Google Analytics + Looker
Connect Google Analytics to Looker for Automated, Reliable Reporting
Bring your web analytics and business intelligence data together — no manual data wrangling.
Why integrate Google Analytics and Looker?
Google Analytics captures how users discover, navigate, and engage with your digital properties. Looker turns raw data into governed, shareable business intelligence. They work well together — but keeping web behavioral data flowing cleanly into Looker dashboards takes real plumbing. Tray.ai connects Google Analytics and Looker so your teams always have fresh, accurate web data without building a single pipeline from scratch.
Automate & integrate Google Analytics & Looker
Use case
Automated Daily Web Metrics Sync to Looker
Schedule a recurring workflow that pulls Google Analytics metrics — sessions, users, bounce rate, goal completions — and loads them directly into your Looker data models each morning. Your Looker dashboards reflect yesterday's web performance without manual exports or CSV uploads. Analysts start every day with data that's already current and ready to explore.
Use case
Campaign Performance Reporting Across Channels
When a new paid or organic campaign goes live, tray.ai can automatically pull Google Analytics UTM-tagged traffic data and surface it inside a dedicated Looker Explore or dashboard. Marketers can compare acquisition channels, landing page performance, and conversion rates without switching between tools — giving the whole organization one place to assess campaign ROI.
Use case
Conversion Funnel Analysis with Blended Data
Merge Google Analytics funnel stage data — from first session to goal completion — with CRM or transactional data already in Looker to build end-to-end conversion funnel models. Tray.ai keeps the Google Analytics behavioral layer continuously updated, so Looker's blended funnel views always reflect real user journeys. Product and growth teams can see exactly where users drop off and what drives them to convert.
Use case
Real-Time Anomaly Alerts from Google Analytics to Looker
Configure tray.ai to monitor Google Analytics data for traffic spikes, conversion drops, or bounce rate anomalies and automatically trigger a Looker dashboard refresh or alert notification. Instead of discovering a tracking issue or a viral traffic event hours after it happens, your team gets notified the moment the data signals something unusual — which makes a real difference when you need to respond fast.
Use case
Audience Segmentation Data for Looker-Driven Personalization
Pull Google Analytics audience segments — demographics, device categories, behavioral cohorts — into Looker so data teams can enrich customer profiles and build more sophisticated segmentation models. Tray.ai automates the extraction and loading of segment data on a scheduled or event-driven basis, keeping Looker's audience tables current. Marketing and product teams can then take those insights back into their personalization and targeting tools.
Use case
Executive Reporting Dashboards Populated Automatically
Use tray.ai to orchestrate a workflow that aggregates weekly or monthly Google Analytics KPIs — traffic trends, top landing pages, channel mix, goal completions — and feeds them into a pre-built Looker executive dashboard. Reports arrive on schedule without anyone manually compiling or formatting data. Leadership gets consistent, reliable web performance summaries that always reflect the latest numbers.
Use case
E-Commerce Revenue Attribution Modeling
Sync Google Analytics e-commerce data — transactions, revenue, product performance, attribution paths — into Looker to power multi-touch attribution models and merchandising analysis. Tray.ai keeps transaction-level data flowing into the right Looker tables on a defined schedule, supporting both real-time dashboards and historical trend analysis. Revenue, marketing, and product teams can finally work from one authoritative view of e-commerce performance.
Get started with Google Analytics & Looker integration today
Google Analytics & Looker Challenges
What challenges are there when working with Google Analytics & Looker and how will using Tray.ai help?
Challenge
API Rate Limits and Data Sampling in Google Analytics
Google Analytics imposes API rate limits and applies data sampling for high-traffic properties, which can cause incomplete or inconsistent data exports when pulling large date ranges or high-cardinality dimensions. For enterprise-scale web properties, this makes it genuinely hard to build reliable, unsampled datasets inside Looker.
How Tray.ai Can Help:
Tray.ai handles Google Analytics API rate limit responses with automatic retry logic and intelligent request throttling. Workflows can break large date range queries into smaller, unsampled chunks and merge the results before loading into Looker, so complete and accurate data lands in your dashboards every time.
Challenge
Schema Mismatches Between Google Analytics Dimensions and Looker Models
Google Analytics has its own naming conventions, data types, and hierarchical dimension structures that rarely map cleanly to Looker's LookML models or the underlying warehouse tables they reference. Manual field mapping is tedious and fragile, especially when Google Analytics reports include calculated metrics or custom dimensions.
How Tray.ai Can Help:
Tray.ai's data transformation tools let teams define reusable field mapping logic between Google Analytics API response schemas and Looker-compatible table structures. Custom dimension and metric mappings can be configured visually, and transformations can be updated centrally without touching individual workflow steps — which matters a lot when schemas change.
Challenge
Keeping Looker Dashboards Fresh Without Overloading Infrastructure
Triggering too-frequent Looker PDT rebuilds or dashboard cache refreshes in response to Google Analytics data updates can strain warehouse compute and create query contention for other Looker users. Getting the refresh cadence right without constant manual coordination is an ongoing operational headache.
How Tray.ai Can Help:
Tray.ai lets teams build condition-based refresh logic — for example, only triggering a Looker PDT rebuild when the volume of new Google Analytics records crosses a meaningful threshold, or scheduling refreshes during off-peak hours. Looker dashboards stay current without putting unnecessary pressure on warehouse performance or costs.
Challenge
Managing Multiple Google Analytics Properties and Looker Projects
Enterprises often manage dozens of Google Analytics properties across brands, regions, or product lines, each needing to feed separate or consolidated Looker projects. Maintaining individual data pipelines for every property-project combination quickly becomes a mess of brittle, hard-to-maintain workflows.
How Tray.ai Can Help:
Tray.ai supports parameterized, reusable workflow templates that accept Google Analytics property IDs and Looker project references as dynamic inputs. A single workflow template can run for multiple property-project pairs, be monitored centrally, and updated in one place — cutting maintenance overhead significantly as the analytics estate grows.
Challenge
Data Governance and PII Compliance Across the Integration Layer
Google Analytics can capture personally identifiable information through custom dimensions, user IDs, or URL parameters if it's not carefully governed. Passing that data into Looker without appropriate filtering or masking creates real compliance risk under GDPR, CCPA, and other privacy regulations.
How Tray.ai Can Help:
Tray.ai lets teams build PII detection and scrubbing logic directly into the integration workflow before data ever reaches Looker. Field-level masking rules, allowlists for approved dimensions, and audit logging can all be configured within the tray.ai workflow layer, so only compliant, appropriately anonymized data flows into Looker models and dashboards.
Start using our pre-built Google Analytics & Looker templates today
Start from scratch or use one of our pre-built Google Analytics & Looker templates to quickly solve your most common use cases.
Google Analytics & Looker Templates
Find pre-built Google Analytics & Looker solutions for common use cases
Template
Daily Google Analytics Metrics to Looker Sync
Pulls a defined set of Google Analytics dimensions and metrics each day and loads the results into a target Looker dataset or triggers a PDT rebuild, so dashboards are refreshed with current data every morning.
Steps:
- Trigger workflow on a daily schedule at a configured time
- Query Google Analytics Reporting API for selected metrics and dimensions across the desired date range
- Transform and map the response data to match the Looker target table schema
- Write records to the Looker-connected data warehouse or call the Looker API to trigger a PDT refresh
- Send a Slack or email confirmation once the sync completes successfully
Connectors Used: Google Analytics, Looker
Template
New Google Analytics Goal Completion to Looker Event Log
When a conversion goal is completed in Google Analytics, this template logs the event details into a Looker-accessible table, enabling real-time conversion tracking and cross-platform attribution analysis inside Looker dashboards.
Steps:
- Poll Google Analytics API at a defined interval for new goal completions
- Filter and deduplicate goal completion events since the last successful run
- Format event data including goal ID, session details, and acquisition source
- Insert new records into the designated conversion events table accessible by Looker
- Trigger a Looker dashboard tile cache refresh to surface new conversion data
Connectors Used: Google Analytics, Looker
Template
Google Analytics Campaign Data to Looker Marketing Dashboard
Extracts UTM-tagged campaign performance data from Google Analytics and loads it into Looker on a scheduled basis, keeping the marketing performance dashboard populated with the latest channel and conversion data.
Steps:
- Trigger on a schedule or when a new campaign tag is detected in Google Analytics
- Fetch campaign, source, medium, and conversion data from the Google Analytics API
- Normalize UTM parameter values and map them to Looker marketing dimension fields
- Upsert campaign records into the Looker-connected marketing data table
- Refresh the Looker marketing overview dashboard to reflect the latest campaign results
Connectors Used: Google Analytics, Looker
Template
Weekly E-Commerce Performance Report from Google Analytics to Looker
Aggregates weekly e-commerce metrics from Google Analytics — including transactions, revenue, and top products — and populates a Looker reporting table, so finance and merchandising teams can access structured performance data without manual exports.
Steps:
- Trigger workflow every Monday morning for the prior week's date range
- Query Google Analytics E-Commerce Reporting API for transactions, revenue, and product data
- Aggregate and summarize results by product category and acquisition channel
- Load structured records into the Looker e-commerce performance table
- Notify the revenue team via email that the weekly Looker report is ready to view
Connectors Used: Google Analytics, Looker
Template
Google Analytics Anomaly Detection with Looker Dashboard Trigger
Monitors Google Analytics for significant deviations in metrics like sessions, bounce rate, or conversion rate, and automatically triggers a Looker dashboard refresh and alert notification when an anomaly is detected.
Steps:
- Run an automated check against Google Analytics API on an hourly or sub-hourly schedule
- Compare current metric values against a rolling average baseline to detect anomalies
- If a threshold breach is detected, call the Looker API to force a cache refresh on the relevant dashboard
- Send an alert to the appropriate Slack channel or email distribution list with anomaly details
- Log the anomaly event for historical tracking and future threshold calibration
Connectors Used: Google Analytics, Looker
Template
Audience Segment Export from Google Analytics to Looker Customer Table
Extracts defined audience segments from Google Analytics and syncs demographic and behavioral attributes into a Looker customer enrichment table, enabling more sophisticated segmentation modeling and downstream marketing activation.
Steps:
- Trigger on a weekly schedule or when a new audience segment is defined in Google Analytics
- Retrieve audience segment definitions and member attributes via the Google Analytics API
- Map demographic and behavioral fields to the corresponding columns in the Looker customer table
- Upsert audience segment records into the Looker-accessible enrichment dataset
- Confirm successful load and update the last-refreshed timestamp in the Looker metadata table
Connectors Used: Google Analytics, Looker