A sophisticated data analysis tool that transforms historical performance data into actionable audience personas and engagement strategies.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install audience-analysis
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install audience-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Audience Analysis skill is a specialized tool within the Openclaw Skills ecosystem designed to decode complex user behavior. By processing historical performance data, it provides deep insights into audience demographics, active time windows, and specific consumption habits.
This skill enables developers and marketers to move beyond guesswork, providing a data-driven foundation for content optimization. Whether you are refining a brand's voice or timing a product launch, this Openclaw Skills integration ensures your strategy aligns with actual user patterns.
To integrate this skill into your workflow, ensure your environment is configured to access the Openclaw Skills API. Use the following structure to initiate an analysis:
# Example request to trigger audience analysis
curl -X POST https://your-instance.com/api/audience/analyze \
-H "Content-Type: application/json" \
-d '{
"content_ids": ["id1", "id2"],
"user_behavior_data": "{...}",
"time_range": "last_30_days"
}'
The skill expects and returns data in a structured format to ensure compatibility within the Openclaw Skills framework:
| Parameter | Type | Description |
|---|---|---|
| content_ids | Array | List of unique identifiers for the content being analyzed. |
| user_behavior_data | Object/String | Raw telemetry or interaction logs associated with users. |
| time_range | String | The temporal window for analysis (e.g., '7d', '30d'). |
| output | JSON | A structured object containing execution results or error logs. |
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