Integrations

Supercharge Google Analytics with Relevance AI

Google Analytics is a robust platform for tracking and analyzing web traffic and user interactions. With Relevance AI, you can leverage these analytics capabilities to create dynamic workflows that drive informed decision-making and optimize user experiences.

Give your AI Agents Google Analytics Superpowers

Google Analytics provides powerful insights into user behavior and engagement. Relevance AI amplifies this by enabling intelligent AI Agents to automate reporting and event tracking, transforming raw data into strategic actions.

Predictive Analytics Mastery

The AI agent leverages historical data patterns to forecast user behavior and anticipate market trends with exceptional accuracy.

Real-time Insight Orchestration

Continuous monitoring and instant analysis of live analytics data enables the agent to make immediate, data-driven decisions.

Cross-channel Performance Optimization

The agent simultaneously analyzes multiple marketing channels to automatically adjust strategies for maximum ROI.

Tools

Equip AI Agents with the Google Analytics Tools they need

Relevance AI seamlessly integrates with Google Analytics to enhance your data-driven workflows.

Google Analytics - Create GA4 Property
Creates a new Google Analytics 4 (GA4) property with customizable settings for tracking and analyzing website/app data, including timezone, industry category and currency specifications.
Google Analytics - Run Report in GA4
Generates customized analytics reports from GA4 properties, allowing specification of date ranges, metrics, dimensions, and filtering options for detailed data analysis.
Google Analytics - Run Report in GA4
Generates customized analytics reports from GA4 properties, allowing specification of date ranges, metrics, dimensions, and filtering options for detailed data analysis.
Google Analytics - Run Report
Executes analytics reports for Universal Analytics (UA) properties, enabling data retrieval based on specified time periods, metrics, and dimensional attributes.
Google Analytics - Create Key Event
Establishes new key events within a GA4 property for tracking specific user interactions, with configurable counting methods for session-based or event-based tracking.
Name
Google Analytics API Call
Description
Make an authorized request to a Google Analytics API
Parameters
["OAuth authentication", "Multiple base URL endpoints", "Flexible HTTP methods", "Custom headers support", "Response handling"]
Use Case
An e-commerce company uses this integration to automatically pull daily website traffic metrics and conversion data from Google Analytics into their customer analytics dashboard, enabling real-time monitoring of campaign performance and user behavior patterns.

Security & Reliability

# Getting Started with Google Analytics & Relevance AI Integration

The integration leverages Google Analytics' OAuth 2.0 authentication framework, ensuring secure access to your analytics data while Relevance AI manages API operations (GET, POST, PATCH) behind the scenes—handling rate limits, error handling, and data formatting automatically.

Built-in data validation and automated dimension/metric compatibility checks ensure your analytics workflows execute reliably, with support for both Universal Analytics and GA4 property types.

No training on your data

Your data remains private and is never utilized for model training purposes.

Security first

We never store anything we don’t need to. The inputs or outputs of your tools are never stored.

Get Started

Best Practices for Non-Technical Users

To get the most out of the Google Analytics + Relevance AI integration without writing code:
  • Start with a well-structured GA4 property: Ensure your property settings, including time zone and industry category, are correctly configured.
  • Utilize pre-built reports: Leverage Relevance AI's templates for common reporting needs to save time and effort.
  • Connect securely: Make sure to use OAuth 2.0 credentials with the appropriate permissions for accessing your GA4 properties.
  • Test your configurations: Run initial reports and event tracking on a test property to validate your setup before applying it to production data.
  • Monitor API usage: Be aware of your API quota and implement rate limiting strategies to avoid hitting usage limits.