Enterprise Foundations
Every measure stays connected to product meaning
Collecting more events does not create clarity when definitions, ownership, tenant context, and decisions drift across analytics tools. Teams end up debating numbers instead of acting on them.
Available
Book a DemoInspectable package · explicit boundaries · focused fit check
The promised outcome
Turn product behavior into decisions you can act on.
Add a usable path from product behavior to shared measures, analysis, and action.
Event contracts
Define actors, actions, objects, time, and tenants.
Collection and validation
Keep malformed signals out of models.
Analytical storage
Separate workloads while retaining identifiers.
Shared measures
Give every KPI an owner and guardrail.
The problem this solves
SaaS teams that need trustworthy product and operating analytics without creating a second data product. Collecting more events does not create clarity when definitions, ownership, tenant context, and decisions drift across analytics tools. Teams end up debating numbers instead of acting on them. Leave it unresolved and the cost compounds: Conflicting KPI definitions erode trust in every dashboard. Missing product and tenant context makes attribution impossible. Analytics work becomes another disconnected platform to operate.
What Analytics Foundation puts in place
A bounded, inspectable package—not a vague transformation program.
Event contracts
Define actors, actions, objects, time, and tenants.
Collection and validation
Keep malformed signals out of models.
Analytical storage
Separate workloads while retaining identifiers.
Shared measures
Give every KPI an owner and guardrail.
Dashboards
Use consistent views for trends and operating state.
Governance
Apply access, consent, lifecycle, and cost rules.
How this creates leverage
Analytics Foundation: how the package removes recurring work
The value comes from connected constraints and operating decisions that continue working after delivery.
- 01Events begin with actor, action, object, tenant, and time contracts rather than dashboard requirements.
- 02Metric definitions, ownership, guardrails, and presentation travel together.
- 03Operational and product analytics remain separate workloads while retaining common identifiers.
- 04The first implementation is tied to a real decision, so collection has an immediate reason to exist.
Inspect the package, understand its boundary, and buy only when it removes your constraint.
The product and its limits should be clear before you commit.
See the thinking and work behind the package
Use relevant articles, lead magnets, and case studies to evaluate the approach before we talk.
Usage attribution
Trace consumption to product, customer, cost, and outcome.
Read the field guideThe CTO metric system
Build decision measures without turning teams into a leaderboard.
Read the field guideCatalina case study
See analytics evolve into a real-time campaign and activation platform.
Read the field guideBefore you buy
Quick answers about fit, scope, and evaluation
The useful questions to answer before adding this package to your product foundation.
Who is this package built for?
SaaS teams that need trustworthy product and operating analytics without creating a second data product.
What does the package make possible?
Add a usable path from product behavior to shared measures, analysis, and action.
Can I inspect what is included first?
Yes. Events, dimensions, metric definitions, ownership, and visualization ship together instead of drifting across tools.
What is intentionally outside the package?
The foundation delivers event, measure, governance, and dashboard patterns. Historical warehouse migration and bespoke enterprise KPI programs are separate engagements.
How do I evaluate it against my product?
Book a demo focused on your product events and decision model.
See the package in your product context
Book a demo focused on your product events and decision model.