Technology and SaaS analytics. The SaaS metrics layer, governed pipeline and revenue reporting, and AI readiness for fast moving B2B companies.
Data team scaling: hiring plans, tooling decisions, and operating models
No unified customer health model connecting product usage, support, and billing data
How do you resolve ARR discrepancies between finance and product teams?
We build a single certified ARR definition in a semantic layer that both finance and product teams consume. We document every business rule, handle edge cases like multi-year contracts and mid-period expansions, and create a reconciliation process that makes discrepancies visible and resolvable before they reach the board.
Can you help us build a product analytics stack from scratch?
Yes. We help early-stage and growth-stage SaaS companies design and build their product analytics infrastructure on modern tools like Snowflake, dbt, and Looker. We make tooling decisions based on your current scale and growth trajectory, not on what is most complex.
Most SaaS metrics layer engagements run 8 to 12 weeks. The scope is typically smaller than enterprise data foundation projects because the data environment is more modern. We start with a 30-day Analytics Truth Audit that identifies the specific metric inconsistencies before any build work begins.
Do you work with early-stage startups or only growth-stage companies?
We work across the full SaaS lifecycle. Early-stage companies typically need help building the right foundation before bad habits become entrenched. Growth-stage companies typically need help cleaning up metric inconsistencies that emerged as the business scaled. Both are solvable.
Technology and SaaS data analytics consulting. Build the SaaS metrics layer, product analytics infrastructure, and revenue attribution models investors trust.
Data and analytics consulting for SaaS and tech companies. Product, pipeline, and ARR metrics.
SaaS companies live and die by their metrics: ARR, NRR, churn, CAC, LTV. We build the metric layer that makes these numbers consistent across product, finance, and go-to-market teams, and defensible in a board room.
Start with a 30-day Analytics Truth Audit. We identify exactly what is broken and give you a 90-day roadmap to fix it.