headline price.
Questions to ask a direct buyer
- Is the license exclusive or non-exclusive?
- Are there limits by buyer, industry, geography, or time?
- Is this a one-time transfer or an ongoing feed?
- Does the deal include future records?
- Can the buyer sublicense or resell the data?
- What uses are permitted?
- Who handles filtering, de-identification, cleaning, and delivery?
- What happens to rejected records?
- What rights apply to derived data, embeddings, or model outputs?
- What deletion, retention, audit, security, and indemnity terms apply?
A published payout range tells you that a buying program exists.
It does not tell you what your data is worth, how many sellers get accepted, or what a normal transaction looks like.
2. Brokers and seller-side advisors
A seller-side advisor starts with your data, then looks for buyers who may want it.
The advisor may help define the asset, position it for the market, identify buyers, manage outreach, compare proposals, and negotiate the transaction.
When an advisor makes sense
An advisor can be useful when you think the data may be valuable but do not yet know who will value it most or how the deal should be structured.
Different buyers can value the same records for different reasons. Testing the market can reveal opportunities that would not be obvious from speaking with a single buyer.
The tradeoff is straightforward: you are paying someone to create and manage that process.
Before hiring an intermediary, understand exactly who they represent, how they get paid, and what control you keep.
Terms to settle before hiring an advisor
You should understand the scope of any exclusivity, the fee structure, who controls buyer communication and data samples, who makes pricing decisions, and what happens to introductions after the engagement ends.
If the intermediary can also receive money from the buyer or another referral partner, make sure that arrangement is disclosed and understand whether it affects what you pay.
How DataDeals works
DataDeals is an independent buyer-matching and introduction service. It helps sellers identify AI companies likely to be interested in their data and facilitates introductions.
It is not a marketplace and does not take ownership of the seller's data.
Our service is free for sellers. We earn referral fees from participating buyers when successful deals are completed. We disclose these arrangements before making introductions. We never charge sellers a commission or deduct a fee from their payments.
Sellers negotiate directly with buyers. There is no exclusivity or obligation to proceed.
See How DataDeals Works for the current terms and process.
3. Data marketplaces
A data marketplace provides infrastructure for selling data.
Depending on the platform, that can include listings, contracts, billing, delivery, usage monitoring, and seller reporting.
The important distinction is simple:
A marketplace gives you infrastructure. It does not automatically give you demand.
Examples
AWS Data Exchange requires providers to register and qualify.
Providers can publish public products or create custom offers. AWS says providers control pricing, duration, legal terms, usage rights, and refund policies, while AWS Marketplace handles collection and monthly payouts after service fees.
Snowflake Marketplace allows eligible providers to create private or marketplace listings, monitor usage, and charge for access inside Snowflake. Paid listings require provider setup, payout configuration, and approval.
Mozilla Data Collective says providers choose their license terms and license data directly to end users, while the platform helps with discovery and may host or deliver the data. Its provider terms also restrict several sensitive data categories unless specifically approved.
Troveo runs a marketplace that licenses company data to AI buyers on a revenue share. See Mercor vs Troveo for how it compares with a direct buyer.
When a marketplace makes sense
Marketplaces work best when your data already behaves like a product rather than an undefined archive.
You should be able to explain what the dataset contains, who it is useful for, how buyers receive it, how often it changes, what buyers are allowed to do with it, and what they are paying for.
You also need to maintain the product and support the delivery model the marketplace requires.
That makes marketplaces a better fit for repeatable data products than highly customized one-time transactions.
Listing infrastructure is not the same as buyer demand.
Putting a dataset on a marketplace does not mean someone will buy it.
Before you choose any route
The route matters, but the underlying deal matters more.
Before you approach buyers, hire an advisor, or create a marketplace listing, understand what you actually have and what you are prepared to sell.
Define the asset
Be specific about what the data represents, where it came from, how much exists, how far back the history goes, and what happened after each record was created.
The business context surrounding the data can be as important as the raw files themselves.
A collection of service records becomes more useful when a buyer can understand the problem, the response, and the outcome.
Check the rights
Having the data does not automatically mean you can license every possible use of it.
Review anything involving personal information, customer or employee records, third-party intellectual property, confidentiality obligations, or regulated information before agreeing to a transaction.
Separate access from ownership
Most data deals involve usage rights, not simply handing over ownership of everything.
A buyer may receive permission to use certain records for certain purposes without owning the underlying data or every possible right connected to it.
The agreement should make that distinction clear.
Price the rights, not just the files
Not all licenses are equal.
The more a buyer asks for, including exclusivity, future data, sublicensing rights, broader permitted uses, or longer retention, the more carefully those rights should be evaluated separately from the dataset itself.
Two offers for the same files can be very different deals.
Decide who does the work
Agree upfront who is responsible for preparing, cleaning, de-identifying, hosting, delivering, maintaining, and eventually deleting the data.
A higher offer may not be better if the seller has to absorb substantial technical, legal, privacy, or operational work to complete the transaction.
Look at what you actually keep
Intermediary fees are only one possible cost.
Marketplace fees, legal review, privacy work, security work, storage, technical preparation, and ongoing delivery can all change the economics.
The important number is not simply what the buyer pays.
It is what the seller keeps after the deal is done.
Keep final approval with the seller
Before transferring raw data or accepting binding terms, know who the buyer is, what data is included, what the buyer can do with it, how long those rights last, whether the buyer can share or sublicense it, and what protections apply.
The practical choice
Go direct when you already have the right buyer.
Use an advisor when you have potentially valuable data but need help finding buyers, creating competition, or negotiating the deal.
Use a marketplace when the data already works like a repeatable product.
Direct buyers provide demand. Advisors help find and negotiate demand. Marketplaces provide infrastructure.
DataDeals helps sellers understand what they have, test buyer interest, compare proposals, and keep the final decision on the seller side.
Start with the Data Value Calculator, or request a free Data Opportunity Review if you already have a dataset or offer you want evaluated.