Catering: your regular customers may not be who you think they are
16 December 2025
There's the first-time customer, the one you see every Monday at precisely 11:45 a.m., or the one who swears by your pastrami sandwich.
And then there are all the others. The ones you never see, the ones who order on the sly with Click & Collect, the ones who drop by on a whim, the ones who never set foot in the store but have their order delivered every Thursday evening, the ones who spend a lot but only occasionally.
They're part of your business, but you don't really know them.
In an economic context where loyalty becomes a pivotal point for stabilizing your business, the customer data completely redefines the notion of regular customer. It shows you who's really coming back, who weighs most heavily in your results, who's dropping out and who deserves your attention.
You no longer trust familiar faces but you can rely on measurable purchasing behaviors: frequency, basket, rhythm, preferences, buying path.
If you want to know who your "real" regulars are, why some count for more than you think, and how you can use this data to boost your performance, you've come to the right place.
The myth of the regular customer: 3 biases that distort managers' perceptions
01. Visibility bias
You naturally tend to notice customers who eat there, whom you see, whom you know a little, with whom you exchange a few words. They make a lasting impression and become "your regulars". But what about those who order online? Click & Collectin delivery or in gust of wind between noon and two ?
Visibility bias therefore leads you to underestimate customers because they are not physically "visible", even though they generate sales.
It gives a distorted image of fidelity. You think your loyal customer is the one you saw 4-5 times during the month, not the one who ordered 12 times from a distance. This error then distorts strategic decisions: offers, loyalty, targeting.
02. Ticket bias
When a customer leaves a big ticket (a large bill or an addition of options), we tend to consider it important, regular or even precious. But a big one-off ticket doesn't make a good regular customer.
If you decide that a customer is "ideal" on the basis of the cost of a meal, you run the risk of overvaluing certain customers. Those who order little but often, or even on a small budget, can represent a stable value, sometimes more profitable in the long term.
The notion of loyalty based solely on the ticket encourages the "occasional big spender" and not necessarily the long-term regular customer.
03. Regularity bias
It's easy to confuse "apparent frequency" with "real regularity". A customer who comes 3 times in one month (vacations, promotional period) and then disappears is not comparable to a customer who comes regularly, over a year, even if they're both regulars at a given moment.
Another case: a customer who changes channel. You see less of him in theaters, but he continues to order online. You think you've lost it, but it's still active.
This bias leads to misidentifying your true regulars and overvaluing "old customers" simply because we've seen them often, without questioning the real quality of this loyalty.
Customer data: key metrics for identifying your high-impact customers
Now that we've pinpointed the biases that distort your perception, how to identify your "real" customers at a glance? You need to be able to open your backoffice, look at a few indicators and immediately understand who's coming back, who's earning and who's dropping out.
And if, on top of that, automation allows you to do this segmentation effortlessly, that's even better: you get a clear view of your database without wasting time on pivot tables.
Purchase frequency: identify the frequency of visits that generates the most value
Purchase frequency gives you an initial reading of your customers' actual behavior. See how many times they come back over 30, 60 or 90 days.
This data helps you to understand the rhythm of your customers' lives: lunchtime customers, weekend customers, evening customers. You can then adapt your offers or campaigns according to these cycles.
Average basket by segment: identify the customers who spend the most and what influences their choices
The average basket is a basic piece of information for a restaurateur, but becomes truly relevant when analyzed by segment.
This approach helps you focus your suggestions at terminal or in QR Codeadjust your offers and adapt the benefits of the loyalty program. A segment may have a low basket but interesting potential if you encourage them to try extras or higher-margin products.
Long-term customer value: measuring contribution over several months
Long-term value gives you a more solid vision than frequency, by combining frequency, basket and retention to see what a customer really brings in over several months.
A customer who comes less often can remain very interesting if his basket remains stable and if he comes back over time.
You're probably familiar with Pareto's law: around 20% of customers generate around 80% of sales. Long-term value helps you to identify this strategic minority, the one that really weighs on your results, instead of relying solely on those you see most in the hall.
Delayed visits: the signal that signals a loss of recurrence
Churn is one of the easiest signals to read. You compare the customer's usual pace with the time since their last visit. If the gap widens, he starts to stall.
This benchmark gives you the right timing to intervene. You can send a relaunch campaign with a special offer, highlight a new product or simply remind people how your business works. loyalty program. A reminder is often enough to bring the customer back before he disappears from your radar forever.
Purchase history: identify habits that influence sales
By tracking purchase history, you can quickly identify the habits of each customer: the dishes he chooses several times, the options he often adds, the times he orders and the frequent associations.
This information helps you to offer consistent suggestions on your digital tools, adjust your menu and direct your additional sales towards what has already proved its worth. You understand what triggers an order, and what can boost the basket without a hard sell.
The 4 regular customer profiles you need to identify in your database
01. The local regular
This is often the neighborhood customer: low basket size but high frequency. He knows your map by heart, he comes back quickly and he's part of your daily flow (bonus: he loves showing his buddies around his favorite spot).
To increase its value, don't try to disrupt its experience. You can highlight extras, offer a more complete menu or use loyalty points to encourage customers to try another dish. This customer doesn't like change, but responds well to small impulses that boost your average basket.
02. Regular premium occasional
A high basket but an irregular rhythm. He comes whenever he feels like indulging, often in the evening or at weekends.
Its potential is in the recall. A targeted campaign, a novelty in line with their preferences, or a high-end product can be enough to bring them back.
You don't need to talk to him often, but you should not forget to contact him when relevant.
03. The regular multi-channel
He orders takeaway, Click & Collect, on-site and on delivery. It's the most profitable customer, because it flows naturally between your channels and adapts to your organization. You can find it in your database with a rich history: several purchasing modes, several consumption moments, several baskets.
To activate it, you can work in 3 stages:
➜ reinforcing the habit: your loyalty program needs to recognize its versatility. You can value multi-channel visits or reward regular cycles. This type of customer responds well to simple, visible and immediately usable benefits.
➜ customize your routes : visit automatic suggestions on terminal or QR Code work very well on him, because you already have a precise history. You can highlight his recurring dishes, something new that's close to his habits, or an extra that he often adds.
➜ work on recurrence : you can plan ahead a few targeted campaigns a yearbased on its consumption moments.
This profile is solid. It doesn't take much to encourage them to stay active, and every action taken on them has a direct impact on your sales, because they respond quickly and across multiple channels.
04. Regular at the end of the line
He's ordering less often and/or his average shopping basket is shrinking - watch out, you're losing him. This customer doesn't pick up the phone overnight. This makes it difficult to spot if you don't follow its data.
You can act early, within 30 or 45 days without a visit. A targeted campaign is often enough: a message linked to their favorite dish, highlighting a new feature in line with their habits, or reminding them of offers from your loyalty program. The idea is not to push him, but to give him an obvious reason to come back.
If you intervene before it disappears, you avoid losing a profile you've already acquired, and you stabilize recurrence. A little preventive action goes a long way towards protecting your sales than a late win-back campaign.
Boost your business performance with your data
Would you like to activate your establishment's full data potential? Contact our team today.
To find out more, explore our resources dedicated to loyalty and digital journeys in the foodservice industry:
➜ Customer loyalty: 3 effective strategies for your restaurant
➜ Creating a post-purchase bond: the keys to customer loyalty in the foodservice industry
➜ Segmenting your database: the cornerstone of customer loyalty
