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AriaHelpDesk
Leistungsgruppe

Analytics & Data

Data-driven insights and measurement

Überblick

Most analytics setups were configured once, extended under pressure, and never audited. The data looks complete and is quietly wrong: duplicate events, internal traffic counted, conversions firing on page load. Everything built on top of it inherits the fault.

The work here is unglamorous and decisive. Design events around the decisions you actually make, validate the numbers against something you know is true, recover what browser restrictions have taken away, and then analyse rather than merely report.

Für wen das gedacht ist

  • Companies whose analytics disagrees with their own sales figures
  • Advertisers whose reported conversions fell without sales falling
  • Teams with several dashboards and no number anyone trusts
Fragen

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Why does our analytics not match our sales figures?

Usually a combination of consent rejection, ad blockers, cross-device journeys and attribution windows, plus implementation faults. A gap is normal; a large or unstable one indicates something fixable, and we quantify each cause rather than accepting it.

Can attribution tell us what caused a sale?

No. Attribution allocates credit among touchpoints you can observe, which is useful for steering. Causation needs a holdout test, and arguing about attribution models is usually a substitute for running one.

Do we need a customer data platform?

Less often than they are sold. For most mid-sized companies a well-integrated CRM plus a warehouse does the same job for considerably less.

  • Umsetzung über Märkte hinweg

    Teams, die in verschiedenen Regionen, Sprachen und Regulierungsrahmen geliefert haben.

  • Von Anfang an prüffähig

    Sicherheit, Barrierefreiheit und Datenschutz entstehen beim Bauen, nicht kurz vor dem Audit.

  • Gemessen statt vermutet

    In jedem Projekt steht die Erfolgskennzahl vor dem Start fest.