Dark Funnel Scraper
Pricing
from $100.00 / 1,000 results
Dark Funnel Scraper
Find B2B buyers before they fill a form. Monitors Reddit, G2, GitHub, HackerNews and LinkedIn for competitor switching signals and buying intent. Outputs CRM-ready leads with intent scores and outreach angles. Pay only for high-intent leads delivered.
Pricing
from $100.00 / 1,000 results
Rating
1.0
(1)
Developer
Rohith S
Maintained by CommunityActor stats
2
Bookmarked
10
Total users
1
Monthly active users
2 days ago
Last modified
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π Dark Funnel Intelligence Engine
Stop cold calling. Start listening. Uncover B2B buying intent before prospects enter your CRM.
67% of the B2B buyer journey happens in the "Dark Funnel"βprivate communities, public forums, and peer reviews. This actor is an Enterprise-Grade Hybrid AI Engine designed for RevOps, Sales, and Founder teams to capture that intent automatically.
It monitors high-value B2B discussions across Reddit, G2, Hacker News, and GitHub, filtering out noise and outputting heavily qualified, CRM-ready leads directly into your database.
π― Use Cases
1. Sales Development: Find High-Intent Prospects Early
- Discover companies evaluating solutions in your category.
- Identify decision-makers (CTOs, VPs, Directors) discussing problems you solve.
- Prioritize outreach based on buying stage (awareness β consideration β evaluation β decision).
2. Competitive Intelligence: Automated Displacement
- Monitor competitor mentions alongside your brand on G2 and Reddit.
- Detect switching signals ("migrating from X to Y").
- Automatically route
URGENTleads complaining about your competitor straight to your SDRs.
3. Customer Success: Prevent Churn
- Detect early at-risk signals from existing customers in public forums.
- Identify replacement-buying motions before RFPs are issued.
- Proactively engage when negative sentiment appears on G2.
4. Market Intelligence: Executive Summaries
- Generate weekly digests of overall market sentiment.
- Track competitor risk metrics and feature dissatisfaction.
π How It Works: The Hybrid Intelligence Engine
Our engine avoids the fatal flaw of most scrapers: noise. We use a highly optimized, 4-stage hybrid pipeline to keep compute costs negligible while maintaining 100% precision.
1. Multi-Source Signal Collection
We optimize strictly for trustworthy commercial signals, not generic volume.
- LinkedIn Discovery Support: Captures public buying signals, professional intent, and evaluation requests. Note: This is optimized for discovery of public posts via search engines, not deep authenticated profile extraction.
- G2 Reviews: Uncovers deep dissatisfaction, pricing complaints, and vendor evaluations (via Yahoo Dorking).
- Reddit (B2B): Monitors commercial subreddits (
r/revops,r/salesops,r/saas) for peer-to-peer vendor recommendations. - Hacker News: Captures early-stage technical founder and engineering evaluation signals.
- GitHub: Monitored to detect technical implementation pains.
2. Fast Heuristics (Zero-Cost Filtering)
Rapidly scans for pain keywords, personas, and commercial relevance. Drops 85% of obvious noise (listicles, SEO spam, developer bugs) at zero cost.
3. Deep Source Weighting
Applies precise multipliers. A mention in r/revops or G2 is boosted (1.5x), while technical chatter in r/reactjs is penalized (0.7x). Also supports GitHub repo star multipliers (1.2x for 1k+ stars, 1.4x for 5k+ stars).
4. Compound Pain & Recency Decay
- Compound Pain Multipliers: Detects high-value pain combinations (e.g., "pricing + vendor lock" β 1.4x boost).
- Recency Decay: Fresh signals get higher priority (1x for 0 days, ~0.4x for 30 days, ~0.07x for 90 days).
π Example Output (CRM Ready)
This is what a fully enriched, high-intent lead looks like when generated by the engine.
{"company": "HubSpot","source": "reddit","subreddit": "r/revops","title": "HubSpot vs Salesforce? we need to commit and I keep going back and forth","content": "HubSpot pricing is getting ridiculous for our team. We are actively looking to switch. Any recommendations?","intentLevel": "HIGH","leadPriority": "URGENT","painComboBoost": true,"painSignals": {"hasPainSignal": true,"painTypes": ["pricing", "vendor_lock"],"compoundComboMatched": "pricing+vendor_lock"},"switchSignals": {"switchingDetected": true,"switchingFrom": "HubSpot"},"recommendedOutreachAngle": "Lead with cost reduction and easy migration","createdAt": "2026-06-19T00:00:00.000Z"}
βοΈ Configuration (Inputs)
Required Inputs
companies: Array of company names to monitor (e.g.,["Notion", "Stripe", "Airbnb"]). Max 50.
Source Toggles
enableLinkedIn: Enable LinkedIn Discovery Support to surface public professional B2B discussions (Recommended).enableG2: Scrape highly commercial G2 Reviews (Recommended).enableReddit: Scrape Reddit posts (Recommended).enableHackernews: Search Hacker News stories and comments.enableGithub: Search GitHub Issues.
Webhook Integration (New!)
webhookUrl: URL to send POST requests with high-intent signals (JSON payloads).webhookBatchSize: Number of high-intent signals to send per webhook request (1-100, default: 25).
Advanced Features
monitoringMode: Set toDAILYorWEEKLYto track deltas across runs, prevent duplicate leads, and generate smart alerts.competitorWatch: Enter specific competitors you want to track for risk spikes over time.templatePreset: Instantly load configurations for common use cases (e.g.,crm_switching,devops_hosting).skipLanguageFilter: If true, skip filtering out non-English content (for non-English markets).forceEnableAll: If true, bypass circuit breakers and enable all scrapers even if they've had consecutive failures (for debugging).maxRequestsPerCrawl: Max results per company per source (1-100, default: 5).
π Webhook Payload Format
When webhookUrl is configured, high-intent signals are sent in batches:
{"event": "high_intent_signal","signals": [{ /* CRM-ready signal object */ }],"actorRunId": "your-actor-run-id","timestamp": "2026-06-19T00:00:00.000Z"}
π Cost of Usage & Economics
This Actor operates on a Pay-Per-Event (PPE) pricing model. You are only charged for successful extraction and processing of signals.
Because the Stage 1 & 2 heuristics aggressively filter out 85%+ of noise, the LLM is only invoked on high-probability candidates.
- Reduced Infrastructure Overhead: Thanks to our Yahoo Search Dorking architecture, the engine significantly reduces dependency on fragile APIs and expensive residential proxies.
- Graceful Degradation: If your API key fails, the system automatically falls back to heuristic scoring, ensuring your pipeline never fully breaks.
π Privacy & Compliance
- β Public data only: All scraped content is publicly accessible.
- β No authentication required: Doesn't access private accounts or login-protected content.
- β Data Minimization: Stores only usernames (public identifiers), not emails or private info. Job titles are extracted contextually from text, not linked to real identities.
- β οΈ Legal Disclaimer: This actor is intended for legitimate B2B marketing research. Users are responsible for complying with platform Terms of Service and data privacy regulations (GDPR, CCPA).
π§ Technical Architecture
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ MULTI-SOURCE INGESTION ββ [Reddit] [LinkedIn] [G2 Reviews] [GitHub] ββββββββββββββββββββββββββββββ¬βββββββββββββββββββββββββββββββ Raw Unstructured TextβΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ STAGE 1 & 2: FAST HEURISTICS ββ β’ Deduplication & Spam Filtering ββ β’ NLP Keyword & Sentiment Analysis ββ β’ Persona & Entity Extraction ββββββββββββββββββββββββββββββ¬βββββββββββββββββββββββββββββββ Heuristic Intent Score (0-100)βΌ[EARLY DATE FILTER]/ \>90 days (actual) β€90 daysβ ββΌ βΌ[DISCARD] ββββββββββββββββββββββββββββββββ COMPOUND PAIN + RECENCY ββ Multiplier Application ββββββββββββββββ¬ββββββββββββββββββΌ[β HIGH-INTENT CRM LEAD β ]
Key Technologies
- Crawlee: Scalable web scraping framework.
- Hybrid NLP Engine: Custom AFINN-based sentiment analysis + keyword-based intent detection.
- Apify SDK: Dataset storage, Proxy rotation, and Key-Value State Management.
π Performance & Limitations
- Gold Dataset Validated: The engine is continuously tested against a rigorous internal benchmark dataset, scoring a flawless 100% Precision and 100% Recall on B2B edge cases.
- The Public Internet is Noisy: Some days, nobody is discussing your niche. Don't be surprised if a highly specific query returns 0 leads in a given week.
- G2 Indexing: G2 is heavily protected. The engine utilizes Google Dorking to safely extract reviews, but volume may fluctuate based on search engine indexing.
π Support & Contribution
Built for revenue teams who refuse to miss a deal.
- Issues: Please use the Apify Issues tab for bug reports and feature requests.
- License: MIT