Financial research concept

Data Cloud Net Revenue Retention Rate

Data cloud net revenue retention measures how product revenue from an existing capacity-contract customer cohort changes from one year to the next.

By Lee BaileyPublished Sep 23, 2026
Research context

See what supports this page, how current it is, and where comparable or historical context is available.

Research date
Sep 23, 2026Use the dated article and cited sources for the definition, examples, and stated limitations.
Operating-model context
15 connected conceptsPart of the reviewed Data Cloud Consumption Economics; issuer definitions remain distinct where disclosed.
Company examples
1 reviewed companyRelationships reflect supported examples, not a normalized cross-company KPI ranking.
  1. Snowflake's calculation
  2. Investor caution
  3. Part of the Data Cloud Consumption Economics
  4. See It in Company Research
  5. Continue Research

Data Cloud Net Revenue Retention Rate measures how product revenue from an established customer cohort changes from one year to the next.

Snowflake reported a 126% net revenue retention rate as of July 31, 2026.

Snowflake's calculation

Snowflake uses a trailing two-year measurement period. The cohort includes customers under capacity contracts that used the platform in the first month of the first year. The company then divides second-year product revenue from that cohort by first-year product revenue from the same cohort.

Customers that stop using the platform remain in the cohort and contribute zero product revenue in the second year.

Investor caution

This is an issuer-defined, dollar-based metric, not a universal SaaS formula. Snowflake includes certain reseller end-customers, adjusts historical figures for specified corporate events, and excludes on-demand-only customers from its customer-count framework.

A rate above 100% indicates expansion within the measured cohort after contraction and churn effects, but it does not identify how much came from price, workload growth, new use cases, or mix.

Source:

Part of the Data Cloud Consumption Economics

Connect realized platform consumption, enterprise customer expansion, contracted demand, revenue mix, and gross-margin economics for consumption-based data-cloud platforms.

How the model fits together
  • Consumption, revenue mix, and delivery economics: Product revenue is recognized from actual platform consumption rather than contract duration. Product revenue mix separates that core consumption revenue from professional services, while product gross profit and margin show the direct economics of delivering the platform and professional-services margin remains economically distinct.
  • Existing-customer expansion and enterprise penetration: Net revenue retention tracks product-revenue change within a defined existing capacity-contract cohort, while million-dollar customer counts and Forbes Global 2000 penetration show how broadly the platform is scaling into large enterprise relationships. These measures use issuer-specific customer definitions and are not interchangeable.
  • Contracted demand and revenue conversion: Remaining performance obligations measure contracted revenue not yet recognized, while RPO growth, expected next-12-month recognition, and capacity-contract remaining life add growth and duration context. In a consumption model, these measures do not form a fixed revenue schedule because actual recognition depends on future customer usage.

See It in Company Research

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