Updated in real-time

Founder Signal Engine

What founders want to build, where they hesitate, and what predicts action — from 300K+ interactions.

Industry Intent

Founder Intention Index

Which industries founders WANT to enter

Platforms dominate founder interest at 2× the rate of AI/Tech

Platforms131
AI/Tech72
E-commerce69
Consulting59
HealthTech55
SaaS52
Customer Clarity

Customer Clarity Score

How specific founders describe their target

Only 13% of founders have a clear customer definition

Semi-clear823
Vague533
Clear211
Semi-clearVagueClear
Score Bands

Score Distribution

Last 30 days — distinct users by score

Most ideas score 70-80 — execution matters more than perfection

0-50
50-70
70-80
80-90
Behavior Types

Founder Behavior Distribution

Classified by sessions, idea changes, and execution

78% of founders are Explorers — only 8% are Builders

Explorer
Sprinter
Refiner
Analyzer
Builder
Conversion

Conversion by Category

% who take action within each category

Brick & Mortar has the highest execution rate at 38.7%

Brick & Mortar38.7%
E-commerce36%
AI/Tech35.8%
Consulting34.6%
Platforms33%
SaaS28.1%
Red Flags

"Should You Be Building This?" Signals

Early misalignment indicators

67% of ideas have unclear distribution — the #1 killer

Distribution unclear670
Customer unclear527
Weak monetization507
Market too broad155
Solution-first / AI-for-X113
Quality Signals

Strong vs. Weak Idea Inputs

What makes an idea compelling (or not)

Strong ideas have constraints; weak ideas have technology

Strong Inputs

  • Specific customer
  • Clear daily pain
  • Lived experience
  • Narrow market
  • Revenue problem

Weak Inputs

  • "Everyone"
  • Vague aspiration
  • No domain edge
  • Abstract market
  • "AI for X"

Strong ideas start with constraints and proximity. Weak ideas start with technology and imagination.

Post-Mortem

Why High-Quality Ideas Don't Move Forward

Distribution of blocking factors (cohort: high score, no execution)

98% fail due to weak founder-problem fit — not idea quality

Weak founder–problem proximity97.9%
Customer too broad or abstract97.4%
No iteration after advice71.3%
Unclear first step after validation64.2%
Scope too large or unclear MVP20.2%
Low confidence signals in language6.6%
Aspirational problem framing2.4%