apify-brand-reputation-monitoring
apify/agent-skills
Monitor brand reputation across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok.
What is apify-brand-reputation-monitoring?
Scrapes reviews, ratings, sentiment, and brand mentions from 8+ platforms using Apify Actors. Use this when you need to track customer feedback, analyze reviews, monitor brand mentions, or gather reputation data across multiple channels.
- Scrape reviews and ratings from Google Maps, Booking.com, and TripAdvisor
- Monitor Facebook page reviews, comments, and reactions
- Track Instagram comments, hashtags, mentions, and tagged posts
- Analyze YouTube and TikTok comments for sentiment
- Export data in CSV or JSON format for further analysis
- Dynamically fetch Actor schemas to understand available parameters
How to install apify-brand-reputation-monitoring
npx skills add https://github.com/apify/agent-skills --skill apify-brand-reputation-monitoring- APIFY_TOKEN in .env file
- Node.js 20.6 or later
- mcpc CLI tool installed (npm install -g @apify/mcpc)
How to use apify-brand-reputation-monitoring
- 1.Determine which platform and data type you need (reviews, comments, mentions, ratings)
- 2.Select the appropriate Actor ID from the provided table based on your data source
- 3.Fetch the Actor's input schema using mcpc to understand required parameters
- 4.Ask user for output preferences (quick answer, CSV, or JSON format)
- 5.Run the monitoring script with the selected Actor ID and user-provided input
- 6.Summarize results including count of items found, file location, and available fields
Use cases
- Monitor hotel or restaurant reviews across Booking.com and TripAdvisor to track customer satisfaction
- Track brand mentions and hashtags on Instagram to measure social media presence
- Analyze Facebook page reviews and comments to identify customer concerns
- Gather YouTube video comments to assess audience sentiment about your brand
- Export review data to CSV for sentiment analysis and reporting
- Brand managers tracking online reputation
- Customer service teams monitoring feedback across platforms
- Marketing teams analyzing social media sentiment
- Hospitality businesses monitoring guest reviews
- E-commerce businesses tracking product feedback
apify-brand-reputation-monitoring FAQ
Choose based on your target: Google Maps for local business reviews, Booking.com for hotels, TripAdvisor for attractions/restaurants, Facebook for page reviews, Instagram for hashtag/mention tracking, YouTube for video comments, TikTok for short-form video sentiment.
Three options: Quick answer (display results in chat only), CSV (full export with all fields), or JSON (full export in JSON format).
Yes, you need APIFY_TOKEN in your .env file, Node.js 20.6+, and the mcpc CLI tool (install with npm install -g @apify/mcpc).
Check the Apify console link in the error output, verify the Actor ID spelling, reduce input size if timeout occurs, or ask the user to check their Apify account status.
Yes, you can export results as CSV or JSON files with all available fields for sentiment analysis, filtering, or reporting.
Full instructions (SKILL.md)
Source of truth, from apify/agent-skills.
name: apify-brand-reputation-monitoring description: Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze reviews, track mentions, or gather customer feedback.
Brand Reputation Monitoring
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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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