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Analytics & Data

Digital Analytics

Analytics implemented so the numbers can be trusted: events designed deliberately, consent handled correctly, and reporting that answers a question someone actually asked.

Panoramica

Most analytics setups were configured once by whoever had access, extended a few times under pressure, and have not been audited since. The result is data that looks complete and is quietly wrong: duplicate events, self-referring traffic, internal visits counted, and conversions firing on page load.

Fixing it is mostly discipline rather than cleverness. Design the events around the questions you ask, implement them consistently, validate against something you already know is true, and then remove the reports nobody opens.

A chi è rivolto

  • Companies whose analytics disagrees with their own sales figures
  • Teams who migrated to GA4 hastily and never revisited it
  • Businesses with several dashboards and no trusted number
Cosa è compreso

Il nostro approccio a Digital Analytics

Le attività concrete che comprende un incarico tipo. Il perimetro si concorda prima: nulla di quanto elencato ricompare più avanti come voce a sorpresa.

  • Measurement plan

    The events and properties you need, derived from the decisions you make, written down before anything is implemented.

  • Implementation

    Consistent event naming and parameters through a tag manager or directly in code, with a data layer that is designed rather than accumulated.

  • Validation

    Checking reported numbers against a source you trust, such as order records. Analytics that has never been reconciled is not evidence.

  • Consent integration

    Consent mode and correct behaviour before permission is given, which is both a legal requirement and a large influence on what data you have.

  • Filters and hygiene

    Internal traffic, bots and referral spam excluded, which is a small job that removes a surprising amount of noise.

  • Reporting

    A small set of reports tied to real decisions, and the removal of the ones nobody opens.

Come procede

Dal primo contatto al risultato misurato

Sempre la stessa sequenza, così sapete cosa viene dopo.

  1. Audit

    Review the current setup for accuracy, duplication and gaps, and reconcile against a known source.

  2. Plan

    Design the measurement plan against the questions the business actually asks.

  3. Implement

    Build and test the tracking, verifying each event rather than assuming deployment means working.

  4. Report and monitor

    Build the reporting layer and add monitoring so a broken tag is noticed within days.

Perché conviene

Risultati, non pile di documenti

Un cumulo di deliverable non è progresso. Questi sono i cambiamenti che il lavoro deve produrre.

  • Numbers people believe

    Reconciliation against a known source is what ends the meetings that are really arguments about data quality.

  • Fewer reports, more use

    Cutting unused dashboards makes the remaining ones visible and maintained.

  • Data that is lawful

    Correct consent handling protects you and improves data quality at the same time.

  • Breakage caught early

    Monitoring means a failed tag is a small problem rather than a quarter of missing data.

Domande

Domande frequenti su Digital Analytics

Quello che ci chiedono prima di contattarci. Se la vostra domanda non c'è, fatecela direttamente.

Why does GA4 not match our sales figures?

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

Should we use something other than GA4?

Alternatives exist that are simpler and more privacy-friendly, and for some businesses they are a better fit. GA4's advantage is its integration with advertising platforms. If you spend heavily on Google advertising, moving away has real costs beyond the tool itself.

How is this different from your data strategy service?

This is implementation: collecting data correctly and reporting it. Data strategy and measurement decides what is worth measuring at all and defines the metrics. If your problem is that two teams report different numbers for the same thing, start there.

How long does an analytics rebuild take?

Audit and plan in two to three weeks, implementation another two to four depending on how many systems are involved. Validation is what takes the time and is the part worth protecting.

State pensando a Digital Analytics?

Diteci che cosa volete cambiare. Se non siamo i partner giusti ve lo diciamo e vi indichiamo di meglio.

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