aef stage detector

The problem

Founders often market to visionaries when their actual customers are pragmatists, or fail to see growth stalling as they hit the chasm. Relying on founder intuition instead of market signals leads to mismatched messaging and wasted ad spend.

What it does

• Analyzes customer reviews, landing pages, and channel data to identify the current adoption stage.
• Constructs a transparent evidence table mapping verbatim signals to specific stages from Innovator to Laggard.
• Identifies mismatches between founder positioning and actual buyer behavior.
• Assesses chasm risk by evaluating category maturity against current growth signals.
• Tracks "stage drift" over time when provided with updated data.

Why this beats prompting it yourself

Generic prompts often hallucinate market maturity or rely solely on landing page copy. This skill enforces a "signal-first" methodology that prioritizes observable buyer behavior and forces a differential diagnosis, preventing the bias of optimistic stage calls.

Use cases

• Diagnosing why a high-growth product has suddenly hit a plateau.
• Auditing a landing page to see if the copy matches the expectations of the current buyer segment.
• Determining if a product is ready to shift from community-led growth to organic search and comparison-based marketing.
• Validating market maturity assumptions before a major pivot or product launch.

Known limitations

Requires external data like customer reviews or intake forms to function. Confidence scores are capped at medium for data sets with fewer than 10 reviews.