A growing collection of Python and SQL scripts designed to solve real-world SEO and marketing problems.
These files focus on isolating and analyzing queries driven by Artificial Intelligence features (like AI Overviews or generative search) versus standard search queries.
| File Name | Type | Description |
|---|---|---|
AI Mode queries.ipynb |
Notebook | Interactive data exploration and visualization of AI-specific search queries. |
AI_Driven_GSC_Queries.sql |
SQL | Extracts and processes GSC data related to AI-driven search behaviors. |
AI_Driven_Traditional_Query_GSC_split.sql |
SQL | Segments GSC query dataset to compare traditional vs. AI-driven traffic and impressions. |
These files handle the grouping of similar keywords based on search engine results, allowing for topic clustering and semantic analysis.
| File Name | Type | Description |
|---|---|---|
SERP Clustering.py |
Python | Executes core logic for SERP clustering, grouping semantically related queries together based on search results. |
GSC SERP Clustering.sql |
SQL | Prepares raw GSC data for the Python clustering script or processes the clustered output into a relational database. |
These files are geared toward understanding why users are searching and how different ranking signals combine.
| File Name | Type | Description |
|---|---|---|
post1_gsc-query-data.sql |
SQL | Pulls foundational GSC query data required for intent classification. |
post1_gsc-intent-classifier |
Script | Takes the GSC queries and classifies their search intent (e.g., informational, transactional). |
rrf_analysis.sql |
SQL | Performs Reciprocal Rank Fusion (RRF) analysis to combine multiple ranking scores into a unified metric. |