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Dine-In Restaurant Experience & Satisfaction Survey

Captures how guests rate a specific dine-in visit — food, service, ambiance, and value — plus their likelihood to recommend. Built for restaurant owners and hospitality groups, with an AI follow-up interview that digs into the specific dish, moment, or interaction behind a low or high recommendation score instead of leaving it as a number.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

12 questions · ~7 min
Q01
Message

Thanks for dining with us! We'd love your honest feedback on today's visit — it takes about 3 minutes and helps us get the little things right.

Q02
Multiple ChoiceRequired

In the last 3 months, how often have you dined in at this restaurant?

  • Today was my first time
  • Once
  • 2-3 times
  • 4-6 times
  • More than 6 times
Q03
Opinion ScaleRequired

Overall, how satisfied were you with today's dining experience?

Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q04
MatrixRequired

Please rate today's visit on each of the following.

5 rows × 5 columns
  • Food quality
  • Speed of service
  • Staff friendliness
  • Cleanliness of the dining area
  • Value for the price
Columns: Poor · Fair · Good · Very good · Excellent
Q05
Multiple Choice

Which of the following did you order during this visit? (Select all that apply)

  • Appetizer/starter
  • Entrée/main course
  • Dessert
  • Alcoholic beverage
  • Non-alcoholic beverage
Q06
Opinion ScaleRequired

How likely are you to recommend this restaurant to a friend or colleague?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q07
AI Interview

Probe the reasoning behind the respondent's recommendation likelihood score. If they rated 8 or below, ask specifically what fell short today — food, service pacing, staff attitude, or value — and get a concrete example (a specific dish, moment, or interaction). If they rated 9-10, ask what one thing stood out as the reason they'd recommend it. If their satisfaction rating and recommendation score seem to point in different directions, ask them to reconcile the gap.

Q08
Best–Worst Trade-off (MaxDiff)

Which of these would do the most to improve your experience at this restaurant, and which would matter least?

  • Improving food quality and taste
  • Faster service without feeling rushed
  • More friendly and attentive staff
  • Better value for the price
  • More menu variety and seasonal options
  • Cleaner and more comfortable dining area
  • Shorter wait times for a table
  • More consistent portion sizes
Pick best & worst per setBest:Would improve my experience the mostWorst:Would improve my experience the least
Q09
Long Text

Is there anything else about today's visit you'd like to tell us?

Q10
Multiple Choice

Which age range do you fall into?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65 or older
  • Prefer not to say
Q11
Multiple Choice

How do you describe your gender?

  • Woman
  • Man
  • Non-binary
  • Prefer not to say
Q12
Message

That's everything — thank you for sharing your experience! Your feedback goes directly to our team to help us improve the menu, service, and atmosphere.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Goes beyond a numeric recommendation score with an AI follow-up interview that probes the specific dish, moment, or interaction behind a low or high score
  • Combines structured ratings (satisfaction scale, matrix rating of food/service/ambiance/value, order selection) with open-ended depth via long-text and adaptive questioning
  • Uses a max-diff question to prioritize which improvements would actually move guest experience, not just flag dissatisfaction
  • Frames the survey conversationally with chat-style opening and closing messages, making it feel like a guest conversation rather than a form

QuestionPro

Restaurant survey questions | Restaurant satisfaction survey questions

This page reads more like a question-bank/guide for building restaurant surveys than a single ready-to-field template. It's useful for researchers assembling their own questionnaire but doesn't present one packaged, deployable survey flow. Good reference for question ideas, less so for immediate fielding.

What it does well

  • Broad library of restaurant-specific survey questions to draw from
  • Established survey research platform with logic and reporting tools
  • Useful as a planning/reference resource before building a survey

Where it falls short

  • Not a single fielding-ready template — requires assembly from a question list
  • No adaptive AI interview to follow up on a low or high recommendation score
  • No published methodology for how any AI scoring or analysis is generated

Jotform

Restaurant Customer Satisfaction Survey Form Template

A ready-to-use, drag-and-drop form template well suited for quick deployment and customization. It's a static questionnaire — every respondent sees the same fixed set of fields regardless of their answers. Strong for simple feedback collection, but not designed to dig deeper into individual responses.

What it does well

  • Fast to deploy with an easy drag-and-drop form builder
  • Highly customizable fields and design
  • Simple, ready-to-use template for basic satisfaction capture

Where it falls short

  • Static form with no adaptive follow-up on why a guest rated their visit a certain way
  • No voice AI interview or guided task/screen-share option
  • No automated per-response quality scoring or transparent AI prompt methodology

SurveyMonkey

Customer Satisfaction Survey Template For Restaurants

A polished, ready-to-field template backed by a mature survey platform with solid reporting and benchmarking features. Like most template-based tools, it presents a fixed question set to every respondent rather than adapting in real time. Well suited for tracking trends over time rather than exploring individual guest stories.

What it does well

  • Ready-to-field template from an established survey platform
  • Strong built-in reporting and benchmarking capabilities
  • Easy distribution across multiple channels

Where it falls short

  • No adaptive AI follow-up interview to probe the reasoning behind a score
  • No voice AI interview option for richer, spoken feedback
  • No transparent, publishable prompt methodology behind any automated analysis

Typeform

Restaurant Customer Satisfaction Survey Template

A conversational, one-question-at-a-time template that's pleasant to fill out and well-branded. The conversational feel is presentational rather than intelligent — question flow can branch on prior answers but doesn't generate new, context-specific follow-up questions based on open-ended responses. Good for completion rates, less so for probing depth.

What it does well

  • Engaging, conversational one-question-at-a-time interface
  • Strong visual design and mobile-friendly experience
  • Supports basic conditional logic between questions

Where it falls short

  • No true adaptive AI interview that generates new probing questions based on a respondent's specific answer
  • No voice AI interview or guided screen-share task option
  • No automated quality scoring or transparent AI prompt disclosure

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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