In this playbook, we'll build a funnel optimization agent that analyzes GA4 ecommerce data with BigQuery SQL, generates recommendations for both product strategy and funnel improvements, and creates an executive summary with prioritized action items to boost conversion rates and increase revenue.
In this playbook, we'll build a customer acquisition reporting agent that analyzes GA4 traffic patterns through BigQuery SQL, generates channel-specific AI recommendations, and provides actionable insights to improve marketing effectiveness.
In this playbook, we'll build a GA4 Analytics Agent that queries cost-effective BigQuery aggregations of Google Analytics data and uses AI to translate natural language into precise SQL, giving your team direct access to insights.
This playbook walks you through building a cost-aware SQL agent that delivers actionable insights from BigQuery. The agent helps data teams democratize access to analytics and avoid unexpected costs through validation and a built-in protection mechanism.
This playbook walks you through building an ecommerce product analytics agent using BigQuery and LangGraph. The agent helps identify opportunities to increase average order value through product combinations, category analysis, and bundle recommendations.
This playbook will walk you through building a repeat purchase analytics library. We'll cover everything from writing SQL queries to creating a Python class for your analysis tools. We'll then create a suite of LangChain tools out of the class and let LLMs figure out how to use the different tools.
