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Analyze Chinese Ai Visibility Sample
Created by
Tim Zinin
Run a self-contained four-row sample showing how ChatGPT, Gemini, Kimi, and Qwen observations are normalized into evidence-ready brand visibility data.
Chinese AI Visibility Dataset Analyzerzinin/chinese-ai-visibility-dataset-analyzer
Brand
Query
Model
Mentioned
+7 fieldsTextNumberBooleanListObject
Input
Brand to track(required):Northstar Running
Brand aliases:Northstar
Competitors and aliases
Competitor name(required):StrideLab+1
Competitor aliases
Inline JSON rows
sourceActorId:apify/chatgpt-search-scraper+3
query:Example observation: trail running brands for new runners+2
text:In this supplied example, Northstar Running appears before StrideLab and PaceForge.+1
sources
checkedAt:2026-08-01T10:00:00.000Z+3
Fallback market:China
Fallback language:English
Maximum source rows:10
Output fields
Brand
Query
Model
Mentioned
Position
Competitors
Grounding
Quality flags
Cited domains
Answer
Checked
Sign up on Apify01
Create your Apify account to access the Chinese AI Visibility Dataset Analyzer.
Start the run02
The Actor will start running based on the input automatically.
Receive the output03
Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.
Integrate into your workflow04
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.
