AI-powered diagnostic
AI-powered diagnostic that pre-coaches and pre-qualifies
A 67-question intake that produces a 10-15 page, voice-consistent PDF report — so prospects show up to discovery calls already self-diagnosed, in Ellen's exact coaching language. Generated $15k+ within 3 months of launch.
Mock metrics
- $15K+
- generated in 3 months (direct + upsell)
- 56
- completions since Jan 2026 launch
- 4+
- converted to high-ticket coaching
The challenge
Ellen was spending discovery calls assessing readiness instead of coaching. Prospects arrived without language for what they were going through, so every call began at zero.
She needed a front-end asset that qualified, segmented, and demonstrated the depth of her work before the first conversation — without diluting the brand into a generic quiz.
The build
67-question Fillout form across 6 scored life domains feeds an n8n workflow. Cleaned data is routed through a Supabase RAG of Ellen's actual frameworks, then Claude (via OpenRouter, with a GPT fallback) generates a personalized 23-section report. A Google Docs template populates and exports to PDF, which is dispatched by Gmail and logged to a tracker sheet.
Session-keyed memory prevents response leakage between simultaneous submissions. A separate error-analysis workflow uses AI to auto-diagnose failed runs. The prompt layer enforces Ellen's exact tone — punchy, non-therapeutic, direct — so the report sounds like her, not a wellness chatbot.
The outcome
Within 3 months of launch, the $139 assessment had 56 completions, generated direct revenue, and converted at least 4 takers into high-ticket coaching engagements — over $15k generated in total from a tool that runs itself.
Prospects arrive at calls already self-aware and fluent in Ellen's framework language. The report itself functions as coaching: it names patterns before the sales conversation starts, so the call begins at trust instead of triage.
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