Synthetic vs User-generated Queries Classifier
Distinguish User Queries from AI-Generated Synthetic Queries
How to Use This Tool
This analyzer helps you identify whether search queries are user-initiated or AI-generated (synthetic). Choose your analysis mode and input method:
- Single Query: Test individual queries to see their classification and features
- CSV Upload: Analyze multiple queries at once (CSV format: one query per line, or column named ‘keyword’ or ‘query’)
- Three Analysis Modes: Feature Extraction (see query characteristics), Rule-Based (simple classification), or ML Analysis (advanced classification)
Feature Extraction Analysis
Extract linguistic features from queries to understand their characteristics. This analysis reveals query length, complexity, entity density, and other signals that differentiate user queries from AI-generated ones.
Rule-Based Classification
Classify queries using linguistic rules and patterns. This method uses interpretable criteria like query length, technical vocabulary, reading complexity, and entity density to determine if a query is user-generated or synthetic.
Machine Learning Classification
Advanced classification using a trained machine learning model. This uses ensemble methods to analyze multiple features simultaneously for more accurate predictions. The model learns patterns from labeled training data to identify subtle differences between user and synthetic queries.
Why Query Classification Matters for SEO & Content Strategy
Understanding the difference between user queries and synthetic queries is critical for modern SEO and content optimization in the age of AI search.
Prioritize User Intent
User queries represent direct search traffic opportunities. These are the terms people actually type, indicating immediate intent and potential conversions.
Understand AI Patterns
Synthetic queries reveal how AI systems think and expand user questions. Understanding these patterns helps you create comprehensive content that satisfies both users and AI search engines.
Competitive Analysis
Identify gaps where competitors focus only on user queries or synthetic patterns. Build content strategies that cover both to dominate search visibility.
Predict Behavior
Synthetic patterns show what AI systems predict users need. This helps you anticipate questions and create content proactively.
Content Optimization
User queries need conversational, simple content. Synthetic queries require technical depth and comprehensive coverage. Different query types = different optimization approaches.
Future-Proof Strategy
As AI search grows (ChatGPT Search, Perplexity, Google AI Mode), understanding synthetic query patterns becomes essential for visibility in AI-powered search results.