Facility AI

The software watches
so you don't have to.

Daily operator digest. Retention alerts before members churn. Revenue anomaly detection that tells you exactly which slot stopped working. One coffee. Three signals. Done.

1 email

Daily at 7 AM

21d

At-risk inactivity gate

−20% · 2wk

Anomaly threshold

Three signals

Narrow alerts that tell you what to do — not 'this dashboard is down.'

Every alert in CourtIQ has one specific trigger, one specific recipient, and one specific action. We'd rather send three useful emails than thirty forgettable ones.

Daily operator digest

Every morning at 7 AM, owners and admins get one email with what needs attention today — yesterday's revenue trend, waitlist overflow, new at-risk members, top/bottom time blocks, schedule anomalies, pending pricing recommendations, and a one-line summary.

Retention risk alerts

Members who were booking 2+ times in the prior 60 days but have gone silent 21+ days get flagged. The highest-LTV lapses surface first so you can reach out with a waived fee or a comp visit before they churn.

Revenue anomaly detection

When any day-of-week × hour slot drops ≥20% vs its 4-week baseline for two consecutive weeks, we notify you. No noise — one dedicated rule, one clear signal, one click to investigate.

Operator digest

One email. Seven signals. Every morning.

Before you finish your coffee, you know exactly what changed overnight — what's trending up, what's trending down, who's at risk, and where to spend the next hour of your day.

  • Sent at 7 AM ET to every owner and admin on your team.
  • Also renders as a "Today's digest" card at the top of the dashboard — so if you miss the email, the signal is still one click away.
  • Idempotent. If your cron fires twice, you still only get one email per operator per day.

Sections in every digest

01

Revenue Δ

Yesterday vs trailing 4-week same-weekday average.

02

Waitlist overflow

Active waitlist count across all courts.

03

New at-risk members

Count of members newly flagged by the retention scan.

04

Top 3 revenue blocks

Best-performing hour-of-week cells from the last 30 days.

05

Bottom 3 revenue blocks

Worst-performing hour-of-week cells — targets for schedule-mix changes or discounts.

06

Schedule anomalies

Peak slots (Fri / Sat evening) that generated zero revenue in the last 30 days, plus waitlist alerts.

07

Pending pricing recommendations

Count of dynamic-pricing recommendations still waiting for your Accept or Dismiss.

Retention risk

We watch for members who were booking regularly and have gone quiet. Not first-timers who didn't rebook — people who built a habit and stopped.

Baseline window
Days 21–81 ago (60 days)
Cadence gate
≥2 bookings in baseline
Inactivity gate
≥21 days since last booking
Lookback cap
90 days
Label
cadence_drop < 45d, lapsed ≥ 45d

Sorted by LTV descending so the biggest lapses surface first.

Revenue anomaly

One narrow rule — we alert when a specific hour-of-week slot has dropped ≥20% vs its 4-week baseline for two weeks running. Not generic "revenue is down."

Scope
Per day-of-week × hour
Threshold
−20% vs 4-week baseline
Confirmation
2 consecutive weeks
Minimum data
6 weeks of history
Alert dedupe
7-day window per slot

Also surfaces the next morning in the operator digest.

Email

Default channel. Resend. Always on unless you turn it off per-type.

In-app

Every notification lands in the dashboard bell alongside the email.

SMS + push

Opt-in per user. Twilio for SMS, Expo for mobile push — same dispatch path as booking confirmations.

No-show follow-up

Hourly cron emails members who missed a booking 2–24 hours ago. Once per booking, never again.

Questions

Honest answers about the 'AI' part.

It's rules. Deterministic, auditable, explainable in a sentence. We don't use an LLM to write your digest or pick which members are at-risk. The math is visible and the thresholds are tuned specifically for pickleball and tennis facility patterns — not generic SaaS behavior.

Facility teardown

See what signals your facility is missing.

Give us 30 minutes and we'll show you your at-risk members, your slot-level revenue trends, and the anomalies your current tools aren't surfacing — whether or not you ever become a customer.