/apify-brand-reputation-monitoring

name: apify-brand-reputation-monitoring
description: "Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors."
risk: critical
source: community
date_added: "2026-09-04"

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:

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):**

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`

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.