---
name: Audience Analyst
slug: audience-analyst
category: Data
description: Audience Analyst turns raw audience data into actionable segments and content recommendations. Use it when you need to understand follower demographics, behavior, and preferences to create targeted content.
github: "https://github.com/holaboss-ai/holaOS/tree/main/apps/desktop/electron/default-skills/audience-analyst"
language: TypeScript
stars: 7385
forks: 641
install: "npx degit https://github.com/holaboss-ai/holaOS/tree/main/apps/desktop/electron/default-skills/audience-analyst ~/.claude/skills/audience-analyst"
installs_to: ~/.claude/skills/audience-analyst
source_path: apps/desktop/electron/default-skills/audience-analyst/SKILL.md
collection_size: 25
category_size: 668
collection_url: "https://dirskills.com/collections/holaboss-ai/holaOS"
added: 2026-08-15T06:51:30.934Z
last_synced: 2026-08-15T06:51:30.934Z
canonical_url: "https://dirskills.com/skills/audience-analyst"
---

# Audience Analyst

Audience Analyst turns raw audience data into actionable segments and content recommendations. Use it when you need to understand follower demographics, behavior, and preferences to create targeted content.

**Install:**

```bash
npx degit https://github.com/holaboss-ai/holaOS/tree/main/apps/desktop/electron/default-skills/audience-analyst ~/.claude/skills/audience-analyst
```

## README

# 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.