A few years ago, it seemed like every platform was launching a data marketplace. But today, the enthusiasm has cooled. More and more data and analytics leaders are expressing skepticism.
The Case Against Marketplaces
Industry critics often point to the same issue: limited demand. Outside of a handful of success stories, many data providers have seen little traction.
As one executive told Bobsled CEO Jake Graham at a recent roundtable, “We listed on a few marketplaces and after three years, made $3.18. It just didn’t work.”
Where the Skeptics Are Right (and Where They’re Not)
Marketplaces are not silver bullets for demand generation. A listing alone rarely delivers results. Too many teams uploaded their data and waited for buyers to show up. Most of them were left disappointed.
The ones who did succeed approached marketplaces differently.
Marketplaces as a Starting Point
Leading data companies treat marketplaces as an entry point into larger enterprise ecosystems. This approach has parallels in the software world, where cloud marketplaces are used to drive expansion—not as the primary sales engine, but as a lever to streamline access and integration.
The real opportunity lies in improving how data is discovered and evaluated within these ecosystems.
Why Discovery Matters More Than Ever
Enterprise data buying is still notoriously difficult. As the market evolves, product managers are beginning to focus less on awareness and more on discoverability. The goal isn’t just to get listed—it’s to be found, understood, and evaluated quickly by technical buyers.
What the Best Data PMs Are Doing
We’ve spoken with over 50 data product managers across the industry. Here are five strategies they’re using to improve data discoverability:
1. Manage your data like a product
Structure your data with clear metadata, well-defined schemas, and thorough documentation.
2. Include example use cases
Show how your data can solve real problems with example queries, sample notebooks, or visualizations.
3. Publish it widely
List your data on your website, major cloud platforms (Snowflake, Databricks, GCP), and relevant industry exchanges.
4. Offer low-friction trials
Provide instant access to samples—no forms or approvals—so potential buyers can quickly experience the value.
5. Package it effectively
Break your data into focused, usable segments that are easy to evaluate and apply.
How Bobsled can help
Customized data products
With Bobsled's product creation engine, product and sales teams to easily build customer products with near zero engineering support. Filter rows, pick columns and even join tables through an intuitive UI. And since the products are logical views on top of the dataset, they do not generate incremental cloud costs.
Learn more about data product creation in
Meet customers where they work
Instantly share data into the ecosystems where modern data teams work. By delivering data directly to customers in Snowflake, BigQuery and more, GTM teams can not only radically accelerate onboarding, but also unlock partnerships with the major data platform.
As Jonathan Gallo, Principal PM of Cloud at Cotality, told us: “We realized early on that we needed to meet our customers in their own decision-making ecosystems. Bobsled was our fast-track into those worlds.”
Learn more about Global Fulfillment with Bobsled