Conversion Funnel Agent

Product and funnel analytics are critical components of ecommerce optimization. While product analytics reveal which items drive revenue and which underperform, funnel analytics expose where customers abandon their journey.

Together, they provide a complete picture of what customers want and what obstacles prevent them from purchasing.

In this playbook, we will build an agent that combines both analyses to deliver an optimization strategy backed by GA4 data.

Here's a preview of a part of the agent output:

# E-Commerce Funnel Optimization Report

Based on the GA4 product funnel metrics and top products data provided, I've identified several critical optimization opportunities to improve conversion rates and reduce drop-offs in your e-commerce funnel.

## Checkout Process Gap

- **Action**: Implement a complete, streamlined checkout process that includes payment and shipping information steps.
- **Rationale**: There are zero events recorded for "Add Payment Info" and "Add Shipping Info" stages, yet purchases are occurring (3,331), indicating a tracking implementation issue or a broken checkout flow.
- **Expected Impact**: Properly tracking these steps could provide visibility into 100% of the missing checkout journey, enabling targeted optimizations that could increase purchase conversion by 20-30%.
- **Priority**: High

## Add to Cart to Begin Checkout Drop-off (89.5%)

- **Action**: Add cart abandonment recovery emails with personalized product recommendations and incentives.
- **Rationale**: Only 10.5% of users who add items to cart proceed to begin checkout, indicating a significant 89.5% drop-off at this stage.
- **Expected Impact**: Implementing abandonment recovery could recover 15-25% of abandoned carts, potentially adding 9,600-16,000 checkout initiations.
- **Priority**: High

## Product Disconnect Between Viewing/Cart and Purchase

- **Action**: Create prominent product bundles featuring top-viewed items (like Google Campus Bike Eco Tee Navy) with top-purchased items (like Google Small Standard Journal Navy).
- **Rationale**: The most viewed/carted products (apparel items) differ completely from the most purchased products (accessories and smaller items), suggesting a pricing or commitment barrier.
- **Expected Impact**: Strategic bundling could increase average order value by 15-20% while boosting conversion rates of popular but less-purchased items by 10-15%.
- **Priority**: Medium

## High-Interest Products Not Converting

- **Action**: Create targeted promotions for the top 5 viewed products (Google Campus Bike Eco Tee Navy, Google Navy Speckled Tee, etc.) that aren't converting to purchases.
- **Rationale**: These products generate high interest (776, 759, 759 views) and cart additions but aren't appearing in top purchases, indicating potential price sensitivity or sizing/fit concerns.
- **Expected Impact**: Addressing specific barriers could increase purchase conversion rates for these products by 20%, potentially generating 300+ additional purchases.
- **Priority**: Medium

## Cart-to-Purchase Conversion

- **Action**: Implement a single-page checkout process with guest checkout option, minimizing form fields and steps.
- **Rationale**: Only 3,331 purchases from 71,501 cart additions (4.7% conversion) indicates a significant checkout friction problem.
- **Expected Impact**: Streamlining checkout could increase cart-to-purchase conversion by 2-3 percentage points, potentially generating 1,400-2,100 additional purchases.
- **Priority**: High

Step 1: Connecting to BigQuery

The first step is establishing a connection to BigQuery where your GA4 data is stored. The agent supports both sample data and your own GA4 implementation.