home / skills / apify / agent-skills / apify-brand-reputation-monitoring

apify-brand-reputation-monitoring skill

/skills/apify-brand-reputation-monitoring

This skill monitors brand reputation by scraping reviews, mentions, and sentiment across major platforms to help track feedback and ratings.

npx playbooks add skill apify/agent-skills --skill apify-brand-reputation-monitoring

Review the files below or copy the command above to add this skill to your agents.

Files (2)

SKILL.md

4.4 KB

---
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)

- `.env` file with `APIFY_TOKEN`
- Node.js 20.6+ (for native `--env-file` support)
- `mcpc` CLI tool (for fetching Actor schemas)

## 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`

Overview

This skill monitors brand reputation by scraping reviews, ratings, sentiment signals, and mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. It orchestrates Apify Actors to collect structured review data and export results in quick chat summaries, CSV, or JSON. Use it to gather customer feedback, detect sentiment trends, and surface urgent issues across major review and social platforms.

How this skill works

Select the appropriate Apify Actor for the target platform, fetch the actor input schema, and run a monitoring script that passes the chosen input to the actor. The tool can return a quick summary in chat or save a full export as CSV or JSON. After the run, it summarizes counts, key fields, and suggests follow-up steps such as sentiment analysis or filtering.

When to use it

You need to collect recent reviews and ratings for a business or listing across multiple platforms.
You want to track brand mentions or hashtags on Instagram, TikTok, or YouTube comments.
You need a repeatable export (CSV/JSON) for downstream analysis or dashboards.
You want quick chat summaries of top mentions without saving a file.
You must investigate sudden drops in ratings or spikes in negative sentiment.

Best practices

Choose the Actor that best matches the target platform and data granularity (reviews vs. comments).
Fetch the actor schema first to confirm required input fields and optional filters.
Start with a small result set to validate inputs before running large exports.
Prefer JSON exports for downstream processing and CSV for manual review or spreadsheets.
Store APIFY_TOKEN in a .env file and ensure mcpc is installed if you fetch actor details.

Example use cases

Weekly scraping of Google Maps and TripAdvisor reviews for a hotel, with CSV exports for the analytics team.
Daily monitoring of Instagram hashtags and tagged posts to find emerging product complaints.
Pull YouTube and TikTok comments for recent campaign videos to measure sentiment and engagement.
Quick chat summary of the latest Facebook page reviews to respond to urgent negative feedback.
Export Booking.com reviews for a set of properties for monthly reputation reporting.

FAQ

What credentials do I need to run monitoring?

Place APIFY_TOKEN in a .env file; Node.js 20.6+ is required for the native --env-file flag.

How do I know which Actor to use?

Match the user need to the Actor list (e.g., Google Maps reviews -> compass/crawler-google-places). Fetch the actor schema to confirm inputs.

What if I get an APIFY_TOKEN not found error?

Create a .env file with APIFY_TOKEN=your_token and re-run the command.