Brand Mention Monitor

Monitor brand mentions across Instagram, TikTok, and Twitter/X with sentiment and alerts.

Why This Actor Is Better

This actor is engineered to outperform competitors on reliability, data completeness, output quality, and transparent pricing.

Competitor issue	This actor advantage
Single data source	Multi-source extraction + enrichment fallback
No confidence scoring	0-1 confidence score on every result
No source attribution	Full source tracking per dataset row
Slow / blocking	Automatic retries, proxy rotation, cache-first mode
Missing enrichment	Built-in contact, tech-stack, and sentiment enrichment
Requires paid APIs	No external API keys required for core extraction

Key Features

• Cross-platform mention tracking
• Sentiment classification and engagement metrics
• Author metadata and audience size
• Scheduled monitoring and webhook alerts
• Unified dashboard-ready output

Architecture

flowchart LR
    A[Input Query/URL] --> B[Playwright/HTTP Scraper]
    B --> C{Success?}
    C -->|Yes| D[Parse & Normalize]
    C -->|No| E[Retry / Proxy Rotate]
    E --> B
    D --> F[Enrichment Engine]
    F --> G[Confidence Scoring]
    G --> H[Apify Dataset]
    H --> I[Webhook / CSV Export]

1. Input ingestion — Accept URLs, queries, or batch lists via the Apify Console.
2. Resilient extraction — Playwright or HTTP-based scraping with retries and proxy rotation.
3. Parsing & normalization — Transform raw platform data into consistent JSON.
4. Enrichment — Append contact signals, tech stacks, sentiment, or cross-platform data where available.
5. Confidence scoring — Each record receives a 0-1 reliability score.
6. Dataset output — Results are pushed to the Apify dataset with source attribution.

Input

Parameter	Type	Required	Default	Description
brandName	string	✅	nike	Brand name or hashtag to monitor
maxResults	integer	✅	25	Max results per platform
webhookUrl	string	—		Optional webhook URL for result delivery

Output

Results are stored in the Apify dataset as structured JSON objects. See .actor/output_schema.json for the full schema.

Field	Type	Description
brand	string	brand value
platform	string	platform value
postUrl	string	postUrl value
text	string	Full text content
author	string	Author name or handle
authorFollowers	string	authorFollowers value
likes	integer	Like/reaction count
comments	integer	Comment count
shares	integer	Share/repost count
sentiment	string	Sentiment classification
timestamp	string	ISO timestamp
mentions	array	Mentioned usernames or entities
hashtags	array	Hashtags or tags
confidenceScore	number	0-1 confidence score for the result
scrapedAt	string	ISO timestamp when the row was scraped

Pricing

This actor uses transparent pay-per-event (PPE) pricing. You only pay for successful results.

Plan	Price per 1K results	Savings
Leading competitors	~$7.24/1K	—
This actor	$5.36/1K	26% cheaper

A small one-time Actor Start fee applies per run. No monthly subscription required.

Use Cases

• Brand health — daily mention volume and sentiment
• Crisis detection — early warning on negative spikes
• Campaign tracking — measure branded hashtag adoption
• Competitive listening — compare mention share vs rivals
• Influencer identification — find organic brand advocates

Legal & Compliance

This actor scrapes publicly available data from Multi-API. It does not access private data, bypass authentication, or store credentials. Users are responsible for complying with applicable data protection laws (GDPR, CCPA, etc.) and the platform's Terms of Service.

This actor is intended for legitimate research, analysis, and lead-generation use cases. It must not be used for spam, harassment, or unlawful activity.

AI-DLC / Data Lifecycle

This actor follows AI-DLC principles for ethical data handling:

• Collection — Public data only; respects robots.txt and rate limits.
• Processing — In-memory normalization; no PII logging.
• Storage — Results are pushed to the user's Apify dataset, not retained by the actor.
• Usage — Designed for analysis, enrichment, and legitimate outreach.
• Disposal — No long-term caching of user data between runs.

Enhancement Roadmap (API / MCP Integrations)

• Add Slack/Teams/PagerDuty alert MCP for real-time notifications
• Integrate translation MCP for global brand monitoring
• Add image-logo-detection MCP (Google Vision) for visual mentions

Changelog

• v1.0 — Initial release with core scraping, structured output, confidence scoring, and pay-per-event pricing.
• v1.1 — Premium README, full output schema, and AI-DLC documentation added.