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Conversion numbers in GA4 that don’t match the numbers in Google Ads. Usually a tag-firing-twice issue or a deduplication gap on cross-platform conversion events.
See how customers are finding your business, what's turning visitors into leads and sales, and where your biggest opportunities for growth exist. GA4, GTM, and custom dashboards turn your website and marketing data into clear, actionable insights that help you make smarter business decisions.
Every interaction on your site flows through a small set of systems before it ever reaches a dashboard. When any one of them is misconfigured, everything downstream is unreliable. Click any node to see what it does.
Every click, scroll, form submission, and purchase begins here. The goal is to capture the right events at the right time, with the right context — so the rest of the pipeline has something meaningful to work with.
GTM sits between your site and every analytics tool downstream. Done well, it's a single point of control for every script on your site. Done poorly, it's where data quality quietly falls apart.
GA4 is where your events get stored, aggregated, and attributed. It's also where most implementations break. Default configurations don't capture what most businesses need, and the interface hides as much as it shows.
When GA4's interface stops answering your questions, BigQuery starts. Raw event-level data, SQL-queryable, joinable with CRM or ad platform exports. The difference between "roughly how many conversions" and "exactly which touch led to which sale."
The final layer — where data becomes decisions. Custom dashboards pulling from GA4, Search Console, ad accounts, and BigQuery, organized around the questions you ask. Just the numbers that matter, clearly.
Most businesses are collecting more data than ever — but important gaps in tracking, attribution, and reporting often make it harder to understand what's actually driving leads and revenue. These are six of the most common issues I uncover in audits that, once fixed, can lead to clearer insights, better marketing decisions, and more confident growth.
Conversion numbers in GA4 that don’t match the numbers in Google Ads. Usually a tag-firing-twice issue or a deduplication gap on cross-platform conversion events.
Form submissions or phone calls that don’t show up in the funnel at all. The marketing dashboard tracks pageviews, the actual revenue events are invisible. The funnel reports look fine; the math underneath is missing the most important rows.
Bot traffic and referral spam polluting reports. Inflates session counts, deflates conversion rate, makes every channel-mix decision noisier than it needs to be. GA4’s defaults filter some but not all.
Cross-domain tracking broken on subdomains, checkout flows, or third-party booking widgets. Users get reassigned new client IDs mid-session, attribution falls apart at the conversion step.
Universal Analytics–style metrics still being reported on out of habit. GA4’s event model is genuinely different; bounce rate, session duration, and goal completions don’t mean what they used to. Reports built on those metrics drift quietly out of usefulness.
Enhanced conversions, server-side tagging, and consent mode left unconfigured. Browser-side tracking alone is leaking 20–40% of conversion data on most sites by 2026 standards. The fix is mechanical; the gap is invisible until it’s closed.
Most accounts use some combination of these four tools. The question is which combination, in which order, and at what scale — the answer changes with how big the business is and how many questions the data has to answer.
| GA4 | GTM | Looker Studio | BigQuery | |
|---|---|---|---|---|
| Best for | Default analytics + reporting | Tag deployment + governance | Custom dashboards + sharing | Raw event data + custom queries |
| Setup complexity | Low–medium | Medium | Low (with clean GA4) | Medium–high |
| Cost | Free | Free | Free | Pay-per-query (typically <$10/mo for GA4 export) |
| When you need it | Always | Always (any tracking beyond pageviews) | When reports need to land outside GA4 | When the GA4 UI runs out of answers |
| Common failure mode | Default config doesn’t capture business events | Tag chaos: double-firing, data layer drift | Disconnected from source-of-truth GA4 | Complex SQL with no governance |
For most engagements, GA4 + GTM + Looker Studio is the right starting trio. BigQuery enters the picture when GA4’s interface stops answering the questions the business is asking — usually a year or two in.
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I architect, implement, and document the measurement layer that sits underneath every marketing decision. Concretely: GA4 property structure and event design, GTM container and data layer, conversion tracking through to enhanced conversions and server-side tagging, and Looker Studio dashboards built around the questions your business asks. The day-to-day reporting work stays with you (or your team); my job is making sure the numbers underneath are honest.
A typical setup covers four layers: account structure (property and stream configuration, internal traffic filters, data retention), event design (custom events tied to real business outcomes, conversion mapping, audience definitions), tag management (clean GTM container, data layer implementation, trigger logic that does not double-fire), and reporting (Looker Studio dashboards, BigQuery export configuration where it earns its keep). Scope varies by what is already in place — a fresh GA4 build is different work from a GTM rebuild on top of an existing GA4 property.
Not until you do. GA4 covers most reporting needs out of the box — page views, conversions, basic attribution, audiences. BigQuery starts earning its keep when GA4 default reports stop answering questions: event-level analysis across long time windows, joins against CRM or ad spend data, custom funnel logic the GA4 UI cannot express. For most engagements, BigQuery is a year-two consideration, not a foundation requirement.
A simple property build with conversion tracking and a starter Looker Studio dashboard typically lands in 1–2 weeks once access is sorted. A full GTM rebuild on top of existing tag chaos plus GA4 reconfiguration plus enhanced conversions plus a custom dashboard set runs 4–8 weeks depending on how much foundational cleanup is in front of the new work. Most engagements have one or two weeks of unexpected debugging when broken events surface mid-implementation.
Common symptoms: conversion numbers in GA4 that do not match the numbers in Google Ads, events firing twice (or not at all), bot traffic polluting reports, key business actions (form submissions, phone calls, signed quotes) missing from the funnel entirely, dashboards that show clicks and sessions but never tie back to revenue. Diagnosis is part of the audit; remediation is the engagement that follows if it makes sense.
Yes. Custom Looker Studio dashboards pulling from GA4, Search Console, ad accounts, and BigQuery — designed around the specific questions you need answered, not generic templates. Every dashboard ships with documentation, scheduled email exports if useful, and a monthly review cadence so the metrics stay tied to actual decisions instead of aging into wallpaper.
GA4 is the platform Google has invested in for the foreseeable future, but the work I do is platform-portable. A clean data layer, server-side tagging, and BigQuery export can survive a platform migration — those are the durable assets. The GA4 UI is the part that would need replacement; the underlying measurement architecture transfers.
Yes. The audit comes first — what is firing, what is broken, what is missing. From there, the remediation is incremental: fix the highest-impact gaps, document what was done, and only rebuild from scratch if the existing setup is genuinely beyond repair. Most engagements are remediation, not greenfield.
Send me access to your GA4 and I'll walk through what's working, what's missing, and where the measurement gaps are. You'll get a clear read on where things stand.