ARCHE DIGITAL MEDIA
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// SERVICE 04 · ANALYTICS

Marketing analytics that drives decisions, not dashboard sprawl.

Senior-led marketing analytics for businesses drowning in data and starving for insight. GA4 architecture, attribution modelling, server-side tagging, and BigQuery integration — built around the questions your business actually needs answered.

// PLATFORMS WE OPERATE ACROSS
GA4
GTM Server
BigQuery
Looker Studio
Conversions API
MMM via Robyn
// THE PROBLEM

Why most marketing data doesn't drive decisions.

Most companies have more data than ever and less clarity than they had five years ago. The dashboards multiply, the meetings stretch, and the actual decisions still come down to gut feel.

GA4 broke most companies' analytics setups when it forced the migration from session-based to event-based measurement. Conversion tracking that worked for years suddenly didn't. Attribution models reset. Reports that took an hour to build now take a day. Three years in, most accounts are still patched together with duct tape — events firing twice, channel groupings misconfigured, audiences not syncing properly.

Three patterns show up in every analytics audit. One: conversion events double-counted across pixel, server-side, and CRM imports — every channel claims the same revenue. Two: attribution stuck on last-click in GA4 despite Google rolling out data-driven attribution as the default in 2023. Three: data sitting in 8-12 different platforms with no unified view, so every cross-channel question becomes a manual spreadsheet exercise.

Worse, the analytics function in most marketing teams has become a reporting bottleneck rather than a decision engine. Someone pulls the numbers. Someone formats the slides. Someone answers ad-hoc questions. Nobody actually moves the business with what the data says, because the data is never trusted enough to act on.

Fixing this isn't a tooling problem — it's an architecture problem. That's what we rebuild.

// HOW WE WORK

Our six-step Marketing Analytics & Insights methodology.

Every engagement follows the same architecture, calibrated to your business model, customer economics, and operational constraints.

01

Analytics audit & data inventory

Map every tracking surface: pixels, server-side tags, GA4 events, conversion APIs, CRM integrations, ad platform conversion uploads. Identify deduplication issues, broken events, attribution conflicts. Document where data is trustworthy and where it isn't.

02

Measurement architecture

Redesign the tracking layer with GA4 as the source of truth, server-side tagging via GTM Server for resilience to ad blockers and iOS 14+, and unified event taxonomy across all platforms. Single conversion definition that flows everywhere consistently.

03

Attribution modelling

Move to data-driven attribution in GA4 for cross-channel credit. For clients with sufficient spend, implement marketing mix modelling (MMM) for true cross-channel truth. Geo-holdout incrementality testing for high-spend channels to validate platform claims.

04

Data warehousing & BI

GA4 to BigQuery export for unlimited historical analysis and joins with CRM, financial, and operational data. Looker Studio or Tableau for executive dashboards. Data modelled around business questions, not platform reporting conventions.

05

Activation & audience sync

Customer data flowing back into ad platforms for value-based bidding: customer match, enhanced conversions, offline conversion imports, server-side conversions API. Analytics that fuels media performance, not just measures it.

06

Reporting & decision cadence

Move from dashboard sprawl to written weekly business reads — what changed, what we tested, what we recommend. Monthly executive reviews built around three to five strategic questions, not 40 chart-tiles nobody looks at.

// WHAT'S INCLUDED

Everything in a Marketing Analytics & Insights engagement.

  • GA4 architecture & rebuild — event taxonomy, conversion definitions, channel groupings, custom dimensions
  • Server-side tagging — GTM Server container deployment on Cloud Run or App Engine
  • Conversions API integration — Meta CAPI, Google Enhanced Conversions, TikTok Events API, Pinterest CAPI
  • BigQuery data warehousing — GA4 export, custom data ingestion, scheduled queries, cost optimisation
  • Looker Studio dashboards — executive, marketing, channel-specific views built around real decisions
  • Data-driven attribution — configuration, validation, channel grouping refinement
  • Marketing mix modelling (MMM) — for clients with sufficient cross-channel spend
  • Incrementality testing — geo-holdout design, statistical power analysis, lift measurement
  • Cross-domain & subdomain tracking — with proper UTM hygiene and session stitching
  • CRM integration — HubSpot, Salesforce, Pipedrive, custom CRMs for offline conversion imports
  • Weekly written analytics reports — actual insight, not auto-generated dashboard exports
  • Direct analyst access — senior data specialist, no junior account manager
// PROVEN ACROSS

Industries we've delivered analytics for.

Senior specialists with hands-on operator experience across the verticals that matter most.

Retail & E-commerce

Multi-SKU catalogues, margin-aware bidding, seasonal demand modelling. Clients include Best&Less, Runaway The Label, Ozmobiles, and Icon By Design.

Health, Fitness & Supplements

TGA-compliant claims, subscription LTV optimisation, conversion-quality tracking. Clients include Fitness First, Body Science, The Man Shake, and Zap.

Travel, Auto & Services

Geo-targeted intent, seasonal demand, lead-quality measurement. Clients include Hertz and iBuyNew.

B2B & Lead Generation

Long sales cycles, CRM-integrated measurement, MQL-to-SQL pipeline modelling, offline conversion imports.

// RESULTS

What senior-led marketing analytics & insights delivers.

+215%
Attributed revenue recovery
DTC ecom client. Server-side tagging deployment + Conversions API rebuild + event deduplication.
7.4×
Reporting efficiency
B2B SaaS client. Replaced 14 disconnected dashboards with one BigQuery-backed analytics layer.
−42%
Customer acquisition cost
Retail client. Customer match audiences + value-based bidding fed by GA4 to BigQuery to Ads.
// ENGAGEMENT

How pricing works.

Marketing analytics is offered as either project-based work (architecture rebuilds, MMM implementations) or ongoing retainer. Retainers start from $3,500/month + GST, calibrated to data volume and stakeholder reporting load. Project work is quoted on scope.

Server-side tagging infrastructure (GTM Server on Google Cloud) typically runs $50-200/month in cloud costs, billed pass-through. BigQuery storage and query costs depend on data volume but generally remain under $200/month for typical mid-market scenarios.

We don't sell analytics as a feature of a paid media engagement. It's its own discipline with its own specialists. Bundling analytics into media management almost always means analytics becomes the part that gets cut when the work compresses.

Every engagement starts with a free analytics audit valued at $2,000. You get a written report identifying broken tracking, attribution issues, and data architecture problems — implementable independently of working with us further.

// QUESTIONS

Marketing Analytics & Insights FAQs.

Do we need server-side tagging?+

Probably yes if you're spending more than $20k/month on paid media. Server-side tagging recovers 10-30% of conversions lost to ad blockers, iOS Intelligent Tracking Prevention, and pixel firing failures. It also future-proofs your tracking against ongoing browser privacy changes.

What's the difference between MMM and MTA?+

Multi-touch attribution (MTA) uses individual user journeys to assign credit — increasingly broken in a privacy-first world. Marketing mix modelling (MMM) uses aggregate spend and outcome data over time, statistically modelling channel contribution without needing user-level tracking. MMM is making a comeback for that reason. Most mature programmes use both: MTA for tactical optimisation, MMM for strategic budget allocation.

Is GA4 actually trustworthy?+

Yes, if it's set up correctly — which most accounts aren't. Out-of-the-box GA4 has consent mode issues, sampling at high volume, attribution defaults that under-credit assisted conversions, and event taxonomy that bears little resemblance to your business model. Trust comes from the rebuild, not the platform.

How much does BigQuery cost?+

Storage is roughly $0.02 per GB/month — most clients run $20-100/month in storage. Query costs depend on usage patterns but typically run $50-300/month with proper query optimisation. Cheaper than most marketing reporting tools and infinitely more flexible.

Should we build this in-house or outsource?+

Both, eventually. The architecture build is specialised one-off work — outsource. Ongoing reporting cadence and decision-making should be in-house — your team needs to own the data layer to act on it. We build the foundation and train your team to operate it.

Do you handle MMM in-house?+

We deliver MMM through partnerships with specialist statistical consultancies for clients spending $200k+/month in media. Below that level, MMM is statistically underpowered and the cost outweighs the insight. For most clients, geo-holdout testing and proper MTA delivers comparable strategic value at a fraction of the cost.

Can you work with our existing martech stack?+

Yes. We're tool-agnostic across most major platforms: Google Cloud, AWS, Azure for data warehousing; Looker, Tableau, Power BI for visualisation; HubSpot, Salesforce, Pipedrive for CRM; Segment, Tealium for CDP; rudderstack, Snowplow for open-source tracking. The discipline is the same — the tooling is a choice.

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