The following technical points need to be focused on to realize efficient natural language queries:
1. Norms for the formulation of queries
- Clarify the timeframe: e.g., "last 30 days", "Q2 2024″, etc.
- Standardize the name of the metric: use the term "page views" rather than "PV" to ensure accurate identification by the model.
2. Configuration of data rights
- Ensure that the service account has
analytics.readonlyand other necessary permissions - Verify the correctness of the query attribute ID (in the format of
properties/123456789)
3. Results-based mechanisms
- Setting reasonable query timeouts (especially for complex queries)
- Handling API Limit: GA4 Data API has a limit of queries per day
4. Model fit optimization
- Create a mapping dictionary for specialized terms (e.g., map "UV" to
activeUsers) - Provide clarification options for fuzzy queries (e.g., "Do you mean the number of users or the number of sessions?")
It is recommended that the first use be preceded byget_standard_dimensionsGet a list of standard fields to understand the range of data dimensions recognized by the system.
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 " What are the technical points to keep in mind when querying GA4 data using natural language?
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