Medium Dashboards system

No-Show Review View

A focused review view dedicated to no-shows and last-minute cancellations — who didn't show, the source/owner/time-slot patterns behind no-shows, reminder-sent vs no-show correlation, and a recovery worklist of no-shows to re-engage — so no-shows become a managed, reducible problem rather than a write-off. It deep-dives the no-show slice of the booking data. A specialized analysis + worklist, distinct from the broader booking status report.

Start a Project All Systems

4 to 7 days: timeline
Medium: complexity
4: tools
4: steps

Built with real HMX dashboard tool paths

Supabase PostgresCal.com webhooksSQL (cross-tab / breakdown)Next.js 16 server componentsSupabase PostgresCal.com webhooksSQL (cross-tab / breakdown)Next.js 16 server components

01 // System facts

System facts

No-Show Review View uses a reporting model and review layer for Dashboards. A focused review view dedicated to no-shows and last-minute cancellations — who didn't show, the source/owner/time-slot patterns behind no-shows, r... The architecture connects a no-show precisely using, supabase postgres, cal, and owner review with an explicit control path.

Outcome

No-shows turn into an analyzable, recoverable list — owners see which slots/sources/reminders drive no-shows and get a ready worklist to win back missed sessions, framed as fewer permanent losses from no-shows.

Main risk

Misclassifying advance cancellations or rescheduled-and-attended bookings as no-shows inflates the rate and pollutes the recovery list.

Prevention

Separate cancelled/rescheduled from genuine no-show using the event timeline, reconcile against the booking status report's totals, and confirm a sample by hand before trusting patterns.

Fallback

If the event timeline can't reliably distinguish no-show from cancellation, report only confirmed no-shows and label the rest 'unconfirmed', keeping the recovery list conservative.

System architecture

No-Show Review View Architecture

6 nodes

a no-show precisely using

SQL for no-show rate broken

Supabase Postgres

Cal

Review Queue

Owner Review

01a no-show precisely using
A focused review view dedicated to no-shows and last-minute cancellations — who didn't show, the source/owner/time-slot patterns behind no-shows, r...
02SQL for no-show rate broken
Write SQL for no-show rate broken down by source, owner, day-of-week, and time-of-day, plus a reminder-sent vs showed cross-tab to test reminder impact.
03Supabase Postgres
Supabase Postgres contributes the trusted model for No-Show Review View so metrics are defined before they are visualized.
04Cal
Build a review view (server component) with the no-show breakdown charts and a recovery worklist of recent no-shows (with contact context) ready for re-engagement.
05Review Queue
If the event timeline can't reliably distinguish no-show from cancellation, report only confirmed no-shows and label the rest 'unconfirmed', keepin...
06Owner Review
No-shows turn into an analyzable, recoverable list — owners see which slots/sources/reminders drive no-shows and get a ready worklist to win back m...

How it is built

Build steps

01Define a no-show precisely (booked slot passed with no completion event, distinct from cancelled-in-advance) using Cal.com events plus CRM booking_status, and agree the recovery window.
02Write SQL for no-show rate broken down by source, owner, day-of-week, and time-of-day, plus a reminder-sent vs showed cross-tab to test reminder impact.
03Build a review view (server component) with the no-show breakdown charts and a recovery worklist of recent no-shows (with contact context) ready for re-engagement.
04Add a pattern flag (e.g. a slot/owner with markedly higher no-show rate) so systemic causes surface instead of being treated as one-offs.

Tools

Workflow surface

Supabase Postgres
Cal.com webhooks
SQL (cross-tab / breakdown)
Next.js 16 server components

Inputs layer: Define a no-show precisely (booked slot passed with no completion event, distinct from cancelled-in-advance) using Cal.com events plus CRM booking_status, and agree the recovery window.
Transform layer: Write SQL for no-show rate broken down by source, owner, day-of-week, and time-of-day, plus a reminder-sent vs showed cross-tab to test reminder impact.
Metrics layer: Supabase Postgres contributes the trusted model for No-Show Review View so metrics are defined before they are visualized.
Visualization layer: Cal.com webhooks handles refresh, review, or reporting delivery while separate cancelled/rescheduled from genuine no-show using the event timeline, reconcile against the booking status report's totals, and confirm a s...
Action layer: No-shows turn into an analyzable, recoverable list — owners see which slots/sources/reminders drive no-shows and get a ready worklist to win back m...

Data flow

01Define a no-show precisely (booked slot passed with no completion event, distinct from cancelled-in-advance) using Cal.com events plus CRM booking_status, and agree the recovery window.
02Write SQL for no-show rate broken down by source, owner, day-of-week, and time-of-day, plus a reminder-sent vs showed cross-tab to test reminder impact.
03Build a review view (server component) with the no-show breakdown charts and a recovery worklist of recent no-shows (with contact context) ready for re-engagement.
04Add a pattern flag (e.g. a slot/owner with markedly higher no-show rate) so systemic causes surface instead of being treated as one-offs.

Controls and fallbacks

Misclassifying advance cancellations or rescheduled-and-attended bookings as no-shows inflates the rate and pollutes the recovery list.
Separate cancelled/rescheduled from genuine no-show using the event timeline, reconcile against the booking status report's totals, and confirm a s...
If the event timeline can't reliably distinguish no-show from cancellation, report only confirmed no-shows and label the rest 'unconfirmed', keepin...

Research basis