Service 01 · Product Analytics

Product analytics your whole team can trust.

I design and implement the data foundation under your product — event taxonomy, tracking plan, and analytics setup — so you can finally answer why users activate, stick around, or leave.

The situation

You're probably here because…

×Your dashboards are full, but nobody quite trusts the numbers in them.
×Events were bolted on over time and nobody can say what half of them mean.
×Two people pull the same metric and get two different answers.
×You can't confidently say why users churn or which feature drives retention.
×Every analytics question turns into a multi-day engineering request.
×You're about to raise, and your metrics story needs to hold up to scrutiny.
What's included

Four ways to work together.

Four ways to work on your analytics foundation. Start wherever you are — most teams begin with a taxonomy and tracking plan.

01Project

Product-Led Approach Implementation

Bake a data-driven, product-led operating model into how your team actually works — not just the tooling, but the habits around it.

  • Metric framework and North-Star definition
  • Activation, retention and engagement models
  • Team rituals for reviewing and acting on data
  • Enablement so the team can self-serve
02Project

Data Taxonomy & Tracking Plan Design

A clean, documented event schema that scales with your product instead of collapsing under it — the single source of truth for what you track and why.

  • Event and property naming conventions
  • Full tracking plan mapped to user journeys
  • Documentation your engineers will actually use
  • Governance so it stays clean as you grow
03Project

Data Foundation & Platform Setup

Choose the right stack for your stage and get it instrumented correctly from day one — or fix an implementation that's already drifted.

  • Tool selection and migration planning
  • Implementation with your engineering team
  • QA and validation of event data
  • Core dashboards for product and growth
04Retainer

Ongoing Analytics Partner

Continuous senior analytics support — so insight keeps flowing without you hiring a full in-house data team.

  • Regular deep dives on product questions
  • Dashboard and reporting upkeep
  • Analysis for board and investor updates
  • On-call for the ad-hoc analytical asks
Outcomes

What you end up with

Numbers you trust

One definition per metric, documented and agreed — so meetings are about decisions, not about whose dashboard is right.

Answers in minutes

Your team self-serves the routine questions instead of queueing behind an engineer or waiting on a data request.

A foundation that scales

Tracking that still makes sense after three product pivots and ten new features, because it was designed to.

How I work

Goal-oriented and transparent, start to finish.

01

Dive in

I go deep on your product, market and goals before touching a single event.

02

Align

We set clear targets and a tight scope so we're aiming at the same thing.

03

Build

I become part of the team — in your tools and chat, doing the hands-on work.

04

Compound

Regular insight and iteration, with everything documented so it stays yours.

The stack

I work in the tools you already have — or help you choose better ones.

AmplitudeMixpanelPostHogGA4SegmentRudderStackBigQueryLookerMetabasedbt
FAQ

Questions founders ask about this.

How long does a tracking plan and taxonomy project take?

Typically four to eight weeks depending on product complexity and how much needs untangling. A focused audit of existing tracking is faster — usually one to three weeks.

We already have Amplitude/Mixpanel set up. Can you fix it rather than start over?

Yes, and that's the more common case. I'll audit what's there, work out what's salvageable, and migrate you to a clean taxonomy without losing your history where it matters.

Do you implement the tracking yourself or work with our engineers?

Both, depending on your setup. I design the plan and specs, then either work alongside your engineers through implementation or handle instrumentation directly in tools that allow it.

Which analytics tool should we use?

It depends on your stage, budget and stack — I'm tool-agnostic and will recommend based on your case, not a partnership. For most early-stage teams it comes down to Amplitude, Mixpanel or PostHog.

Is this useful pre-product-market-fit?

Very. Getting the foundation right early is far cheaper than untangling three years of accumulated tracking debt later, and it's what lets you learn quickly while you search for fit.

Ready to trust your product data?

Book a 20-minute intro call. Tell me what's broken in your analytics and I'll tell you honestly what it would take to fix it.

Book an intro call →
Also explore

The other two tracks.