Fivetran's ecosystem-led growth
Bob Moore, CEO and co-founder of Crossbeam, on ecosystem-led growth
Fivetran worked as an ELG model because the product sat in the middle of a multi vendor workflow that customers were already assembling. A data team would use Fivetran to pull data from apps like Salesforce or Shopify into Snowflake or BigQuery, shape it with dbt, and analyze it downstream, which made warehouse vendors, transformation tools, and consultants natural partners in both sourcing and closing deals. That let Fivetran grow by riding the expansion of the whole modern data stack, not just its own direct sales motion.
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The product itself created partner adjacency. Fivetran sold managed connectors into cloud warehouses, and customers commonly paired it with Snowflake, dbt, and reverse ETL tools like Census. In practice, that means the same buyer often evaluates several vendors at once, so partner referrals are tightly tied to real implementation work, not loose brand marketing.
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The strongest ELG setups are built around a small set of high value partners, not a giant marketplace. In this stack, a handful of products account for most customer value. Snowflake integrated Fivetran into Partner Connect and marketplace procurement, while Fivetran later expanded formal co selling and reselling incentives for partners, turning technical compatibility into a repeatable sales channel.
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Fivetran also shows the limit of ecosystem dependence. Its growth came from maintaining hundreds of connectors across changing third party APIs, but that same position exposed it when large SaaS vendors built native warehouse exports and when open source players like Airbyte pushed connector creation to the community. The ecosystem is a distribution engine, but it also keeps pressure on margins and differentiation.
This points toward a more consolidated data stack where the winners are the companies that become the default connective tissue between other tools. Fivetran's planned merger with dbt Labs pushes in exactly that direction. The next phase of ELG in data will come from owning more of the shared workflow, while still staying neutral enough that the rest of the ecosystem keeps sending customers through.