Building a Reddit Social Listening Workflow with OpenClaw
A developer has shared their experience building a Reddit social listening workflow using OpenClaw to automate brand monitoring tasks that previously required manual effort.
Workflow Components
The system consists of several key components:
- Data Collection: Since Reddit didn't provide an API key, the developer created a fallback system using JSON and HTML scraping. Data is pulled from multiple endpoints including new Reddit and old Reddit, with user agent rotation to maintain functionality.
- Post Analysis: Each post is analyzed for intent (recommendation requests, complaints, comparisons), competitor mentions with sentiment analysis, and basic risk signals (spammy threads, locked posts).
- Ranking System: Posts are ranked based on multiple factors including relevance, freshness, engagement, and intent.
- Brand Matching: Posts are compared with a brand profile (keywords, competitors, buyer intent) using semantic similarity to find related topics.
- Data Storage: Results are added to Google Sheets every hour using a cron job and Google Workspace CLI.
- Learning System: The developer reviews posts in the sheet, marking them as saved or irrelevant. The system learns from this feedback to improve future searches.
Current Limitations
The developer notes several challenges with the current implementation:
- Adding more brand profiles causes the system to break
- Sometimes returns results that are completely out of context, possibly due to using an LLM to create brand profiles
- Currently spending significant time fixing code issues
The workflow has improved results and speed compared to manual monitoring, but the developer acknowledges it's not perfect yet and is seeking insights from others who have worked on similar projects.
📖 Read the full source: r/openclaw
👀 See Also
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