Customer segmentation for restaurants and hotels, with examples

Customer segmentation for restaurants and hotels means grouping guests who behave differently enough to deserve different treatment: a different email, a different offer or a note for the team on arrival. The most useful segments come from data you already hold, such as when a guest last visited, how often they come, what they spend, why they come and how far ahead they book.

A segment earns its place when it is big enough to matter, behaves differently from the rest of your guests and comes with a decision attached. If you cannot say what you will do differently for a group, leave it as a report.

How does RFM segmentation work for restaurants?

RFM scores each guest on three measures: recency (how long since their last visit), frequency (how many visits) and monetary value (how much they spend). IBM's SPSS documentation describes a common version: rank guests into five groups on each measure, with 5 for the most recent, most frequent or highest-spending, then combine the three digits into a code from 111 to 555. The same documentation names recency as the most important factor in identifying customers likely to respond to a new offer, followed by frequency and then spend.

You do not need all 125 combinations. A restaurant can work with a handful of groups:

When does a regular become a lapsed regular?

Lapsed depends on the guest. A weekly regular who has missed six weeks has changed their habits, while a guest who comes twice a year has not lapsed after six weeks. Define lapse relative to each guest's usual gap between visits, for example no visit in three times their average interval, or use a fixed window for each frequency band.

Say a guest has visited every three weeks for a year and has not booked in nine weeks. That guest belongs in a win-back segment. A guest whose only visit was nine weeks ago belongs with new guests who did not return, and needs a different message.

What are occasion-based segments?

Occasion segments group guests by why they come. Restaurants see business lunches, date nights, family meals and celebrations. Hotels see midweek corporate stays, leisure weekends and special-occasion breaks. The same guest can sit in more than one.

The data usually comes from the booking: an occasion field in the booking form, the day and time, the party size and whether a company card paid. A guest who books a table for two on a Saturday every few months and notes an anniversary is a better audience for a set-menu evening than for a weekday lunch offer.

Can you segment guests by dietary preferences?

Dietary preference segments are useful for menu launches, because guests who want to hear about a new vegan menu are an obvious audience. The safest way to build that segment is to ask: a preference choice on your signup form or profile lets guests pick the menu news they want.

Treat allergy information differently. A note that a guest has a nut allergy or coeliac disease says something about their physical health, and the ICO's guidance treats data concerning health as special category data under UK GDPR. Using it needs a lawful basis and one of the conditions in Article 9. Preferences such as halal or kosher can also reveal religious belief, another special category. Keep allergy records for service and food safety, and take advice before using any of this to target marketing.

How should hotels segment guests by booking lead time?

Lead time is the number of days between booking and arrival, and it tells you how a guest plans. Guests who book months ahead for summer respond to early offers and have time to add spa treatments or dinner before they arrive. Last-minute bookers respond to short-notice availability, and any pre-arrival messages for them need to fit into a day or two.

Useful bands for a hotel might be 0 to 7 days, 8 to 30 days and over 30 days. Compare average spend per stay across the bands before you build campaigns around them, because a band that books late but spends heavily on arrival needs a different message from one that books early and spends little.

How to build customer segments in Tiquo

Tiquo's segments are dynamic: they include every customer who matches the filters and update as customer data changes. Filters combine with AND and OR logic and cover age range, location, total spend, total orders, last visit date, customer status, membership plan, tags, service history, marketing consent and custom parameters. Last visit date, total orders and total spend give you the raw inputs for RFM-style groups, and the segment builder shows an estimated audience size before you send anything.

Custom parameters add typed fields to customer profiles, such as text, number, date, yes/no or dropdown values, and you can filter on them and build segments from them. A menu-interest or occasion field is one way to capture data your system does not hold by default.

Segments can also be selected in Analytics to focus the charts on one group, so you can see how lapsed regulars or high spenders book and spend before you message them, and a customer's profile shows which segments they belong to.

A guest's place in a segment does not by itself make them eligible for a marketing message. When several lists or segments are selected for one send, Tiquo removes duplicates, and only customers who have opted in to marketing receive it. Our guide to customer lifetime value explains how to weigh segments by value, and the guide to choosing between a CRM and a customer data platform covers joining guest data from several systems first.