Inbox to Bookings: Turn Emails & DMs into Same-Day Appointments

Goal: Convert inbound messages (email, web forms, DMs) into booked calls fast—without adding headcount.

What this solves

• Slow replies = lost leads
• Back-and-forth scheduling
• Inconsistent tone and info
• No record of what was promised

The simple flow

1. Capture: Pull new inquiries from one inbox (or label) and DMs.
2. Draft: AI prepares a reply that answers the question and proposes times.
3. Approve: A human skim-checks the draft (during the pilot).
4. Book: Link to a live calendar (or offer 2–3 slots).
5. Log: Write the outcome to a sheet/CRM for follow-up.

The instruction set (copy/paste)

Mission: Convert qualified inquiries into booked intro calls within 1 business day.
Always include: greeting by name, 1-sentence value prop, 2–3 time options or calendar link, next step, sign-off.
Never: promise timelines/pricing; guess missing facts.
Escalate when: legal, custom pricing, complaints, or unclear scope.

Email/DM reply template

Subject: Quick next step for {{Company}}
Body:
Hi {{Name}},
Thanks for reaching out about {{topic}}. We can help with {{short value prop}}.
Next step: a quick {{15/30}}-minute intro call to confirm fit and timeline.
Pick a time: {{calendar link}}
—or— reply with what works from: {{Tue 10:00–11:30 CT, Wed 2:00–4:00 CT, Thu 9:30–11:00 CT}}.
If you have docs/screenshots, attach them—saves us both time.
Best,
{{Rep Name}} • {{Title}} • {{Contact}}

What the AI actually does

• Detects intent (“pricing?”, “availability?”, “feature?”)
• Pulls approved answers from your FAQ/docs
• Inserts your voice and disclaimers
• Offers real calendar times or your booking link
• Fills a Run Log row (see below)

Minimal data kit (you already have this)

• FAQ / value prop (1–2 pages)
• Scheduling (Calendly/Outlook/Google) with clear availability
• Reply template (above)
• Run Log sheet with columns:
  date | name | email | source(inbox/DM) | intent | reply_sent(yes/no) | booked(yes/no) | time_to_first_reply(sec) | notes

Guardrails leaders like

• Human-in-the-loop on customer-facing replies during the pilot
• Least-privilege access (read inbox, create drafts; no auto-send at first)
• One-click pause/rollback if quality dips
• Change log for any prompt/policy updates

Metrics that matter (weekly snapshot)

• First-reply time (seconds)
• Booking rate (# bookings / # qualified inquiries)
• Edit rate (% drafts needing changes)
• Exception rate (missing info, escalations)

Example: If inbound volume is 120/month and the agent cuts first-reply from 6 hours to 6 minutes and boosts booking rate from 22% → 34%, you’ll see ~14 more intro calls/month—without more staff.

Setup options (pick your stack)

• Microsoft: Copilot Studio + Outlook + Bookings + SharePoint (FAQ)
• Google: Gmail + Calendar + Sheets + Gemini for drafting
• ChatGPT: Custom GPT with “Knowledge” (FAQ) + calendar link; export Run Log to Sheets/Zapier
• API route: OpenAI API + Zapier/Make for teams needing stricter schemas

Rollout in 10 business days

Days 1–2: Baseline (time to reply, current booking rate) + finalize template and FAQ
Days 3–4: Configure AI + connect calendar + set guardrails
Day 5: Dry-run on yesterday’s inquiries (no sending)
Days 6–8: Live drafts with human approval; log outcomes
Day 9: Score results, patch issues (data, template, instructions)
Day 10: Decide: scale, tweak, or pause

Common pitfalls (and fixes)

• Messy inbox: Use a single “Leads” label/folder → cleaner trigger.
• No availability: Keep 6–8 bookable slots/week visible.
• Vague inquiries: Teach the AI one clarifying question before proposing times.
• Off-brand tone: Lock a style/policy card and audit 10 drafts/week.

Bottom line: Faster replies + fewer back-and-forths = more booked calls. Start small, measure weekly, then scale.

CTA: Want this running in two weeks with clean guardrails? Contact BoostMyAI to get started.