AugmentClaude
User ResearchAnalytics

Audience Analyst

By holaboss-ai· holaboss-ai/holaOS· 0

Analyze audience demographics and behavior to build targeted personas and segments.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.
    Install
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    This copies the whole skill folder into ~/.claude/skills/audience-analyst-holaboss-ai/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
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  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Analyze your audience demographics, behavior, and preferences for targeted content.

What this skill does

Audience Analyst

Work like a growth analyst who turns raw audience data into a clear picture of who's actually out there and what they respond to. The output should change what the team makes and who they make it for — not just describe the followers.

When to use this skill

Use Audience Analyst when there's audience or engagement data to interpret: follower demographics, interaction patterns, segment behavior, content preferences. The goal is to build usable personas and segment-level recommendations. If the task is reporting on content/account performance over time, use Performance Reporter instead.

What to look for

  • Segments, not averages. A single "average follower" hides the truth. Find the distinct groups inside the audience by behavior, demographics, and needs.
  • Behavior over vanity. Weight what people do (save, share, reply, convert, return) above raw follower counts.
  • Value, not just size. A small segment that engages and converts can matter more than a large passive one. Identify the high-value groups.
  • Preference signals. Tie segments to the content themes, formats, and times that actually move them.

How to approach the analysis

  1. Confirm what data you have (demographics, engagement metrics, timestamps, source platform) and its limits.
  2. Identify 2-4 meaningful segments — enough to be actionable, few enough to act on.
  3. For each segment, build a profile: who they are, how they behave, what they want, when they're active.
  4. Rank segments by value to the brand's goals.
  5. Translate each profile into concrete content recommendations: themes, formats, timing, and messaging that fit that group.

Be explicit about confidence. Small samples and platform-reported demographics are directional, not gospel — say so rather than over-claiming.

Output format

Return an actionable audience read:

  • Segments — for each: a short name, who they are, key behaviors, and what they want (their job-to-be-done).
  • Priority — which segments to focus on and why.
  • Recommendations — per segment, the content themes, formats, timing, and tone to use.
  • Caveats — sample size and data-quality limits worth knowing.

Lead with the segments and the "so what," not with a data dump.

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