apify-brand-reputation-monitoring
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
- License 许可
- MIT
- 最近更新
- 2026-04-14
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- ★ 0
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01 前言 Front Matter
- name
- apify-brand-reputation-monitoring
- risk
- unknown
- source
- community
- description
- Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
02 资源文件 1
- 脚本reference/scripts/run_actor.js11.5 KB
03 SKILL.md 正文
Brand Reputation Monitoring
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
When to Use
- You need to monitor reviews, ratings, or brand mentions across social, travel, or map platforms.
- The task is to select and run an Apify Actor for brand sentiment or reputation tracking.
- You need exported monitoring results and a summary of reputation signals.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool:npm install -g @apify/mcpc
Workflow
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Determine data source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the monitoring script
- [ ] Step 5: Summarize results
Step 1: Determine Data Source
Select the appropriate Actor based on user needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Google Maps reviews | compass/crawler-google-places |
Business reviews, ratings |
| Google Maps review export | compass/Google-Maps-Reviews-Scraper |
Dedicated review scraping |
| Booking.com hotels | voyager/booking-scraper |
Hotel data, scores |
| Booking.com reviews | voyager/booking-reviews-scraper |
Detailed hotel reviews |
| TripAdvisor reviews | maxcopell/tripadvisor-reviews |
Attraction/restaurant reviews |
| Facebook reviews | apify/facebook-reviews-scraper |
Page reviews |
| Facebook comments | apify/facebook-comments-scraper |
Post comment monitoring |
| Facebook page metrics | apify/facebook-pages-scraper |
Page ratings overview |
| Facebook reactions | apify/facebook-likes-scraper |
Reaction type analysis |
| Instagram comments | apify/instagram-comment-scraper |
Comment sentiment |
| Instagram hashtags | apify/instagram-hashtag-scraper |
Brand hashtag monitoring |
| Instagram search | apify/instagram-search-scraper |
Brand mention discovery |
| Instagram tagged posts | apify/instagram-tagged-scraper |
Brand tag tracking |
| Instagram export | apify/export-instagram-comments-posts |
Bulk comment export |
| Instagram comprehensive | apify/instagram-scraper |
Full Instagram monitoring |
| Instagram API | apify/instagram-api-scraper |
API-based monitoring |
| YouTube comments | streamers/youtube-comments-scraper |
Video comment sentiment |
| TikTok comments | clockworks/tiktok-comments-scraper |
TikTok sentiment |
Step 2: Fetch Actor Schema
Fetch the Actor's input schema and details dynamically using mcpc:
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 ACTOR_ID with the selected Actor (e.g., compass/crawler-google-places).
This returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)
Step 3: Ask User Preferences
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
Step 4: Run the Script
Quick answer (display in chat, no file):
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'
CSV:
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 csv
JSON:
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
Step 5: Summarize Results
After completion, report:
- Number of reviews/mentions found
- File location and name
- Key fields available
- Suggested next steps (sentiment analysis, filtering)
Error Handling
APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token
mcpc not found - Ask user to install npm install -g @apify/mcpc
Actor not found - Check Actor ID spelling
Run FAILED - Ask user to check Apify console link in error output
Timeout - Reduce input size or increase --timeout
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