Social Analytics Skill for ChatGPT: Compare Reach and Impression Denominators
Turn supplied social metrics into an auditable table. Distinguish unique reach, total impressions, frequency, and engagement rates with labeled denominators.
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 social-media-manager/skills/social-analytics/SKILL.md from the pinned GitHub source. Keep the name, description, and instructions for social-analytics 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 social-analytics 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 campaign reached 200 accounts, recorded 300 impressions, and received 18 interactions. Compute both engagement rates and average frequency.What to check
Show 9% per reached account, 6% per impression, and frequency of 1.5. Label both denominators and avoid projecting long-term performance from the sample.
Original SKILL.md on GitHub · Updated
Frequently asked question
Can engagement rates from two channels be compared directly?
Check event definitions, date ranges, and denominators. Explain differences side by side or recompute a shared definition using available counts.