AI rebook prediction
Written by Peko Research Team.Last updated: 05/18/2026.
A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality. Prioritises which lapsing guests deserve a personal call vs an automated nudge.
Published: 05/18/2026
Updated May 2026 — A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality. Prioritises which lapsing guests deserve a personal call vs an automated nudge. A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality.
This is part of our full guide to why customers stop coming back. Also worth reading: How accurate AI rebook predictions are and The 3-day churn-prediction window.
Quick facts
- Definition
- A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality. Prioritises which lapsing guests deserve a personal call vs an automated nudge.
- Why it matters
- A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality. Prioritises which lapsing guests deserve a personal call vs an automated nudge.
- Related terms
- Lapsed guest flag
A model that scores each guest's probability of returning in the next N days based on visit cadence, service mix, ticket trend, and seasonality. Prioritises which lapsing guests deserve a personal call vs an automated nudge.
In the Vietnamese market, this concept interacts tightly with Zalo OA reach, VND cash/QR payment mix, and the district-cluster dynamics of competing venues. Applied properly it can move 5–15 points of 90-day cohort retention.
PEKO operationalises this concept as part of the loyalty layer that runs alongside the venue's existing booking system (Booksy, Fresha, Mindbody, KiotViet, or paper) rather than replacing it.
Numbers on this page: named sources are listed below; figures without a named source are PEKO merchant data, Vietnam, Jan 2024 – Jun 2026, or PEKO estimates where modelled. See the datasets behind these numbers.
FAQ
Which Vietnamese verticals does ai rebook prediction apply to?
Best fit for barbershops, nail bars, hair salons, spas and beauty salons — verticals where rebook discipline and the guest-stylist relationship drive most of the revenue.
How long does implementation take?
With PEKO, a small venue typically goes live in 3–5 days: contact import, Zalo OA connect, basic reminder cascade switched on, then tuning over the first 2–3 weeks.
Do I need to replace my current booking system?
No. PEKO is positioned as a loyalty layer on top of existing booking systems — Booksy, Fresha, Mindbody, KiotViet or paper diaries all stay; PEKO adds retention on top.
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Term
Operator dashboard
A single screen for venue owners showing today's bookings, no-show risk per slot, lapsed-guest counts, and outstanding win-back queues. Replaces 4–6 spreadsheets and a manual phone-tree.
Term
Win-back window
The interval after a guest's dormancy threshold during which a win-back offer still recovers a meaningful share of guests. Closes at roughly 2× the rebook window — beyond that, win-back economics collapse.
Answer
Your best customers leave silently — how do you notice?
Silent churn is the default, not the exception. The only reliable detector is a per-customer visit rhythm, because a departure looks exactly like a quiet fortnight until it is permanent.