About Trend Seeker
Market intelligence from real demand evidence
We turn live user pain and market signals into business ideas you can inspect, compare, and validate.
Scan public conversations, funded work, reviews, podcasts, and search activity for repeated demand signals.
Track fresh ideas and ideas gaining new evidence.
Unlock deeper source signals and full Pro idea details.
The Problem
Useful market evidence is scattered across community discussions, hiring plans, podcast conversations, product reviews, search activity, and new launches. Each source provides a partial view, and repeated posts or copied observations can make demand look stronger than it is. Trend Seeker organizes that activity into evidence people can inspect without treating every mention as an independent customer.
What Trend Seeker Does
Trend Seeker analyzes 626,218 matched market signals across Reddit, job ads, podcasts, Google Trends, app-store reviews, and other public product reviews to surface business ideas backed by inspectable evidence. You can inspect how often a problem recurs and whether interest is changing.
In the latest seven-day product-facts window, 90,409 matched demand signals reached at least one idea, an average of about 12,916 per day. This is research evidence, not a count of customers, sales, or guaranteed demand.
- Browse categorized business ideas across major product and service sectors
- Compare Opportunity Score v3 quality, depth, breadth, trends, and competition inputs
- Watch new evidence arrive in the Live Signals feed
- Explore related problems and opportunities in the Demand Map
- Validate your own idea against matched market signals
How It Works
The research pipeline is a continuous loop. Source-specific gates preserve context, deduplication prevents repeated records from inflating demand, and published ideas remain connected to their supporting evidence:
- Discover - Collect activity from communities, jobs, podcasts, reviews, search interest, and launches
- Qualify - Apply source-specific gates and reject weak or ambiguous signals
- Match and cluster - Deduplicate evidence and connect it to shared problems, buyers, and ideas
- Score and publish - Rank traceable opportunities using evidence, trends, and competition
Opportunity Score v3
Opportunity Score v3 is an evidence-first research-prioritization score. Its normalized inputs are 40% signal quality, 15% evidence depth, 10% independent source breadth, 15% search trends, and 20% competition opportunity. Qualifying evidence and trend snapshots use a 60-day half-life.
Confidence is separate and describes coverage. AI-generated market buildability, legacy urgency and specificity, and duplicate mention volume do not contribute points. The score is not a success probability, market-size estimate, or substitute for reading the evidence.
Read the complete Opportunity Score v3 methodologyWho Built This
Trend Seeker is built and maintained by Tonis Tiganik, a software engineer based in Estonia. After years of building products and watching founders struggle to find ideas worth pursuing, the pattern became clear: useful ideas begin with what real people already need.
The stack includes a Rust backend, a server-rendered React frontend, and custom NLP pipelines. New signals are processed continuously, and public product facts refresh about every two hours.
Contact
Questions, feedback, or partnership inquiries? Reach out at [email protected]