Measurement

“We don't trust our numbers.”

Amplitude says one thing, the ad platforms say another, and the board deck uses a third. Nobody trusts the dashboards, so decisions quietly fall back to gut feel. The fix is not another dashboard. It is a measurement foundation that holds up when someone actually checks it.

The symptoms

You probably recognise a few of these.

Two "sources of truth" disagree and no one can say which is right.
Conversions in the ad platform do not match conversions in analytics, so you are optimising spend on numbers you do not believe.
Revenue in the warehouse does not tie back to the campaigns that drove it.
Every new report needs an analyst to reverse-engineer what an event actually means.
Tracking breaks silently on a deploy and you find out weeks later.

Event stitch · Amplitudeunified

Front endPage ViewedCTA Clicked

BackendOrder CreatedPayment Received

UTM · referrer · conversion before identity

What I build

Event schemas designed around the questions you actually need answered. Not a generic template lifted from someone else's stack.
Tracking implemented across web, product, and backend sources. The same event means the same thing everywhere it fires.
Attribution that survives scrutiny, including before the user identifies. Front-end clicks still tie back to revenue.
Reporting tied to revenue, not vanity metrics. The numbers a board actually asks about.
Documentation your next hire can pick up without a handover call. Handover, not lock-in.

Capabilities

The specific, findable things I do inside this. Open one for detail.

Analytics and event tracking implementation

Instrumented cleanly across web, product, and server, so every event means the same thing wherever it fires. I implement against a documented plan rather than sprinkling tags ad hoc, which is what keeps the data trustworthy months later. The result is a foundation your team and your tools can both rely on.

Segment
GTM
GA4
Mixpanel
Amplitude

Tracking plan and event-schema design

A documented schema built around the questions you actually need answered, not a generic template lifted from someone else's stack. Every event and property is named and defined once, so the same thing means the same thing everywhere it fires. Your next hire can read it and understand the data without a handover call.

Segment
Mixpanel

Marketing attribution

Attribution that survives scrutiny, including pre-identity front-end to back-end stitching, so a conversion ties back to its source before the user ever logs in. I unify the click and the conversion on a shared identifier instead of guessing across disconnected tools. That means spend decisions rest on numbers you can actually defend.

Amplitude
GTM

Server-side and first-party tracking

Resilient collection that survives ad blockers and browser privacy changes by moving key events server-side and first-party. As third-party cookies and client-side tags keep degrading, this is what stops your data quietly thinning out. You keep measuring the customers you would otherwise lose to blocked scripts.

Segment
GTM

Dashboards and reporting

Reporting tied to revenue and the metrics a board actually asks about, not vanity numbers that look good in isolation. I build the views in the tools you already use, so nobody has to reverse-engineer what a chart really means. The reports hold up when someone senior starts asking where a number came from.

Looker
Metabase

Tracking audits and QA

Validated against DevTools and the real network requests, not just "it fires" in a tag-manager preview. I check that events carry the right properties and values under real conditions, on real pages. Silent breakages get caught here instead of weeks later in a report that looks wrong.

How this kind of engagement runs

A short discovery to audit what exists: tools, tags, data flows. Then a designed schema, then implementation and QA against the real world, validated against DevTools, not just "it fires." Project or retainer. You work directly with me.

Tools I reach for

Segment
GTM
Mixpanel
Amplitude
GA4
Looker
Metabase

Related proof

DTC / Ecommerce

From spreadsheet reporting to a live growth stack

The problem

A DTC brand ran paid across Meta and Google, reported in spreadsheets, and had no idea which channel actually drove repeat purchases. Front-end clicks and back-end conversions lived in different systems, so nothing tied cleanly to revenue.

What I built

I designed the event schema, stitched front-end and back-end conversions on a shared transaction ID so attribution held before a user ever identified, and piped everything into a warehouse.

The result

Revenue tied back to the campaigns that drove it, and closed-loop reporting was live in four weeks.

4 wksto closed-loop reporting

Explore other services

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Let's look at your stack.

A 30-minute call. You describe the mess; I'll tell you honestly whether I can help.

Book an intro call