MasterPrompt VaultBY MASTERESTAURANT

AI assistant · N4 Executable plan

◆ Included in the annual plan⭐ Reviews, Reputation and Automated Messagingv1.1.1 · 2026-08-26

Recovery Flow Builder for Unhappy Restaurant Guests

Builds the flow your restaurant uses to win back a guest who left angry: who enters and who does not, the private message sent only once, what gets replaced at recipe cost with its monthly ceiling, and the fix that stays in the kitchen.

N4
Depth
12/23
Your data
3
Compatible AIs
5
Steps to use it
Depth of the resulttap a level to see what you get
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N4Executable plan

A plan with owners, deadlines and the metric you review. Not advice: an agenda someone can execute on Monday.

◆ This assistant 23 of the 164 published assistants are at this level

Is this for you?

What it does and what you get

  • Most restaurants answer the complaint in public and stop there: the guest never returns and nobody notices.
  • This assistant takes the job that starts where the public answer ends —the move to private, with a name and a role— and turns it into a flow with rules that bite: who enters (only the guest who left a contact route), what gets replaced and what does not, with the gesture costed at recipe cost instead of menu price, and a single attempt with its window, because pushing someone who stays quiet stops being service.
  • It ends where a complaint really closes, which is inside: a fix with an owner and a date, and the rule that a theme repeated three times freezes replacements.

What you end up with

Five chained deliverables: each case with its entry verdict, the replacement rule with recipe cost and monthly ceiling, the private message ready to send on every route, the clock of the single attempt, and the 60-day board with the in-house fix.

EXAMPLE This is what you getAn example built with Sazón de Origen, the house's fictional restaurant.Not your data: your result is built with YOUR restaurant's.See the full example →

Sample result

Sazón de OrigenFictional contemporary Colombian restaurant in Medellín, 2 locations, 6 years in business. Every sample result in the library comes from this same case. Fictional restaurant

The owner asked this: "Five guests left angry this month: two two-star reviews, a sancocho sent back, a delivery that arrived cold and a table complaint on Saturday. I answered the two reviews in public and that was that."

Of the five, four have somewhere to write to and one does not. That one is not a gap in the method: it is the rule working.

CaseWhen and whereCheckable factContact routeVerdict
Cold Trucha al ajillo, 2★ on the search profileThursday 1:40 p.m., Laureles locationDocket 4187: 19 minutes between the pass and the table, in the middle of the lunch rushProfile private messageEnters
Sancocho de tres carnes sent backSunday 12:50 p.m., dining roomThe server logged the return on the docket but not the cause; paid by card and left an email for the invoiceEmailEnters
Own-delivery order arrived coldTuesday 8:10 p.m.52 minutes on the road against the 35 the house promisesOrder WhatsAppEnters
2★ on the delivery platform, "the portion is not the one in the photo"Saturday 1:20 p.m.No exit weight recorded; there is nothing to check it againstPlatform chat, which closes at 72 hoursEnters, short window
Table complaint, Saturday 8:30 p.m.Dining room, El Poblado locationThe plate left cold; the server settled it with a complimentary lemonade and nobody took a detailNoneDoes not enter

The fifth one stays out because there is no CRM and no dining-room guest list: from the room you can only recover whoever left a detail, and nobody asked this one for it. The case is not lost, it moves whole into block ⑤ and leaves the flow here.

Two findings the count puts on the table: two of the four that enter broke inside the strong slots of the house —Tuesday-to-Friday lunch and Sunday midday—, which is where most people see it; and the platform one has no checkable fact because nobody weighs the plate at dispatch. Illustrative figures, built from the data you gave.

This is 3 of 5 parts. Behind the wall are the two pieces that actually get executed. The clock of the single attempt, channel by channel: when the message goes out, who signs it with name and job title, how long the window lasts —5 days on the profile and email, 3 on delivery WhatsApp, 72 hours in the platform chat— and what gets written when nobody answers, with the Monday 9:00 a.m. cut where every case falls into one of three boxes and the silent ones are closed for good. And the in-house fix with the 60-day board: theme, times in 30 days, fix, owner, date and the figure that closes it, plus the rule that freezes the cold-plate replacement until twenty dockets in a row leave under six minutes, and the row that forces every replacement to be logged where waste is logged.

See the full example — free account

Works with these AIs

ChatGPT — the best for this assistant The best fit here: it costs the gesture at recipe cost and writes the private message in the same register, without sliding from arithmetic into apology halfway through.

How to use it

Gather the cases from the last 30 days where somebody left angry: a table complaint, a one- or two-star review, a returned plate or a badly dispatched order, each with its date and hour.
Answer in public first the reviews that need it, and only then copy this assistant into your AI, with your business details and the cases pasted one by one.
Tell it, for each case, whether a contact route was left behind and which one: without that detail the guest does not enter the flow and the assistant will send the case to the in-house fix.
Send every private message yourself through the matching channel, signed with a name and a role, and log the send date in the register it hands you.
At 60 days read the board: how many came back, in how many days, and which fix is still open in the kitchen.

Which of your data it uses

12
of 23

This assistant works with 12 of the 23 fields in «My Restaurant», among them Restaurant name, Business type and Active sales channels. It does not ask out of curiosity: these are what make the answer speak about YOUR scale instead of an industry average — the same calculation on a business of another size returns a number you cannot decide with. You fill them once and they apply across the library, so the second assistant you open already starts with them in place. Whatever you leave blank, the assistant asks for one thing at a time instead of inventing it, and says so before answering, so you know what it is working from.

Restaurant nameBusiness typeActive sales channelsActive social channels (with the @ or the link)Strong and slow daypartsBest-selling dishesMenu price rangeApproximate food cost (%)Communication toneTeam sizeAverage check (with currency)Main goal this year

Always up to date

Every assistant carries a visible version and date. When an AI changes how it works, the assistant's version goes up and you see what changed.

Same method, another variant

Inside the app this is a single control: you press it and the assistant reframes itself, including the variants that don't appear here because they don't have their own page yet.

Which moment

More assistants in this category

Included in the always-growing library

Access to every published assistant, adapted to your AI and personalised with your restaurant's data, updates included.

Recovery Flow Builder for Unhappy Restaurant GuestsN4 · Executable plan · Included in the annual plan See the plan

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