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Everyday Food Preference & Decision Drivers Survey

Maps what people actually eat, which cuisines and attributes they favor, and what really drives a food choice in the moment — price, health, convenience, or taste. Built for food brands, restaurants, and meal-kit teams shaping menus or products. An AI follow-up interview reconstructs the last real meal decision instead of relying on stated preferences alone.

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질문 13개 · 약 7분
Q01
메시지

Hi! We'd love to understand your everyday food choices — what you like, what you avoid, and what actually tips the scale when deciding what to eat. Your responses are completely confidential and anonymized. This takes about 6 minutes and there are no wrong answers.

Q02
객관식필수

Which of these best describes how you eat most of the time?

  • Eat everything (omnivore)
  • Vegetarian
  • Vegan
  • Pescatarian
  • Flexitarian (mostly plant-based)
  • Low-carb / keto
  • Other
Q03
객관식필수

Which cuisines do you genuinely enjoy eating — not just tolerate? Select all that apply.

  • Italian
  • Mexican
  • Chinese
  • Indian
  • Japanese
  • Middle Eastern
  • American / comfort food
  • Thai / Southeast Asian
  • Mediterranean
  • French
Q04
객관식필수

In the last 30 days, how often did you try a dish or cuisine that was new to you?

  • Never
  • Once
  • A few times
  • Weekly or more
Q05
매트릭스필수

When you're deciding what to eat, how important is each of the following?

6개 행 × 5개 열
  • Taste and flavor
  • Health / nutrition
  • Price
  • Convenience / prep time
  • Sustainability or ethical sourcing
  • 외 1개
열: Not at all important · Slightly important · Moderately important · Very important · Extremely important
Q06
최선·최악 선택형(MaxDiff)필수

Thinking about picking a meal on a typical day, which of these matters most, and which matters least?

  • Great taste
  • Low price
  • Health benefits
  • Fast / minimal effort
  • Familiar and comforting
  • Large portion size
  • Locally sourced or sustainable
  • Visually appealing
세트별 최선·최악 선택최선:Matters most최악:Matters least
Q07
점수 배분필수

You have 100 points to distribute across the factors below based on how much weight each one gets in your typical food decisions. Split them however feels honest — they don't need to be equal.

  • Price
  • Taste
  • Health / nutrition
  • Convenience
  • Brand or reputation
  • Packaging or presentation
100점 배분
Q08
의견 척도필수

How willing are you to try an unfamiliar dish or ingredient you've never had before?

척도: 1 – 7
최소:Very hesitant, I stick to what I know최대:Very willing, I actively seek novelty
Q09
평점 척도

How satisfied are you with the food options currently available to you day-to-day (grocery, delivery, restaurants nearby)?

범위: 1 – 5
최소:Very dissatisfied최대:Very satisfied
Q10
AI 인터뷰

Ask the respondent to walk you through the last meal or snack they chose for themselves, step by step: what options they considered, what ultimately tipped the decision (price, mood, health, convenience, habit), and whether they were happy with the choice afterward. If their stated top priority from the point-allocation question doesn't match what actually drove that real decision, gently probe the gap. If they say they 'just grabbed whatever,' dig into what 'whatever' usually is and why that's the default.

Q11
객관식

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
Q12
객관식

How many people, including yourself, do you typically cook or shop for?

  • Just myself
  • 2 people
  • 3-4 people
  • 5 or more people
  • Prefer not to say
Q13
메시지

Thank you for sharing your food preferences! Your answers will feed directly into how we shape menus and products to match what people actually want to eat, not just what they say they should eat.

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Goes beyond stated preferences with an AI follow-up interview that reconstructs the respondent's actual last meal decision, surfacing real behavior instead of self-reported ideals
  • Combines a matrix, constant-sum, and max-diff exercise so we can triangulate what really drives choice — price, health, convenience, or taste — rather than relying on a single ranking question
  • Every AI-driven follow-up runs on transparent, reviewable prompts and produces automated per-response quality scoring plus an auto-generated report, unlike static form builders
  • Includes context questions (household cooking size, novelty-seeking, cuisine breadth) so food brands and meal-kit teams can segment findings by real usage patterns, not just demographics

Jotform

Picnic Food Preference Form Template

A fielding-ready static form built for a specific event use case (picnic planning) rather than general everyday food-decision research. It's easy to deploy and customize visually but is scoped narrowly and not designed to probe the reasoning behind choices. Useful as a lightweight intake form, not a decision-driver study.

잘하는 점

  • Ready-to-use, easily customizable form builder
  • Simple, low-friction respondent experience for casual event planning

아쉬운 점

  • No adaptive follow-up questioning — collects only fixed, self-reported answers
  • No mechanism to weigh or trade off decision drivers like price, health, or convenience
  • No automated scoring or synthesized reporting of responses

SurveySparrow

Sample Food Preference Questionnaire Template | Uncover Dietary Trends

A fielding-ready conversational-style survey template aimed at general dietary trend discovery. It covers preference and habit questions in a friendly chat-like format but is still a fixed-question instrument. Good for broad trend snapshots rather than reconstructing specific real decisions.

잘하는 점

  • Conversational, chat-style question flow that feels approachable
  • Positioned specifically around food/dietary trend topics

아쉬운 점

  • No adaptive AI interviewing — all questions are pre-set with no follow-up probing
  • No structured trade-off tools (e.g., points allocation or max-diff) to quantify what matters most
  • No transparent prompt methodology or automated report generation

QuestionPro

Food survey questions | Food-related survey questions & template

A category page/template collection of food and fast-food restaurant survey questions rather than a single polished, ready-to-field instrument. Useful as a question bank for restaurant-style feedback, but it reads more like a reference library than a cohesive decision-driver survey. Good for teams wanting to build their own from parts.

잘하는 점

  • Broad library of food and restaurant-specific question examples
  • Backed by an established survey platform with reporting and distribution tools

아쉬운 점

  • Presented as a question bank/category page, not a single cohesive fielding-ready template
  • No adaptive AI follow-up to reconstruct an actual recent meal decision
  • No built-in trade-off measurement (constant-sum/max-diff) for ranking decision drivers

Typeform

Consumer Preference Survey Template

A general-purpose consumer preference template that could be adapted for food brands, but it is not food-specific and covers preference topics broadly rather than everyday meal decisions. Its polished conversational UI is a strength, though the content isn't purpose-built for food, cuisine, or meal-choice research.

잘하는 점

  • Clean, on-brand conversational interface known for high completion rates
  • Flexible template that can be adapted across product categories

아쉬운 점

  • Not food-specific — no built-in cuisine, meal-timing, or food-attribute questions
  • Static question flow with no adaptive AI interview to probe an actual recent decision
  • No transparent prompt logic or automated per-response quality scoring

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