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.
Aperçu
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.
À qui cela s'adresse
- 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
Notre approche de Digital Analytics
Les travaux précis que couvre une mission type. Le périmètre est convenu d'avance : rien ici ne réapparaîtra plus tard comme une ligne surprise.
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.
Du premier échange au résultat mesuré
Toujours la même séquence, pour que vous sachiez ce qui vient ensuite.
Audit
Review the current setup for accuracy, duplication and gaps, and reconcile against a known source.
Plan
Design the measurement plan against the questions the business actually asks.
Implement
Build and test the tracking, verifying each event rather than assuming deployment means working.
Report and monitor
Build the reporting layer and add monitoring so a broken tag is noticed within days.
Des résultats, pas des livrables
Un empilement de documents n'est pas un progrès. Voici les changements que le travail doit produire.
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.
Questions fréquentes sur Digital Analytics
Ce qu'on nous demande avant de nous contacter. Si votre question n'y est pas, posez-la nous directement.
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.
Vous réfléchissez à Digital Analytics ?
Dites-nous ce que vous cherchez à changer. Si nous ne sommes pas les bons interlocuteurs, nous vous le dirons et vous orienterons ailleurs.
Vous cherchez la vue d'ensemble ?
Digital Analytics accompagne généralement d'autres travaux en Data, Analytics & Measurement. Parcourez tout le domaine pour voir les liens.