BigQuery + Looker Analytics Setup
Budget: $250 – $750 USD
I need a fully-automated analytics stack that funnels data from GoHighLevel, Stripe, Google Analytics 4, and Whop into BigQuery and then visualises the key KPIs in Looker Studio.
The warehouse should be designed primarily for reporting—clean, well-modelled tables that refresh on a reliable schedule—so I can quickly slice everything from acquisition costs to sales-team close rates without wrestling with raw exports.
Scope of work
• Build or configure the ETL pipelines that extract each source’s data, load it into BigQuery, and transform it into a unified schema. If an off-the-shelf connector (Fivetran, Airbyte, native GA4 export, etc.) is the best option, set it up; if custom Cloud Functions or SQL is more practical, document the logic clearly.
• Create curated views or materialised tables for: customer acquisition and retention, revenue and MRR/ARR trends, website & funnel engagement, and detailed sales-rep performance metrics.
• Design interactive Looker Studio dashboards that surface those insights at executive and team levels, with filter controls for date ranges, campaigns, and pipeline stages.
• Schedule automatic refreshes and set sensible data-quality checks so the visuals always reflect the latest numbers.
• Deliver concise documentation covering schema diagrams, refresh cadence, and instructions for extending the model with new fields.
Acceptance will be based on:
1. Every source syncing to BigQuery with no manual intervention.
2. Latency under 4 hours between source update and dashboard refresh.
3. Dashboards accurately matching sample figures provided during UAT.
4. Clear, reproducible setup documentation.
The warehouse should be designed primarily for reporting—clean, well-modelled tables that refresh on a reliable schedule—so I can quickly slice everything from acquisition costs to sales-team close rates without wrestling with raw exports.
Scope of work
• Build or configure the ETL pipelines that extract each source’s data, load it into BigQuery, and transform it into a unified schema. If an off-the-shelf connector (Fivetran, Airbyte, native GA4 export, etc.) is the best option, set it up; if custom Cloud Functions or SQL is more practical, document the logic clearly.
• Create curated views or materialised tables for: customer acquisition and retention, revenue and MRR/ARR trends, website & funnel engagement, and detailed sales-rep performance metrics.
• Design interactive Looker Studio dashboards that surface those insights at executive and team levels, with filter controls for date ranges, campaigns, and pipeline stages.
• Schedule automatic refreshes and set sensible data-quality checks so the visuals always reflect the latest numbers.
• Deliver concise documentation covering schema diagrams, refresh cadence, and instructions for extending the model with new fields.
Acceptance will be based on:
1. Every source syncing to BigQuery with no manual intervention.
2. Latency under 4 hours between source update and dashboard refresh.
3. Dashboards accurately matching sample figures provided during UAT.
4. Clear, reproducible setup documentation.