MCP Practical Solutions for Ecommerce Conversion Rate Analysis
For the characteristics of e-commerce business, GA4 data analysis can be implemented according to the following process:
- Key Event Configuration: Ensure that the purchase event and associated parameters (e.g. value, currency) are set in GA4. Verify that all custom event dimensions are available via get_dimensions in MCP.
- Conversion funnel modeling: Use run_report to build a multi-step query - first query the product page views, then query the add to cart event, and finally match the purchase completion event to calculate the conversion rate for each segment.
- Comparison of user segments: Combine dimensional filter conditions to compare conversion performance across traffic sources/device types/user regions. For example: { "dimensions": [{"name": "sessionSource"}], " metrics": [{"name": "conversions"}], "dimensionFilter ": { "filter": {"fieldName": "eventName", "stringFilter":{"value": "purchase"}}}}.
- natural language rapid analysis (NLRA): Input commands such as 'Compare mobile and PC add-on conversions over the past 30 days' to the big model to quickly get visual suggestions.
Best Practice: It is recommended to automatically run the core conversion report every day, save the results as CSV, and combine it with a big model for trend prediction and anomaly detection to realize true data-driven operation.
This answer comes from the articleGoogle Analytics MCP: A Local Server Tool for Connecting GA4 Data to Big ModelsThe
May not be reproduced without permission:AI productivity tools " How to apply MCP tools in e-commerce scenarios to improve the efficiency of conversion rate analysis?
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