AI Funnel Optimization Playbook

Use this monthly operating rhythm to improve lead quality from ERP/CRM + AI website traffic.

North-Star Metrics

• AI tool start rate (ai_tool_start events / unique visitors)
• AI handoff rate (ai_tool_handoff / AI tool starts)
• AI-assisted lead submission rate (ai_assisted_lead_submit / AI handoffs)
• Sales-accepted lead rate for AI-assisted submissions
• Booked meeting rate from AI-assisted submissions

Monthly Optimization Loop

1. Measure
   • Export last 30 days of AI funnel events and lead outcomes.
   • Segment by source, industry, and recommended track.
2. Diagnose
   • Identify top drop-off point (tool start, handoff, form submission, or sales acceptance).
   • Review session recordings or heatmaps for friction on affected step.
3. Experiment
   • Run 2-3 prioritized tests with a clear hypothesis and success threshold.
   • Keep one variable per test (headline, CTA, trust block, or form prompt).
4. Scale
   • Promote winners to default and document impact.
   • Archive losing tests with notes so they are not repeated.

Recommended Experiments

• Headline test: Outcome-first copy vs capability-first copy on solutions hero.
• Trust placement test: Case-study proof block above vs below AI planning tools.
• CTA test: "Send Plan to ATW Team" vs "Get My AI Roadmap Review."
• Form framing test: Default message with AI summary vs blank optional message.
• Track framing test: "Prebuilt accelerators" vs "Rapid implementation track."

Reporting Template

• Traffic: Sessions, unique visitors, source mix
• Funnel: Starts -> handoffs -> submitted leads
• Quality: Sales accepted, meetings booked, opportunity created
• Decision: Keep, iterate, or retire each experiment

Governance Notes

• Keep event naming stable across releases.
• Record major content or UX changes in release notes for attribution.
• Review form quality with sales weekly to calibrate scoring assumptions.