We review your Google Cloud and Workspace setup at no cost and show you exactly where data is slipping through the cracks. Scattered sources, no central warehouse, manual reporting that burns hours, GA4 gaps, Workspace processes running on copy-paste. If you want it fixed, we scope a fixed-price engagement: BigQuery pipelines, server-side tagging, Looker dashboards, and Apps Script automation that connects to the rest of your stack.
A team that has never looked at your actual data flows cannot tell you what is really missing. So the proposal is generic, the timeline is optimistic, and six months later you have a BigQuery dataset nobody queries because it was built to a spec that never matched reality.
We flipped it. The audit comes first and it comes free, built on your real environment: your GA4 property, your current GCP projects, your Workspace setup, and the tools sitting next to them. You see exactly what is broken and what each fix is worth in time saved or data restored before any money changes hands. If the audit finds nothing worth building, we will tell you that, and you owe nothing.
No procurement loop, no day-rate negotiation, no open scope. The front end runs on one short form and one call.
Work email and a brief description of what Google tools you are on: GCP, GA4, Workspace, any BI or data tooling. That is the whole form.
We look at your GA4 setup, GCP projects, BigQuery usage, Workspace configuration, existing automations, and the integrations connecting them to the rest of your stack.
A short call to walk through what we found: the data gaps, the automation opportunities, the infrastructure waste, and the order of priority. You keep the findings either way.
If you want it built, we write a fixed-scope proposal: the pipelines, the dashboards, the automations, the integrations, with a delivery schedule and a price you approve before any code is written.
Good data infrastructure only works if the collection is clean, the warehouse is queryable, and the outputs reach the people making decisions. Build one layer without the others and the investment is wasted.
Server-side GA4 tagging on Cloud Run so your analytics survive ad blockers and consent flows. BigQuery as the central warehouse, with ELT pipelines pulling from your CRM, your product database, your ad platforms, and your Workspace exports. Pub/Sub for event-driven triggers between services. Clean data in, clean data out.
Looker Studio dashboards connected live to BigQuery so reports update themselves. Custom Looker semantic layers for teams that need self-serve querying without writing SQL. GA4 explorations and audiences built to the actual questions your marketing and product teams ask, rather than the default views nobody uses.
Google Workspace administration: user provisioning, security policy, shared drive governance, and licence management that scales without a full-time admin. Apps Script automations that replace the copy-paste workflows: form-to-CRM syncs, approval routing in Sheets, calendar and Meet integrations, and document generation that used to take someone an afternoon.
Want the technical depth? Every one of these areas is broken down with architecture diagrams and methodology in the complete Google integration guide. This page gets you a free audit; the guide is the reference.
Every item in your audit follows the same structure: what is broken, the data behind it, the time or accuracy recovered per week, and the exact spec your team can build to without a follow-up meeting.
The card on the right is illustrative. Your audit is built from your real GCP environment and GA4 property.
Sources Salesforce via REST + Ads API + Stripe webhook to Pub/Sub Pipeline Cloud Function triggered on Pub/Sub, loads to BigQuery Schema revenue_daily: date, channel, campaign, revenue, cost Report Looker Studio reads BigQuery live, auto-refreshes 06:00
Some teams need a single pipeline and a dashboard. Others need the full GCP data architecture and Workspace automation from scratch. The audit tells us which. The price is in the agreement before any work begins.
Data infrastructure and operational automation across industries. A few that map closely to a Google integration engagement:
Data infrastructure and growth work for a SaaS project management tool, including analytics and reporting consolidation.
Scaling a fashion marketplace to 500 brands, with a unified data layer connecting product, ad spend, and revenue reporting.
Attribution and funnel reporting rebuilt on clean GA4 data so the team could see which channel was actually driving direct bookings.
Drop your work email and a line about what Google tools you are on. We reply within 24 hours to confirm scope and book a short findings call. The audit itself is free.
Two fields. We do the rest.
A free audit on your real environment. A fixed scope to build what is missing, only if the numbers justify it. Findings in a week.
Get a free Google audit