Data Strategy & Measurement
Deciding what is worth measuring, defining it once so everyone agrees, and building tracking that survives privacy changes and platform updates.
Überblick
Most companies measure too much and decide too little. Dashboards proliferate, definitions drift between teams, and nobody trusts the number enough to act on it.
We work backwards from the decisions you make regularly. Each one needs a small number of measures, defined precisely, collected reliably. Everything else is optional, and cutting it makes the rest visible.
Für wen das gedacht ist
- Companies where two teams report different numbers for the same thing
- Businesses whose tracking broke with a privacy or platform change
- Teams with plenty of dashboards and no decisions being made from them
Unser Vorgehen bei Data Strategy & Measurement
Die konkreten Arbeitspakete eines typischen Projekts. Der Umfang steht vorab fest, nichts davon taucht später als Überraschung auf der Rechnung auf.
Decision inventory
The decisions you actually make and how often. Measurement that does not serve a decision is overhead.
Metric definitions
Each measure defined in one place, in words, including the edge cases. This is what ends the disagreements.
Tracking implementation
Event design and tagging built to be maintainable, with server-side collection where the browser can no longer be relied on.
Attribution approach
A model matched to your sales cycle and honest about its limits. Last click is not wrong so much as narrow.
Privacy and consent
Consent handling and data retention designed in from the start, which is both a legal requirement and a data quality question.
Reporting layer
A small number of reports people actually open, each tied to a decision and a review cadence.
Vom ersten Gespräch zum gemessenen Ergebnis
Immer dieselbe Reihenfolge, damit Sie wissen, was als Nächstes kommt.
Audit
What is tracked now, what is broken, and which numbers are being reported that nobody can reproduce.
Define
The decision inventory and the measurement framework, agreed with the teams who will have to live with the definitions.
Implement
Tagging, server-side collection and consent handling, built and validated against known values rather than assumed correct.
Operate
Reporting, a review rhythm, and monitoring so that when tracking breaks, somebody finds out that week.
Ergebnisse statt Aktenordner
Ein Stapel Dokumente ist kein Fortschritt. Das hier sind die Veränderungen, die die Arbeit bewirken soll.
One number per question
Shared definitions end the meetings that are really arguments about arithmetic.
Measurement that lasts
Server-side collection and proper consent handling mean the next browser change does not erase your data.
Fewer dashboards, more use
Cutting reports nobody opens makes the remaining ones visible and, more importantly, maintained.
Faster decisions
When the number is trusted, the meeting is about what to do rather than whether the data is right.
Häufige Fragen zu Data Strategy & Measurement
Was Kundinnen und Kunden fragen, bevor sie sich melden. Fehlt Ihre Frage, stellen Sie sie uns direkt.
Our analytics broke after a privacy change. Can you fix it?
Usually. That normally means moving critical measurement server-side and rebuilding consent handling so that what you do collect is lawful and complete. It is a common starting point.
Do we need a data warehouse?
Not always. It becomes worthwhile when you need to join marketing data to sales or product data, which is often but not universal. We will say if you do not need one.
How long does implementation take?
Audit and framework in three to four weeks. Implementation depends on how many systems are involved, typically another four to eight.
Which tools do you use?
Whatever you already have, where it is adequate. GA4, server-side tagging, and a warehouse when justified. We do not have a platform to sell you.
Data Strategy & Measurement im Kopf?
Sagen Sie uns, was sich ändern soll. Passen wir nicht, sagen wir das und nennen Ihnen eine bessere Adresse.
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