Video Analytics Interpreter for ChatGPT: Diagnose CTR and Retention
Use creator-supplied impressions, click-through rate, watch time, and retention points to investigate packaging, opening hooks, or pacing. Produce a diagnosis and a practical next test.
中文Install in ChatGPT
Use an eligible ChatGPT workspace with permission to create skills and, for uploads, upload permission. The installation path for this text-only adaptation was checked against OpenAI documentation. Workspace runtime verification is pending.
- Download workflows/video-creator-workflow/.claude/skills/video-analytics-interpreter/SKILL.md from the pinned GitHub source. Keep the name, description, and instructions for video-analytics-interpreter together as a standalone text skill.
- In a ChatGPT workspace with skills and uploads enabled, open Plugins, Skills, Create, and Upload from your computer. Choose a skill package format accepted by the file picker. You can also choose Create with editor and enter the original name, description, and instructions.
- After the scan completes, check that video-analytics-interpreter appears in Installed. Type @ in a new chat, select the skill, and use the fictional example on this page to check the output.
Example task
A fictional six-minute tutorial has 8,000 impressions, 2.5% CTR versus 4% on three comparable videos, 72% retention at 00:30, and a replay spike at 04:10. Ask for observations and two separate hypotheses.What to check
Report the CTR gap and preserve the 72% and 04:10 evidence. Suggest a title or thumbnail test and keep the replay spike open to interpretation. Avoid treating the CTR gap as proof of a specific cause.
Original SKILL.md on GitHub · Updated
Frequently asked question
Does low CTR mean I should re-edit the whole video?
Compare CTR and retention with traffic sources and similar videos. If clicks are weak but opening retention is stable, a title or thumbnail test is a practical first step.