Automate Reddit Topic Intelligence with n8n + AI

Reddit has deep, fast-moving discussions where buyers and practitioners surface pains in real time. When you respond with helpful context, you earn trust and organic marketing opportunities. This guide shows how to automate a Reddit → AI → team workflow in n8n so you never miss conversations that matter to your product narrative.

Why automate Reddit monitoring?

• Volume and speed: Subreddits update continuously; manual tracking is noisy and slow.
• Relevance filtering: Large threads contain tangents. AI summaries keep only the signal.
• Team awareness: Marketing, product, and sales each need tailored next steps. Automation routes insights to the right people.

Architecture at a glance

1. Ingestion: n8n polls Reddit search or subreddit feeds on a schedule.
2. Enrichment: AI cleans and summarizes posts + comment context into crisp takeaways.
3. Relevance scoring: Prompted AI ranks items by your ICP, topics, and red flags.
4. Routing: High-scoring items flow to Slack/Email/Notion for owners; low-signal items are archived.
5. Feedback loop: Owners mark "actioned" vs. "ignore" to retrain prompts and filters.

Prerequisites

• An n8n instance (self-hosted or cloud) with a persistent queue.
• Reddit app credentials (client ID/secret) for the API.
• An OpenAI-compatible model key (e.g., OpenAI or hosted alternatives).
• Destination apps: Slack, email, Notion, or HubSpot.

Step-by-step n8n flow

1) Trigger: Scheduled Reddit search

• Use Schedule trigger (e.g., every 30 minutes) followed by HTTP Request nodes hitting https://oauth.reddit.com/r/{subreddit}/search with q="your keywords" and sort=new.
• Store post_id, title, URL, author, upvotes, subreddit, and top comment excerpts.
• Persist the post_id in a Postgres or Data Store node to avoid duplicates.

2) Normalize content

• Add a Function Item node to trim text, strip markdown, and limit body length before AI calls.
• Create a compact payload:
  • headline
  • problem_statement
  • evidence (upvotes/comments)
  • link
  • subreddit

3) AI summarization + scoring

• Use an OpenAI (or generic HTTP Request) node with a system prompt such as:

  You are a B2B marketing analyst. Summarize the post in 80 words. Extract buyer pain, urgency, and any product gaps. Score relevance 1-5 for teams: Marketing, Product, Sales.
  Return JSON with: summary, pains[], urgency, marketing_score, product_score, sales_score, recommended_action.
  

• Set temperature low (0.2–0.4) for consistency. Map scores to fields for later routing.

4) Decision + branching

• Add an IF node that checks marketing_score >= 4 OR product_score >= 4.
• High-signal branch:
  • Send a Slack message to #market-intel with the summary, scores, and link.
  • Create/append a Notion page (or Google Sheet) with metadata for weekly review.
• Low-signal branch: Archive to a Data Store and mark as "ignored" for reporting.

5) Feedback capture

• In Slack, ask recipients to react with ✅ or ❌. Use an On Reaction Added trigger (or scheduled Slack history fetch) to update the Notion row with actioned=true/false.
• Add a nightly Function node that aggregates feedback and exports a CSV of kept vs. ignored posts.

6) Prompt tuning loop

• Weekly, feed the CSV back into an OpenAI fine-tune or use it to update prompt examples:
  • Include positive examples where teams engaged.
  • Include negative examples that looked relevant but were noise.
• This raises precision and reduces Slack fatigue.

Example variables to parameterize

Variable	Purpose	Example
subreddits	Audience clusters	r/devops, r/QualityAssurance, r/startups
keywords	Pain signals	"release pipeline", "flaky tests", "compliance", "load testing"
urgency_threshold	Branching signal	marketing_score >= 4
routing_channels	Team destinations	#market-intel, #product-voice, CSM email list

Tips for production hardening

• Rate limits: Reddit caps requests; keep intervals to 30–60 seconds and cache tokens.
• Security: Store API keys as n8n credentials; avoid hardcoding secrets in Function nodes.
• Observability: Log every decision (scores, branch taken) to a database for reporting.
• De-duplication: Hash (subreddit + post_id) and check before sending alerts.
• Throttling: Batch Slack posts (e.g., 5 items per message) to reduce noise.
• Failover: Add retries and dead-letter queues for API failures.

How teams can act on the insights

• Marketing: Draft empathetic comments linking to playbooks, case studies, or upcoming webinars.
• Product: Capture recurring pains as backlog insights with priority based on urgency scores.
• Sales/CS: Proactively reach out to accounts if the thread matches their tech stack or challenges.

KPIs to prove value

• Response time to relevant threads (minutes instead of hours).
• Number of meaningful replies left by the team per week.
• Growth in inbound demos mentioning Reddit conversations.
• Reduction in "noise" alerts after prompt tuning.

Deployment checklist

• n8n credentials created for Reddit + OpenAI + Slack/Notion.
• Data store created for deduplication and logs.
• Schedule tuned to respect rate limits.
• Prompt and routing logic tested against 10 sample posts.
• Stakeholder channels agreed (who owns what).

Wrap-up

With a small, well-instrumented n8n workflow, you can turn Reddit’s firehose into curated, actionable intelligence. Pairing AI summarization with clear routing rules keeps your team present in the conversations that matter—earning goodwill, learning from the market, and opening authentic marketing opportunities.