Analytics Consulting
Measurement systems built to drive decisions, not reports.
Overview
How I approach this work
I have designed measurement frameworks across SaaS, marketplaces, and subscription products — defining KPIs, building funnel models, and tracking the metrics that shift decisions. Analytics engagements I take on usually involve pruning the vanity numbers a team has accumulated and replacing them with a smaller set that actually drives action. The goal is to leave behind a system the team can run off of.
The first step in an analytics engagement is almost always an instrumentation audit — what is being tracked, where it is going, and how much of it is trustworthy. From there I map the business model to a KPI tree: conversion, AOV, LTV, churn, engagement — whichever set actually describes how the company makes money. That becomes the input to dashboards and alerts that people actually look at, and to A/B testing and experimentation frameworks that can measure whether changes move the needle. I have done this across four-plus SaaS products with their own funnel shapes, and the work transfers well across verticals.
Deliverables
What a typical engagement produces
Concrete artifacts from this kind of work.
- Instrumentation audit
- A complete audit of current tracking with a list of broken events, redundant tags, and measurement gaps — prioritized by impact on decisions.
- KPI and dashboard system
- A reviewed KPI tree mapped to the business model, with dashboards and alerts that highlight the metrics that should move each week and how much.
- Experimentation framework
- A documented approach for running A/B tests and interpreting results — including sample size guidance and a template for writing test hypotheses that are falsifiable.
- Years in analytics and growth
- 4+
- SaaS KPI trees designed
- 6+
- Tools
- PostgreSQL, custom dashboards
Related areas
Other parts of my practice that overlap with this one.
Performance Consulting
Infrastructure and web performance that shows up in the numbers.
AI Consulting
Practical AI integration, tested in production.