The most widely used analytics platform in the world, and the one most organisations run on a fraction of its configuration.

Google Analytics (GA)

Google Analytics is the foundation of modern digital measurement. It helps organisations understand how customers discover, engage with and convert across websites, apps and digital experiences.

As marketing becomes more automated and privacy expectations continue to advance, the quality of your analytics implementation has a direct impact on reporting accuracy, attribution, audience creation and business decision-making.

Louder helps organisations design, implement and govern Google Analytics environments that remain reliable as platforms, privacy frameworks and customer journeys become more complex.

From GA implementations and Google Analytics 360 onboarding through to data architecture, BigQuery integrations and advanced measurement frameworks, we help teams move beyond basic reporting and build analytics infrastructure they can trust.

Whether you’re migrating to GA, improving data quality, creating executive reporting environments or connecting analytics with wider marketing and business systems, our team works across strategy, implementation and operational governance to ensure measurement supports better decision-making.

Why it matters

Marketing performance is increasingly shaped by the signals available to advertising and analytics platforms. Weak event tracking, inconsistent tagging, fragmented consent management and poor governance can reduce visibility, distort reporting and limit optimisation opportunities.

A well-configured Google Analytics environment provides a trusted source of truth for customer behaviour, conversion performance, audience insights and marketing effectiveness.

What Louder does

  • Implementation and migration — schema design, tagging through GTM against a specified data layer, and validation that the events actually carry what they claim to.
  • Property configuration — retention, attribution model and windows, reporting identity, cross-domain, internal traffic and referral exclusions, set deliberately rather than left at default.
  • Conversion architecture — what counts, and specifically which key events are permitted to feed Google Ads bidding.
  • Ecommerce and item-scoped tracking, reconciled against the transaction system rather than against itself.
  • BigQuery export — setup, modelling, and an honest account of why the export and the interface disagree.
  • Audit and remediation of an existing property, including the parts that cannot be fixed retrospectively.
  • Training and documentation so the client’s team can interpret the reports without a translator.

Common challenges

  • Data retention left at the default. Discovered when somebody asks for a two-year comparison that no longer exists and cannot be recovered.
  • Custom dimensions registered ad hoc. Slots are consumed as requests arrive, the cap is reached about a year in, and the choice becomes deleting historic dimensions or not measuring the new thing.
  • Personal information in event parameters. An email address or order detail passed as a parameter breaches Google’s terms and can result in data being purged from the property.
  • Cross-domain not configured. A checkout on a payment domain starts a new session as a referral, and every conversion in the funnel is misattributed to it.
  • The export and the interface compared without adjustment. Raw events are not sessions, and reconciling them is a modelling exercise rather than a bug hunt.