Built with BubbleLab · Automated · Weekly delivery
A fully automated pipeline that scrapes Reddit every week, clusters real user complaints into startup ideas, scores them for market viability, and lands in your inbox every Monday morning - no manual effort required.
💡 The output: A ranked report of 5–10 startup ideas, each with: problem description, target audience, willingness-to-pay evidence, monetisation model, competitor gaps, and suggested next steps.
| Subreddits scraped | 6 |
| Posts per run | 300+ |
| Ideas ranked | 5–10 |
| Runs automatically | Every Monday, 9am GMT |
Built entirely in BubbleLab using their visual workflow builder — no infrastructure setup, no server management. The flow runs on a cron schedule and chains three tools together.
1 → Scrape Reddit Pulls top posts from the past week across 6 subreddits: r/smallbusiness, r/Entrepreneur, r/problems, r/SaaS, r/NoStupidQuestions, r/PersonalFinance. Filters for minimum 50 upvotes and 10 comments to ensure real engagement.
2 → AI Analysis (Gemini 3 Pro) Clusters posts by problem theme. For each cluster: defines the problem, identifies the audience, scores willingness-to-pay (0–10) from comment language, recommends a monetisation model, and uses web search to audit existing solutions.
3 → Email Report via Resend Formats findings into a structured HTML email and delivers it every Monday at 9am GMT. Each idea includes WTP quotes, competitor gaps, and a suggested next step.
| Layer | Detail |
|---|---|
| Platform | BubbleLab.ai — visual workflow builder |
| AI Model | Google Gemini 3 Pro Preview |
| Web Search | Built-in tool for competitor research |
| Email Delivery | Resend (transactional email API) |
| Trigger | Cron — every Monday 9:00am GMT |
| Output Schema | Zod-validated JSON → structured HTML email |
Ideas are ranked by a composite score: frequency × engagement × WTP score. This surfaces problems that are both high-volume and backed by genuine intent to pay — not just popular gripes.
Rank ideas by: (frequency × engagement × WTP score)
WTP score: extract exact quotes — "I'd pay", "worth paying for", "would switch from X"
Existing solutions: use web search — expensive? missing features? complained about?