--- name: apify-brand-reputation-monitoring description: "Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors." risk: unknown source: community --- # 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) - `.env` file with `APIFY_TOKEN` - Node.js 20.6+ (for native `--env-file` support) - `mcpc` CLI 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: ```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 `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: 1. **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 2. **Number of results**: Based on character of use case ### Step 4: Run the Script **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 csv ``` **JSON:** ```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 ``` ### 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`