Problem
Reddit is a real-time stream of people describing problems they're ready to pay someone to solve. Phrases like "is there a way to automate this" or "how much would it cost to build" signal someone mid-decision, not mid-research. The problem is volume and timing. Manually scanning subreddits for relevant posts is impossible at scale, and by the time you find a genuine buyer, someone else already replied.
Results
- Zero daily monitoring time: System runs 24/7 with no manual scanning required
- Under 15-minute alert time: From post detection to Telegram notification with pre-drafted reply
- 60+ exclusion patterns: Three-layer SOLR filter plus AI qualification eliminates false positives
- Up to $18,000-$26,000/year recovered: At $100/hr consulting rate, replacing 3.5-5 hours of weekly manual monitoring
Before vs After
Before: 30-40 minutes per day manually scanning Reddit across multiple subreddits, seven days a week. Inconsistent coverage, no tracking, missed opportunities, and no data on which subreddits or post types convert.
After: Alerts arrive only when a real match fires. Engagement drops from hours to under 10 minutes per lead because the reply is already drafted. Full feedback loop tracks time-to-engage, subreddit performance, and conversion patterns automatically.
Client Goal
Build a passive lead generation channel from Reddit that identifies qualified buyers in real time, delivers actionable notifications, and creates a closed-loop system that gets smarter over time without requiring daily manual effort.
Challenges
- Signal buried in noise: Reddit mixes genuine buyer intent with students, competitors, self-promotion, and completely unrelated automation topics (Minecraft, home automation, debugging threads)
- Timing determines visibility: Reddit's algorithm surfaces early comments. A reply in the first hour gets exponentially more visibility than one posted twelve hours later. Manual monitoring cannot compete with that clock
- False positives kill efficiency: Job postings, budget flags ("I'm broke"), dev forum questions, and mod messages all pattern-match on surface keywords but waste time when acted on
- No engagement tracking: Without a feedback loop measuring which subreddits convert, which posts get replies fastest, and which patterns lead to clients, Reddit stays a guessing game instead of a data-driven channel
Solution Overview
We built a real-time Reddit monitoring engine powered by a custom SOLR search query running against Reddit's post feed 24/7. Posts pass through a three-layer positive filter (buying intent, manual process pain, AI/automation relevance) and a NOT layer with 60+ exclusion patterns. Qualified posts trigger an n8n workflow that adds AI qualification, pulls full thread context, drafts targeted replies, and delivers everything to Telegram with one-tap action buttons for posting and CRM logging.
How It Works
- SOLR Real-Time Scraper: A custom SOLR-powered scraper monitors Reddit's post feed continuously. The structured boolean filter checks three positive layers: buying/hiring intent (25+ signal phrases), manual process pain (frustration keywords), and AI/automation relevance (tool and category keywords). All three layers must match
- NOT Layer Filtering: Over 60 exclusion patterns remove false positives: job postings, self-promotion, budget flags, dev forum debugging, geo exclusions, bot/mod patterns, and unrelated automation topics. Only genuine business buyers who need workflow automation pass through
- AI Qualification: Posts clearing the SOLR filter hit an AI qualification node in n8n. This second pass reads the post with full context and confirms genuine buyer intent. Binary output: drop or pass
- Thread Context Retrieval: The workflow pulls the complete Reddit thread for passing posts: original post, triggering comment, top comments with their replies. The AI uses this context to draft something that adds unique value the existing replies haven't covered
- AI Reply Drafting: The AI Agent analyzes three dimensions: whether the original poster is the real buyer, whether the triggering commenter is expressing a need, and what value hasn't been covered yet. It picks a reply strategy and drafts targeted outreach accordingly
- Telegram Notification + CRM Logging: The drafted reply lands as a Telegram message with post metadata and two inline action buttons. "Sent" triggers the engagement tracker (Make.com detects the new Reddit comment, fires back to n8n, logs time-to-engage in Google Sheets). "Log to CRM" creates a Notion entry with lead details, pipeline stage, and post URL. Button changes to "Logged to CRM" to prevent duplicates
Key Features
- Three-layer positive filter + NOT layer: Structured SOLR boolean query with 25+ intent signals, pain keywords, relevance checks, and 60+ exclusion patterns for near-zero false positive rate
- AI-powered double qualification: Keyword filter catches surface intent, AI qualification layer reads full context to confirm genuine buyer. Two gates, not one
- Pre-drafted contextual replies: AI reads the entire thread before drafting, so every reply adds unique value instead of repeating what others said
- Closed-loop engagement tracking: Make.com detects posted replies, matches them to detected posts in Google Sheets, and logs time-to-engage. Over time, the data shows which subreddits convert, which post patterns produce clients, and how fast opportunities are being captured
- One-tap CRM pipeline: Telegram action button creates a Notion entry with all lead context in a single tap. Pipeline stage, subreddit, drafted outreach, first contact date, and post URL all logged automatically
Tools Used
n8n
Core workflow orchestration. Handles AI qualification, thread retrieval, reply drafting, Telegram delivery, and engagement tracking logic
SOLR (via Syften)
Real-time Reddit monitoring with structured boolean filter queries. Three positive layers plus 60+ exclusion patterns running 24/7
OpenAI
AI qualification layer confirms genuine buyer intent. AI Agent drafts contextual replies after analyzing the full thread
Telegram
Notification delivery with pre-drafted replies and inline action buttons for posting and CRM logging
Make.com
Engagement tracker. Detects new Reddit comments, matches to original detected posts, and logs time-to-engage metrics
Google Sheets
Engagement data store. Logs detected posts, engagement timestamps, and time-delta metrics for performance analysis
Notion
CRM pipeline. One-tap logging from Telegram creates entries with lead context, pipeline stage, drafted outreach, and post URL
Video Walkthrough
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