Audience Personas
SkillDocs & knowledgeBuild evidence-led social audience personas from customer interviews, comments, reviews, or CRM notes.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Audience Personas skill
What this skill tells your AI
The instructions your AI receives, as published by ootto-ai/claude-content-skills in skills/audience-personas/SKILL.md and read by ahel’s review.
Turn supplied customer evidence into grounded audience segments. Use it when a marketer has interviews, comments, reviews, or CRM notes and needs to decide who a message is for. It is not for inventing demographics, market size, or personas from intuition.
1. Establish the evidence
Ask for the source, date range, decision owner, offer, and desired audience action. Keep direct quotes separate from summaries and name material that is missing.
2. Group observable patterns
Cluster the evidence by job-to-be-done, desired outcome, objection, exact language, and trigger. Cite the source for each cluster. Do not manufacture a segment just to reach a round number.
3. Produce a usable segment
For each evidence-backed segment, return its job, language, objections, useful message angles, and the question it is already asking. Label confidence and unresolved questions.
4. Hold claims for review
Flag any demographic statement, outcome claim, or customer quote that needs approval before public use.
Hard rules
- Do not infer demographics, income, identity, or intent not present in the source.
- Do not turn one loud comment into a market-wide claim.
- Keep observed language distinct from suggested copy.
- If evidence is thin, ask for more comments, reviews, or interviews.
Failure modes
| Symptom | Cause | Fix |
|---|---|---|
| Generic personas | source has no concrete language | ask for verbatim comments or interviews |
| False certainty | inference appears as fact | label it as a hypothesis |
| Too many segments | minor differences treated as groups | merge around the shared job-to-be-done |
Where it sits
social-listening gathers recurring conversation → audience-personas groups it → positioning-audit turns it into a message.
Signals
- GitHub stars
- 28
- Forks
- 5
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
audience-personas- Source
- github.com/ootto-ai/claude-content-skills