Clean data, before anything else
GA4, GTM, and BigQuery implementations that make every downstream decision trustworthy.
Analytics and tracking is configuring GA4, Google Tag Manager, conversion tracking, attribution, and UTM tagging as one verified system, then reporting the result with a specific recommendation, rather than trusting each platform's numbers at face value.
Why it comes first
Every engagement starts with a measurement audit. We've seen too many accounts where the "traffic increase" or "lead volume" being reported was actually a tracking bug - clean infrastructure isn't a nice-to-have, it's the only way to know if anything else we do is working. That starts with GA4 and Google Tag Manager configured to reflect how the business actually operates, not the default event set most properties ship with.
From there, conversion tracking gets reconciled against ad platforms and CRM data so bidding decisions are based on real outcomes, and attribution gets modelled against the actual sales cycle instead of a last-click default that starves every channel that isn't the final touch. Consistent UTM tagging keeps it all comparable over time, and dashboards turn the result into something a stakeholder can act on - not another wall of numbers.
Problems we solve in Analytics & Tracking
The default setup looks complete but is not
Enhanced measurement fires automatically, making it easy to assume tracking works when it cannot answer a real business question.
Only one person understands the setup
If the original builder leaves, nobody else can safely add a tag or diagnose a broken one.
Conversions counted differently, or twice
Each ad platform uses its own attribution logic, so the same purchase or lead can get counted more than once.
Upper-funnel channels look unproductive
A default last-click model gives all the credit to whatever was clicked last, so channels that were actually contributing get cut.
The same campaign fragments into several rows
Inconsistent UTM tagging splits one campaign into multiple variants depending on who tagged the link.
Reports end in a wall of numbers, not a decision
Data gets delivered without interpretation, an anomaly, or a stated next action.
Everything covered in Analytics & Tracking
GA4
Events, dimensions, and e-commerce tracking configured to match your specific business model, not just the defaults.
Google Tag Manager
A documented, well-structured container with a real data layer, so tracking survives beyond whoever built it.
Conversion Tracking
Conversion events configured and reconciled across ad platforms and CRM so spend decisions reflect real outcomes.
Marketing Attribution
A credit model matched to your actual sales cycle, so upper-funnel channels get credit for the work they do.
UTM Management
A governed naming convention and enforcement so campaign data stays comparable over time.
Marketing Dashboards
Automated Looker Studio dashboards built around specific business questions, not a generic template.
Reporting & Insights
Performance reports that pair the numbers with analysis and end in a specific recommendation.
What actually changes
| Before | After |
|---|---|
| Only automatically collected events are captured | Events map to real business actions and are validated against source systems |
| Only the original builder understands the tracking setup | A documented container and event map anyone on the team can maintain |
| The same conversion counted on multiple ad platforms | Conversions reconciled against CRM records and de-duplicated |
| All credit given to the final click before conversion | Credit modelled to match the actual sales cycle |
| The same campaign fragments into several rows depending on who tagged it | One governed naming convention, one campaign, one row |
| Numbers exported and pasted manually every period | Dashboards refresh automatically and reports end in a recommendation |
What we report on
Data validation gap
The documented, explainable difference between what platforms report and what CRM or order data actually shows.
Duplicate & match rate
Tracked across ad platforms to catch double-counted conversions before they skew bidding.
Channel credit distribution
Reported by how credit shifts once upper and mid-funnel touchpoints are counted correctly.
Campaign data consistency
Measured by how many campaigns report as one unified row versus fragmented variants.
Manual reporting time eliminated
The recurring export-and-paste work an automated dashboard was built to replace.
Tools we work with
Every Analytics & Tracking service, broken down
Get GA4 Data You Can Actually Trust and Act On
We build the events and dimensions that answer your real business questions, not just the GA4 defaults.
Google Tag ManagerOne place to manage every tag, cleanly
GTM implementation and container management so every tracking tag is documented, tested, and reliable.
Know which conversions actually count
Conversion tracking configured across ad platforms and analytics so spend decisions are based on real outcomes.
Stop Cutting Channels That Were Actually Working
We model attribution around your real sales cycle, so upper-funnel channels get credit for the work they're actually doing.
UTM ManagementConsistent tagging is the whole point
UTM naming conventions and governance so campaign data stays clean and comparable over time.
One dashboard, not five exported spreadsheets
Looker Studio dashboards that answer specific business questions, refreshed automatically.
Get Reports That End in a Decision, Not a Wall of Numbers
Every report we send pairs the numbers with a clear, specific recommendation - not just data.
Industries we work with
Built for teams like yoursPairs well with Analytics & Tracking
Turn Search Into a Channel That Compounds, Not One You Rebuild Every Quarter
Technical foundations and AI-era search readiness - traffic that keeps paying off long after a campaign ends.
Get more from the traffic you already have
Systematic conversion testing across landing pages and funnels, not one-off redesigns.
Know what to measure before you decide how
Measurement strategy, attribution, tracking architecture, and data strategy built before implementation, not after.
Why choose EASI7
We fix tracking before we touch results
Every engagement starts with the same audit we'd run on our own accounts, so the numbers you're optimizing against are actually true.
One accountable team, not siloed vendors
The same team that does this also owns the rest of your stack - no handoff, no blame-shifting between vendors.
Built for how AI search actually works
Everything we build is structured to be extractable by AI answer engines, not just ranked in a list of blue links.
Reporting tied to your own dashboard
Every number we report ties back to GA4/GTM events you can see directly - not a screenshot from a tool you can't independently verify.
How to engage us for this
Project-based
A defined outcome with a start and end date - an audit, a migration, a campaign build, a tracking overhaul. Fixed scope, fixed price, agreed upfront.
Ongoing retainer
Continuous management and optimization once the initial build is live - campaigns, SEO, reporting, and iteration run every month under one accountable team.
Advisory
Strategy and oversight without full delivery - we review what's already running, unblock decisions, and point an in-house or existing team in the right direction.
Common questions
Having GA4 installed and having it configured correctly are different things. Most accounts we audit have the platform running but are missing conversion events, proper attribution, or a data layer - meaning the numbers look complete but aren't trustworthy.
A standard implementation with a proper data layer typically takes one to two weeks, depending on how many conversion events and integrations are involved.
Universal Analytics data itself can't be migrated into GA4 directly since they're structurally different platforms, but we can export and preserve historical UA data separately for reference while GA4 builds its own history going forward.
GA4 and GTM are the most common starting point, but we also work with PostHog for product-led tracking and BigQuery as a warehouse layer when reporting needs exceed what native connectors handle. The platform matters less than whether the underlying event structure is sound.
No - some gap between what happens and what gets recorded is unavoidable, due to ad blockers, consent choices, and cross-device behaviour no tracking system fully solves. What we guarantee is that the gap is known and documented, not hidden, so decisions are made with an honest picture instead of a false sense of precision.
Not sure your tracking is actually accurate?
Every engagement starts with a measurement audit - we'll tell you if the numbers you're already reporting can be trusted.
Ready to get started?
We usually reply within 24 hours.
Analytics & Tracking, in detail
Scope, area by area
| Area | What we deliver |
|---|---|
| Foundation | GA4 and GTM configured and documented around real business actions and events |
| Conversion Accuracy | Cross-platform conversion tracking reconciled against CRM and de-duplicated |
| Attribution & Tagging | Multi-touch attribution modelled to your real sales cycle, plus governed UTM tagging |
| Reporting | Automated dashboards and analysis-led reports that end in a specific recommendation |
How this compares
| Analytics Built as One System | Analytics as Disconnected Tools |
|---|---|
| Every layer - events, conversions, attribution, tagging - is verified against a source of truth | Each platform is trusted at face value with nothing reconciled against another |
| A documented setup anyone on the team can maintain | Tracking depends entirely on whoever originally built it |
| Every report ends in a specific recommendation | Numbers get delivered with no stated next action |
Clean data is not a nice-to-have step before the real work - it is the only way to know whether anything else being measured is actually true.
What we measure this against
- The documented, explainable gap between what platforms report and what CRM or order data actually shows
- Which layer - events, conversions, attribution, or tagging - is actually the source of an inaccurate number
- Whether reports and dashboards are being acted on, not just opened
Where this applies
- A business scaling ad spend that needs confidence the conversion numbers justifying it are real
- A team about to cut a channel budget based on a last-click report that may be undercrediting it
- A growing marketing team that inherited an undocumented GTM container or fragmented UTM tagging
- Leadership wanting one dashboard instead of reassembling five platform exports every month