Own your guest data, then build loyalty and targeting on top of it
Every order placed through a delivery marketplace builds someone else's customer list. Every direct order builds yours. GetGarnish turns that list into one guest record, a loyalty program that runs automatically off it, and AI-driven targeting that gets sharper as the data grows, without pretending AI should write your website or talk to your guests unsupervised.
Why owning your guest data matters
For most of the last decade, restaurants handed their customer relationships to delivery marketplaces without much thought. The order arrived, the commission was paid, and the guest's details stayed with the app. The cost of that shows up later. When you want to fill a slow Tuesday, you have no one to contact. When a competitor opens nearby, you have no way to remind your regulars you exist. Every promotion has to be paid for twice, once to acquire the guest and again to reach them. A restaurant CRM fixes the second half of that problem. Direct ordering fixes the first. Online ordering
What the CRM holds
One record per guest, containing contact details, full order history, average ticket, order frequency, time since last order, preferred channel, loyalty status, and which location they order from. Not one row per order, and not three separate records because someone ordered on the website, in the app, and at the counter.
Segments worth building
First-time guests
The largest opportunity in most restaurants. The gap between first and second order is where the majority of guests are lost, and it responds well to a single well-timed message.
Regulars
Your most valuable group. Worth protecting with early access, better rewards, and messages that do not read like mass sends.
Lapsed guests
Thirty, sixty, and ninety days without an order, each with a different message and a different offer. This is consistently the highest-return campaign on a restaurant account.
High-value guests
Above-average ticket or above-average frequency. Frequently the source of catering and private event business, and rarely asked.
Daypart and channel segments
Lunch-only guests, weekend delivery guests, and pickup-only guests all behave differently and should not receive the same message.
Loyalty: turning that data into repeat visits
A returning guest costs nothing to acquire, orders more predictably, and tends to have a higher average check because they already trust the menu. Raising the frequency of guests you already have is almost always cheaper than finding new ones. Loyalty is what makes that repeat behavior deliberate instead of accidental, but only if it changes behavior. A program that rewards people for what they were going to do anyway is a discount with extra steps.
Points on spend
Guests earn points per dollar and redeem for rewards. Flexible, easy to explain, and works across a wide check range. Best for restaurants with a broad menu and variable ticket sizes.
Visit-based
Earn per visit rather than per dollar. Simple, and it drives frequency rather than ticket size. Best for cafes, quick service, and anywhere the check is consistent. A coffee shop should almost always use this.
Tiered
Guests unlock better benefits at higher levels. Effective when you have a clear group of high-value regulars worth treating differently, and unnecessary if you do not.
Cashback
A percentage back as credit toward a future order. Very easy to understand and it pulls guests back specifically to spend the balance.
Subscription
A monthly fee for a recurring benefit, for example free delivery or a daily discounted item. Works for high-frequency concepts and generates predictable revenue, but it needs real volume to be worth building.
How the program runs
Enrollment without friction
Guests join when they order online, in the app, or at the counter with a phone number. No cards, no separate signup flow, no app required to start.
Automatic earning
Points accrue from the order itself, whether it came from the website, the app, or the counter through the POS. Nothing depends on staff remembering to ask.
Rewards guests can see
Progress appears where the guest already is: in the app, at checkout, and in order confirmations. Invisible progress is the most common reason programs die.
Pricing the reward without losing margin
The best rewards are high perceived value and low food cost. A free side, a specialty drink, an appetizer, or a dessert reads as generous and costs a fraction of what a percentage discount off the whole check costs. Two rules worth holding to. First, avoid percentage discounts on the full ticket, because they scale your cost with the guest's spend in exactly the wrong direction. Second, keep the first reward close enough to be believable. If a guest cannot picture reaching it, the program has no effect on the next visit. We model the reward against your actual food cost and average ticket before the program goes live, so nobody discovers the math problem three months in.
Where AI actually helps once the data is clean
Campaign targeting
Choosing which guests should receive which message, and when, based on order history. This is where AI quietly does the most useful work in restaurant marketing.
Segment and pattern-finding
Building audience segments from order data, flagging anomalies in campaign performance, and surfacing patterns in guest behavior that would take a person hours to find by hand.
Drafting guest-facing copy
Useful as a starting point for offer copy, review responses, and campaign drafts. It should not be the finished product, a person reads and approves anything before it reaches a guest.
Where it still falls short
Anything requiring judgment about a specific guest, a specific complaint, or a specific service problem. Anything that needs to sound like your restaurant without a person editing it. Anything where being wrong costs a customer, unsupervised pricing changes, unsupervised public responses, serious complaints, food safety issues, unsupervised order modifications. The pattern that works is AI drafting and a person approving. The pattern that fails is AI publishing.
How it all connects to your other marketing
The guest record is the input; loyalty enrollment is one of the ways it grows. Once both are running, email and text campaigns go to segments based on what people actually ordered, a reward already sitting in a lapsed guest's account, a lunch-only guest getting a lunch offer, while your app gives regulars a reason to keep it installed. You can build lookalike audiences for paid campaigns from your best guests and report on repeat rate and guest value properly, none of which works without the record underneath it. Without it, most restaurants are sending the same message to everyone and hoping.
What changes for your restaurant
- One guest record across your website, app, and counter, feeding loyalty, email, and SMS
- Enrollment that happens during ordering instead of a separate signup flow
- Rewards priced against your actual food cost, not guessed at
- Segments built from real order history, first-time, regulars, lapsed, high-value, not guesswork
- A guest list you own and can export, not one held by a delivery marketplace
- Campaign targeting that gets sharper as order history grows
- A clear line between what AI drafts and what a person approves before it reaches a guest
Before you book a call
A restaurant CRM keeps one record per guest, combining contact details with full order history, frequency, and value. Loyalty is one of the ways guests get identified into that record, it gives people a reason to self-identify and come back, while the CRM is where that identity and history actually live, including guests who never joined the loyalty program. The guest list and order history belong to your restaurant and can be exported at any time.
Talk to someone who understands restaurants
Twenty to thirty minutes, with your site and Google profile open in front of us. No obligation, no demo script.