Apify Brand Reputation Monitoring
Pull reviews, ratings, and social mentions from Google Maps, Booking, TripAdvisor, and major social platforms into structured datasets for reputation tracking.
Overview
Apify Brand Reputation Monitoring is an agent skill most often used in Grow (also Launch distribution checks, Operate support triage) that orchestrates Apify Actors and mcpc to scrape reviews, ratings, and brand mentions
Install
npx skills add https://github.com/apify/agent-skills --skill apify-brand-reputation-monitoringWhat is this skill?
- Five-step checklist workflow from Actor selection through scripted run and results summary
- Platform routing table mapping user needs to Apify Actor IDs (Google Maps, Booking, TripAdvisor, and more)
- Runs via mcpc CLI against Actor schemas with user-chosen output format and filename
- Requires APIFY_TOKEN in `.env` and Node 20.6+ for native `--env-file` loading
- Covers business reviews, hotel scores, and attraction/restaurant feedback use cases
- 5-step workflow checklist from Actor selection through results summary
- Actor routing table for Google Maps, Booking.com, and TripAdvisor review sources
Adoption & trust: 2.5k installs on skills.sh; 2.1k GitHub stars; 1/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need cross-platform review and mention data in one place but each site uses a different shape and there is no maintained scraper in your repo.
Who is it for?
Indie SaaS or local businesses monitoring Google Maps, travel listings, or social mentions on a schedule with an existing Apify account.
Skip if: Builders without APIFY_TOKEN, legal clearance for scraping, or a need that is satisfied by a single platform’s official API only.
When should I use this skill?
User asks to monitor brand reputation, analyze reviews, track mentions, or gather customer feedback.
What do I get? / Deliverables
You get a defined Actor run, saved export, and agent-written summary of reputation signals you can feed into dashboards, alerts, or support workflows.
- Exported review and mention dataset in user-selected format
- Actor run configured from fetched schema
- Agent summary of monitoring results
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Canonical shelf is Grow because the skill’s outcome is ongoing measurement of customer sentiment and mentions after you have something in market to defend. Analytics fits best: exported ratings, review text, and mention counts are inputs to dashboards, alerts, and quarterly reputation reports—not one-off launch copy.
Where it fits
Pull recent Maps and social mentions right before a Product Hunt or press push to know baseline sentiment.
Schedule Actor runs into a weekly CSV for rating trends and review volume by location.
Correlate negative Booking or TripAdvisor reviews with churn emails for a hospitality side project.
How it compares
Use this Apify Actor workflow instead of hand-maintaining per-site scrapers when you already standardize on Apify and mcpc.
Common Questions / FAQ
Who is apify-brand-reputation-monitoring for?
Solo builders and small teams shipping products who must track reviews and mentions across maps, hospitality, and social platforms without building bespoke crawlers for each site.
When should I use apify-brand-reputation-monitoring?
Use it in Grow when you refresh sentiment dashboards or escalation rules; at Launch when you baseline reputation before a push; and in Operate when support needs recent negative reviews pulled into a ticket context.
Is apify-brand-reputation-monitoring safe to install?
Treat it as code that uses your APIFY_TOKEN, network access, and third-party Actors—review the Security Audits panel on this Prism page and your Apify usage policy before running in production.
SKILL.md
READMESKILL.md - Apify Brand Reputation Monitoring
# Brand Reputation Monitoring Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors. ## 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 co