apify-audience-analysis
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English🇨🇳
Translation
ChineseAudience Analysis
受众分析
Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.
使用Apify Actors分析并了解你的受众，从多个平台提取粉丝人口统计数据、互动模式和行为数据。
Prerequisites
前提条件
(No need to check it upfront)
- file with
.envAPIFY_TOKEN - Node.js 20.6+ (for native support)
--env-file - CLI tool:
mcpcnpm install -g @apify/mcpc
（无需预先检查）
- 包含的
APIFY_TOKEN文件.env - Node.js 20.6+（支持原生功能）
--env-file - CLI工具：
mcpcnpm install -g @apify/mcpc
Workflow
工作流程
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Identify audience analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings复制此清单并跟踪进度：
Task Progress:
- [ ] Step 1: Identify audience analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findingsStep 1: Identify Audience Analysis Type
步骤1：确定受众分析类型
Select the appropriate Actor based on analysis needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Facebook follower demographics | | FB followers/following lists |
| Facebook engagement behavior | | FB post likes analysis |
| Facebook video audience | | FB Reels viewers |
| Facebook comment analysis | | FB post/video comments |
| Facebook content engagement | | FB post engagement metrics |
| Instagram audience sizing | | IG profile demographics |
| Instagram location-based | | IG geo-tagged audience |
| Instagram tagged network | | IG tag network analysis |
| Instagram comprehensive | | Full IG audience data |
| Instagram API-based | | IG API access |
| Instagram follower counts | | IG follower tracking |
| Instagram comment export | | IG comment bulk export |
| Instagram comment analysis | | IG comment sentiment |
| YouTube viewer feedback | | YT comment analysis |
| YouTube channel audience | | YT channel subscribers |
| TikTok follower demographics | | TT follower lists |
| TikTok profile analysis | | TT profile demographics |
| TikTok comment analysis | | TT comment engagement |
根据分析需求选择合适的Actor：
| 用户需求 | Actor ID | 适用场景 |
|---|---|---|
| Facebook粉丝人口统计数据 | | Facebook粉丝/关注列表 |
| Facebook互动行为 | | Facebook帖子点赞分析 |
| Facebook视频受众 | | Facebook Reels观众 |
| Facebook评论分析 | | Facebook帖子/视频评论 |
| Facebook内容互动 | | Facebook帖子互动指标 |
| Instagram受众规模统计 | | Instagram账号人口统计数据 |
| Instagram基于位置的分析 | | Instagram带地理标签的受众 |
| Instagram标签网络分析 | | Instagram标签网络分析 |
| Instagram全面分析 | | Instagram完整受众数据 |
| Instagram基于API的分析 | | Instagram API访问 |
| Instagram粉丝数量跟踪 | | Instagram粉丝跟踪 |
| Instagram评论导出 | | Instagram评论批量导出 |
| Instagram评论分析 | | Instagram评论情感分析 |
| YouTube观众反馈 | | YouTube评论分析 |
| YouTube频道受众 | | YouTube频道订阅者 |
| TikTok粉丝人口统计数据 | | TikTok粉丝列表 |
| TikTok账号分析 | | TikTok账号人口统计数据 |
| TikTok评论分析 | | TikTok评论互动分析 |
Step 2: Fetch Actor Schema
步骤2：获取Actor架构
Fetch the Actor's input schema and details dynamically using mcpc:
bash
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"Replace with the selected Actor (e.g., ).
ACTOR_IDapify/facebook-followers-following-scraperThis returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)
使用mcpc动态获取Actor的输入架构和详细信息：
bash
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"将替换为所选的Actor（例如：）。
ACTOR_IDapify/facebook-followers-following-scraper此命令将返回：
- Actor描述和README
- 必填和可选输入参数
- 输出字段（如果可用）
Step 3: Ask User Preferences
步骤3：询问用户偏好
Before running, ask:
- Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
- Number of results: Based on character of use case
运行之前，询问以下内容：
- 输出格式：
- 快速回答 - 在聊天中显示前几条结果（不保存文件）
- CSV - 包含所有字段的完整导出
- JSON - JSON格式的完整导出
- 结果数量：根据使用场景的特点确定
Step 4: Run the Script
步骤4：运行脚本
Quick answer (display in chat, no file):
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'CSV:
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.csv \
--format csvJSON:
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format json快速回答（在聊天中显示，不生成文件）：
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'CSV格式：
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.csv \
--format csvJSON格式：
bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format jsonStep 5: Summarize Findings
步骤5：总结分析结果
After completion, report:
- Number of audience members/profiles analyzed
- File location and name
- Key demographic insights
- Suggested next steps (deeper analysis, segmentation)
完成后，报告以下内容：
- 分析的受众成员/账号数量
- 文件位置和名称
- 关键人口统计洞察
- 建议的后续步骤（深入分析、受众细分）
Error Handling
错误处理
APIFY_TOKEN not found.envAPIFY_TOKEN=your_tokenmcpc not foundnpm install -g @apify/mcpcActor not foundRun FAILEDTimeout--timeoutAPIFY_TOKEN not foundAPIFY_TOKEN=your_token.envmcpc not foundnpm install -g @apify/mcpcActor not foundRun FAILEDTimeout--timeout