learn
intermediate
ChatGPT
Claude
AI Video Analysis: Understanding What Works on YouTube
Use AI to analyse YouTube video performance data. Learn how to interpret analytics and use AI insights to improve future content.
10 min read27 February 2026
YouTube
analytics
analysis
Export your YouTube analytics as CSV files; AI processes structured data more effectively than descriptions.
Focus on retention over views; ask AI to identify why certain videos lose audiences at specific timestamps.
Compare content performance by category: tutorials vs vlogs vs reviews. Let AI identify which formats resonate most.
Analyse seasonal trends in your analytics; AI can identify patterns that inform content calendars.
Ask AI to generate specific A/B test ideas based on what you've learned; test one variable at a time.
Why This Matters
YouTube analytics provide raw data, but interpreting trends and extracting actionable insights requires analysis. AI models excel at identifying patterns in engagement metrics, viewer retention, and demographic data. This guide teaches you to use AI as your analytical partner to understand what resonates with your audience.
How to Do It
1
Export your analytics data and ask ChatGPT or Claude to identify trends. AI can spot patterns humans might miss, such as which content types retain viewers longest.
2
Analyse which videos lose viewers early and which maintain engagement throughout. AI helps you identify common factors in high-performing content.
3
AI can analyse which audience segments engage most with different content. Use these insights to tailor future videos towards your most engaged demographics.
4
Provide AI with your competitors' publicly available data and your own metrics. Ask it to identify strategic differences and opportunities in your niche.
5
Rather than just viewing numbers, let AI translate data into specific content recommendations. Move from 'this video performed well' to 'replicate these three elements in future videos.'
Prompts to Try
Here are my YouTube analytics for the last 3 months: [ANALYTICS_DATA]. What patterns do you notice about viewer retention, audience engagement, and content performance? What content should I create more of?
Compare my video performance with these competitors: [COMPETITOR_DATA]. Where am I underperforming? What content strategies should I adopt?
Analyse this viewer demographic data: [DEMOGRAPHIC_DATA]. Which audience segment is most engaged? What content changes would appeal more to high-engagement demographics?
Common Mistakes
Not following best practices
{'tip': 'Export your YouTube analytics as CSV files; AI processes structured data more effectively than descriptions.'}
Frequently Asked Questions
CSV files or structured tables work best. Include metrics like views, watch time, average view duration, and engagement rates, organised by video date.
AI can identify patterns in successful content and suggest topics likely to resonate, but audience preferences evolve. Treat AI predictions as hypotheses to test.
Monthly reviews identify trends over time. Quarterly deep dives with AI help refine your content strategy and identify emerging patterns.
Next Steps
["Data-driven content creation separates growing channels from stagnating ones. By using AI to analyse your YouTube performance systematically, you transform raw metrics into strategic intelligence. Regular analysis, combined with willingness to experiment and adapt, creates a feedback loop that continuously improves your content and grows your audience."]