A Practical Guide to Niche Scoring for AI SaaS

The pillar guide for AI SaaS teams running niche scoring.

Standard five criteria plus one AI-specific addition: competitive crowding. Total time: fifteen to twenty minutes.

Step 1: List Five Candidates

Five candidate niches. Include the technically exciting one and at least two you would not pick by gut.

Step 2: Score on Six Criteria (1-10)

• Reachability — specific channel for paying customers
• Pain Frequency — daily/weekly/monthly trigger
• Existing Spend — what they pay today for adjacent solutions
• Differentiation — customer-visible mechanism, not model choice
• Builder-Fit — audience and trust, not capability
• Competitive Crowding — how many AI startups already shipped this idea

Step 3: Sanity Check Top Two

For the top two candidates, write one paragraph each:

• Why this would work
• Why it would not

If the "why not" paragraph is more concrete, the score is wrong somewhere. Re-score.

Step 4: Pick and Move

Highest score wins. Schedule problem interviews against it within a week.

Score is permission to continue. Interviews are validation.

AI-Specific Failure Modes

• Inflated builder-fit (capability vs audience)
• Inflated differentiation (model choice vs customer-visible mechanism)
• Skipped crowding research (the niche is already crowded)
• Endless scoring while waiting for "the model landscape to stabilize"

The Trade

Twenty minutes catches niches where capability does not match market shape.

The alternative is six months of misaimed engineering against a niche that scoring would have flagged.