Niche Scoring Examples for AI SaaS

Two worked examples. Names and numbers illustrative.

Example 1: Ex-Google ML Engineer

• AI for code completion: R5 F8 S9 D3 B6 C2 = 33
• AI for SOC 2 compliance evidence: R7 F6 S9 D7 B4 C8 = 41
• AI for academic peer review: R5 F4 S5 D6 B5 C9 = 34
• AI for legal contract redlining: R7 F7 S9 D5 B3 C4 = 35
• AI for sales email personalization: R8 F8 S9 D4 B5 C2 = 36

Winner: SOC 2 evidence collection. The crowding score (8 = mostly empty) tipped it. Sales email and code completion both have ten+ players already.

Example 2: Solo AI Developer

• AI for podcast show notes: R8 F6 S7 D4 B7 C3 = 35
• AI for veterinary record summarization: R4 F7 S6 D7 B3 C9 = 36
• AI for SaaS onboarding email sequences: R8 F8 S9 D5 B6 C5 = 41
• AI for grant proposal drafting: R5 F4 S6 D7 B5 C8 = 35
• AI for restaurant menu translation: R6 F5 S5 D5 B4 C7 = 32

Winner: SaaS onboarding emails. Reachable, frequent pain, real existing spend, moderate crowding (so still differentiable).

What These Show

Adding the crowding criterion changes which niche wins.

Without it, the "hot" AI SaaS niches (code completion, sales emails) keep scoring well despite being saturated. With it, the boring underexplored niches surface as actual winners.