Alma Eriksson

Inbound-meeting router

Calendly bookings classified by intent via GPT-4, routed to the right AE in Slack, full context attached.

No-show rate down 22%; first-call quality up.
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Problem

Inbound Calendly bookings landed on whoever was on duty — half the time the wrong AE, no context, awkward first 10 minutes. Prospects dropped off.

Flow

Calendly webhook → GPT-4 classification → round-robin within target pod → HubSpot update → Slack DM 15 min before call.

Cadence

Per inbound booking, ~12/day

What I built

  • Calendly webhook trigger on each new booking
  • GPT-4 classifies intent from the booking notes + lead source
  • Round-robin within the right AE pod (mid-market vs SMB vs enterprise)
  • Slack DM to assigned AE with full lead context 15 min before call

Limits

  • English-only intent classification — non-EN bookings go to default rep
  • Doesn't reschedule — only routes; reschedule is on Calendly itself
Inbound-meeting router

AI tools used

  • OpenAI API
  • Zapier
  • Slack