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audience-research

用于创作者、网红或品牌的受众研究:整合公开主页信号、TikTok受众画像、地域、语言、粉丝与评论等证据,判断目标市场匹配度、赞助适配度与数据置信度,并按模板生成研究报告;对平台未公开的人口统计只做有限推断并标注置信度。

ScrapeCreators
热度 0.00
最近更新 2026-10-19 01:43:26
分类:营销依赖:第三方 API / 代码执行 / 读写文件 / 联网浏览搜索应用场景:市场分析 / 社交媒体 / 研究 / 推荐

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add scrapecreators/social-media-research-skills/audience-research
Metadata
name
audience-research
description
Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
allowed-tools
Bash, Read, Write, WebFetch
version
1.0.0
author
ScrapeCreators
license
MIT
homepage
https://scrapecreators.com
repository
https://github.com/ScrapeCreators/social-media-research-skills
metadata
{"openclaw":{"requires":{"env":["SCRAPECREATORS_API_KEY"]},"primaryEnv":"SCRAPECREATORS_API_KEY","homepage":"https://scrapecreators.com","tags":["social-media","research","scrapecreators"]}}

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.