Reach the enterprises
already looking for your data.

When Datastruct is helping a customer with real budget and a real production use case run discovery, we might reach out to anywhere from ten to twenty different data vendors to collect metadata that helps the customer determine fit for their use case. If that information isn't published on your website, we may reach out and ask you directly.

We can't promise any probability of being selected, but data vendors who provide the best, richest, and most accurate information are always more likely to advance to the next stage.

Absolutely not. Most of our production integrations are structured as processor agreements, where the data vendor has a direct relationship with our customer. What we're doing during discovery and testing is streamlining our customer's ability to explore what's available and determine market fit, moving to production as quickly as possible, for both the customer's benefit and the vendor's.

Our technology lets us move and work with data faster than vendors often can on their own, and our pre provisioned data budgets cut out what can sometimes be weeks or months of searching for budget to fund a data test. Our goal is to streamline the process, never to cut a data vendor out of the relationship. Often during testing, the vendor is brought in directly to talk with the customer and build their own dedicated relationship.

We want this to be an amazing sales channel for you: real use cases, committed resources to test and evaluate data, and a genuine shot at productionalizing the solution and developing an ongoing customer relationship.

Samples work for some of our customers, but often our customers have more sophisticated needs and a specific population they need to test against. We strongly prefer free data tests and do everything we can to minimize the work required on the vendor's side, including handling the actual enrichment through your APIs ourselves, so you don't have to lift a finger. That said, we understand data tests sometimes carry real costs, and we're fully capable of covering those through our data budgets.