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audience-research

audience-research

github.com/scrapecreatorsMarketing & growth5.0k1.3k installsUpdated 9w ago
Repository

About audience-research

A skill for assessing whether a creator or social account reaches a target audience. It combines available public metrics, demographics, regional and language signals, comments, and content topics, while labeling confidence.

Key features

  1. 01Review of public profile and audience data
  2. 02Analysis of region, language, and niche signals
  3. 03Comparison with target-market needs
  4. 04Confidence labels based on available evidence

Use cases

  1. 01Check creator fit for a target market
  2. 02Compare audience fit across creators
  3. 03Assess influencer or sponsorship opportunities
  4. 04Understand who engages with an account

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/scrapecreators/social-media-research-skills --skill audience-research

After installing, type/audience-researchin Claude Code to confirm it loaded.

Details

From the project README

Audience Research

Overview

Evaluate whether a creator or social account reaches the right audience. This skill combines available public profile metrics, TikTok audience demographics, regional signals, follower/following data when available, comments, language, and content topics.

When to Use

Use this skill when the user asks to:

  • check if a creator's audience fits a market
  • compare audience fit across creators
  • find US-heavy, country-specific, or niche-specific creators
  • evaluate sponsorship/influencer opportunities
  • understand who appears to engage with an account

Useful Sources

  • /v1/tiktok/user/audience
  • /v1/tiktok/profile/region
  • profile endpoints across platforms
  • follower/following endpoints where available
  • comments on recent posts
  • link-in-bio pages and creator shops for niche signals

Workflow

  1. Pull profile and available audience/demographic data.
  2. Pull recent content and comments if audience intent matters.
  3. Extract region, language, niche, product/category, and community signals.
  4. Score audience fit against the user's target market.
  5. Label confidence based on the strength of public data.

Output Format

# Audience Research: {creator}

## Fit Summary
- Target market:
- Fit score: High/Medium/Low
- Confidence: High/Medium/Low

## Evidence
| Signal | Evidence | Source |
|---|---|---|

## Audience Notes
- Geography:
- Language:
- Niche/content fit:
- Comment quality:

## Sponsorship Recommendation
- Good fit / Maybe / Poor fit
- Why:

Common Pitfalls

  • Do not infer exact demographics from vibes. Use available evidence and label assumptions.
  • Do not overpromise audience details for platforms that do not expose them publicly.
  • Do not ignore mismatch between creator location and audience location.

Comments

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