Shared definitions
Conversion, retention, and ops KPIs everyone agrees on.
Focus · BI & Analytics
Analytics that change next week's decisions.
Trusted metrics, practical pipelines, and product-integrated insight - so founders and ops leads aren't flying on vanity charts.
Outcomes
What success looks like.
Faster answers
Less waiting on ad-hoc spreadsheet pulls.
Insight in the product
Surfaces where operators already work.
Capabilities
How we deliver in this area.
Event instrumentation
Track what matters in apps and backends.
Pipelines & warehouses (right-sized)
Start small; grow when questions demand it.
Dashboards that get opened
Designed around decisions, not chart zoo aesthetics.
Predictive signals
When history supports forecasting or risk scores.
Experiment support
Instrumentation for A/B and feature flags.
Privacy-aware analytics
Minimize PII; respect consent and region rules.
How we run it
A clear path from brief to release.
Seniors stay close to the work. Status stays honest. The process bends to your stage.
01
Name the decision
What choice will this data change?
02
Inventory sources
Apps, DBs, sheets - and the gaps.
03
Deliver a thin loop
One pipeline and one surface people use.
04
Expand carefully
Add models and warehouses when baselines are solid.
Questions
Straight answers before you commit.
Do we need a full data team first?
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Do we need a full data team first?
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No. We often start with product analytics and a focused warehouse slice.
Can you feed our existing BI tool?
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Can you feed our existing BI tool?
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Yes - or build in-product views when operators never open the BI suite.