Google Analytics shows one order count, the CRM another, finance a third.
We combine the sources in one warehouse, agree on the counting rules (what counts as an order, a refund, a duplicate) and document them.
All your business data in one warehouse, updated automatically
Ads in one dashboard, orders in the CRM, leads in a spreadsheet, and none of the numbers match. We pull these sources into one data warehouse and keep it updated on a schedule. You see real cost per customer instead of guesses.
Quote and schedule after your brief
Who it's for
- Online stores with orders, ads and inventory in separate systems
- Companies paying for ads without knowing which lead became a sale
- Teams building reports by hand in spreadsheets every month
- Businesses preparing clean data for AI agents, forecasting or dashboards
Problems we solve
Someone assembles reports manually, and it takes a day or two every time.
We build data pipelines (ETL: scripts that fetch, clean and load data on a schedule). The report refreshes itself.
We can't tell which ads make money because sales data isn't linked to clicks.
We join ad spend, site visits and CRM deals through shared identifiers, then calculate cost per lead and per sale by channel.
We worry the warehouse will turn into a surprise cloud bill.
We use table partitioning (splitting by date), query limits and Google Cloud budget alerts. You get a rough monthly cost estimate before we start.
What's included
- Audit of data sources: GA4, ad accounts, CRM, store, spreadsheets
- Warehouse design: raw, cleaned and reporting-ready tables
- Google Cloud project and BigQuery setup under your account
- GA4 export to BigQuery and Google Ads and Meta Ads connections
- Pipelines from your CRM and store via API (the way systems exchange data) or ready-made connectors
- Data cleaning: duplicates, currencies, time zones, UTM tags
- Reporting tables and Looker Studio connection
- Data quality checks: automated tests for gaps and sudden spikes
- Documentation: table schema, metric definitions, handover guide
- Access handover: the project and all keys are yours under the agreed terms
Choose the scope
Use a package to describe what you need. We agree on the quote and schedule after reviewing your brief and requirements.
01
Start
Small businesses that need site, ads and leads in one place
- GA4 export to BigQuery
- Google Ads and Meta Ads connections
- One reporting table: spend and leads by channel
- Looker Studio dashboard
02
Business
Stores and service companies with a CRM and several channels
- Everything in Start
- CRM or store pipeline
- Lead → deal → revenue linking
- Automated data quality checks
- Documentation and team training
03
Complex integration
Companies with several systems, inventory, ERP or AI data needs
- Everything in Business
- ERP or accounting system integration
- Custom analytics data models
- Data preparation for AI agents and forecasting
- Cloud cost controls
How we work
Brief and requirements
You describe the task and current workflow. We clarify requirements, choose a first stage and prepare a quote.
Pilot with a KPI
We take one source and one reporting table. We agree a measurable result, for example: the cost-per-lead report matches the CRM.
Pipeline build
We connect the sources, clean the data and build the tables. Payment is in stages.
Checks and reports
We reconcile the numbers with your systems and build dashboards and quality tests.
Handover
You get access, documentation and training. After that you can run it yourself or keep working with us.
Scope and limits
- We don't promise perfect data: if sales reps leave CRM fields empty, reports will show it but not fix it
- We can't recover data that was never collected: GA4 history in BigQuery starts from the day of the connection
- We don't fix your cloud bill in advance: it depends on query volume, so we estimate and cap it
FAQ
Do I need a warehouse if I already use Google Analytics?
If GA4 reports are enough, no. A warehouse makes sense when you need to join site, ads and CRM data, keep data longer or run your own calculations.
How much does BigQuery cost per month?
We prepare a quote after reviewing your brief and requirements. A first stage can cover: gA4 export to BigQuery; Google Ads and Meta Ads connections. Scope, payment and schedule are agreed before work starts.
Who owns the cloud project?
We agree on the handover of code, materials and account access before work starts. Third-party licences and services are listed separately when needed.
Which CRMs and stores can you connect?
Systems with an API or connectors, such as HubSpot, Pipedrive, Salesforce, Shopify and WooCommerce. For rarer tools we first check whether the data is accessible.
How long until the first report?
The schedule depends on scope, materials, access and external approvals. After your brief we agree on stages and acceptance criteria. For marketing outcomes, we also agree on how to measure progress: rankings, leads and sales depend on more than the work delivered.
Can we start small?
Yes. We start with a pilot: one source, one reporting table, a clear KPI. If you are happy with the result, we expand.
Start with your task
Describe your business, the outcome you need and your current workflow. We will clarify the requirements and prepare a quote after your brief.