Create your survey

Create your survey

Create your survey

Best survey questions for feedback: how to write great questions for multilingual survey audiences

Adam Sabla - Image Avatar

Adam Sabla

·

Sep 11, 2025

Create your survey

The best survey questions for feedback aren’t just clear in English—they need to resonate across languages, too. Designing great questions for multilingual survey audiences means anticipating more than just literal translation.

Getting global feedback right means navigating cultural nuances and avoiding translation bias. In this guide, you’ll find a practical playbook for crafting effective feedback questions for cross-language success—plus hands-on tips leveraging our multilingual survey capabilities.

Core principles for multilingual feedback questions

Every feedback survey needs questions people actually understand. For multilingual surveys, simple, direct language is your ally—it reduces confusion and keeps questions faithful across translations. This applies whether you’re using an AI survey builder or creating questions by hand.

Idioms, metaphors, and references like “in a nutshell” or “hit the nail on the head” can stump even professional translators, and result in survey responses that lose meaning. Avoid idioms and strip out slang, local jokes, or abbreviations—they rarely have direct counterparts in every language, and research confirms this is a key step to avoiding misinterpretation worldwide [2].

Stick to concrete language—ask about actions, experiences, or events your audience can visualize, not abstract ideas like “value” or “alignment.” Sentences should be complete, not fragments: different languages require different structures, and complete sentences reliably preserve meaning during translation [3].

Good practice

Bad practice

How satisfied are you with our service?

How much do you vibe with our approach?

What can we improve to serve you better?

What can we tweak to hit a home run?

Example: “What stood out to you the most?” may become ambiguous when translated. Instead, try: “What specific part of your experience was most helpful?” Concrete, specific, and globally clear.

Because I know firsthand how consistency matters, I recommend using Specific’s AI to lock in uniform phrasing across languages—and keep your feedback questions crisp every time.

12 feedback questions that work globally

Let’s get practical: here are twelve feedback questions any global team can run, plus localization guidance. These questions are organized by category, with recommendations for tone and follow-up so that even as they’re adapted automatically in other languages, they remain effective and clear.

  1. Satisfaction

    • 1. How satisfied are you with our product or service?
      Spanish: ¿Qué tan satisfecho(a) está con nuestro producto o servicio?
      Tone: Neutral and polite
      Follow-up limit: 2, ask for specific reasons if dissatisfied

    • 2. Was there anything you found frustrating?
      French: Y a-t-il quelque chose qui vous a frustré(e) ?
      Tone: Gentle, non-accusatory
      Follow-up limit: 1, probe for examples

    • 3. Did you find what you were looking for?
      German: Haben Sie gefunden, wonach Sie gesucht haben?
      Tone: Reassuring and straightforward
      Follow-up limit: 1, clarify if not

  2. Improvement

    • 4. What could we do better?
      Spanish: ¿En qué podríamos mejorar?
      Tone: Open and constructive
      Follow-up limit: 2, ask for suggestions

    • 5. Did you run into any problems?
      French: Avez-vous rencontré des problèmes ?
      Tone: Supportive, solution-focused
      Follow-up limit: 1, ask for resolution ideas

    • 6. Is there something missing you expected?
      German: Gab es etwas, das Sie erwartet, aber nicht gefunden haben?
      Tone: Curious, inviting
      Follow-up limit: 1, clarify expectation

  3. Experience

    • 7. How easy was it to use our product/service?
      Spanish: ¿Qué tan fácil fue usar nuestro producto/servicio?
      Tone: Simple and direct
      Follow-up limit: 2, explore any difficulties

    • 8. Was any part confusing?
      French: Y a-t-il quelque chose que vous avez trouvé déroutant ?
      Tone: Friendly, non-judgmental
      Follow-up limit: 1, ask what helped clarify

    • 9. Did you receive good support from us?
      German: Haben Sie von uns guten Support erhalten?
      Tone: Appreciative, warm
      Follow-up limit: 1, request detail if not

  4. Recommendation

    • 10. Would you recommend us to a friend or colleague?
      Spanish: ¿Nos recomendaría a un amigo o colega?
      Tone: Respectful, neutral
      Follow-up limit: 1, ask for main reason

    • 11. What’s one thing that stood out for you?
      French: Quelle est la chose qui vous a le plus marqué ?
      Tone: Curious and positive
      Follow-up limit: 2, dig into story/context

    • 12. What would make you use us again?
      German: Was würde Sie dazu bewegen, unser Angebot erneut zu nutzen?
      Tone: Aspirational
      Follow-up limit: 2, discuss motivators/barriers

If you want a shortcut, the AI survey generator crafts these questions for you automatically and optimizes for your selected languages. Specific’s automatic AI follow-up questions also flex to your audience, adapting tone and depth across language boundaries. This is what makes true localization possible—even for open-ended probes.

Avoiding translation bias in feedback surveys

Translation bias happens when questions are misunderstood or lose their intended tone—often because of literal translation or unfamiliar phrasing. This can cause misleading or unreliable feedback, reducing data quality.

Literal translations can swap the original intent for something strange! For example, “What’s your biggest pain point?” might literally translate to “Where is your biggest physical pain?” in some languages. Instead, directly ask, “What challenges did you face during your use?” This prevents misinterpretation and bias. Other pitfalls:

  • Example 1: “What’s your two cents?” → Solution: “What is your opinion?”

  • Example 2: “How’s it going?” → Solution: “How is your experience so far?”

  • Example 3: “Please rank on a scale of 1–10” may not translate intuitively. Solution: Explain the ends—“1 means not at all satisfied, 10 means very satisfied.”

  • Example 4: “Are you on cloud nine?” → Solution: “Are you very satisfied?”

Question length also matters. Longer or compound questions tend to lose clarity when translated, causing more room for mistakes or misunderstanding. Stick to short, single-idea questions when possible. Testing translated surveys with native speakers is crucial to eliminate errors or cultural mismatches before launch [4]. We see this in our own practice—live conversational surveys help catch misunderstandings instantly, before they snowball.

Response scales rarely map one-to-one between cultures. For example, some cultures avoid extremes (choosing 5 out of 10 as “average”) while others see 7 as “neutral.” Always state what each end of a scale means, and keep response order the same in every translation to maintain data consistency across languages [1].

If you want to dig deeper into response meaning, Specific’s AI survey response analysis tool reveals multilingual insights—surfacing trends, misunderstandings, and even subtle translation mismatches.

Setting up your multilingual feedback survey

The best global surveys nail their tone of voice for the culture: polite and formal for German audiences, relaxed and informal for Latin American respondents, and neutral for mixed settings. Set tone once in your AI survey builder and your follow-ups auto-adjust for every language.

Different regions respond to probing in unique ways; for instance, Japanese or German audiences may prefer fewer follow-ups, while North American or Brazilian respondents might welcome more in-depth questions. I recommend follow-up limits of 1–2 in most multilingual feedback flows, with culturally-sensitive escalation only for key insights.

Time zone and response pattern matter, too: send conversational surveys when local working hours begin, not when your team is available.

Localization settings in Specific let you enable multiple languages per survey and tune each version. As you build, the AI survey editor lets you tweak language and follow-up logic with a simple chat command, making it easy to apply local context to every feedback flow. Example prompt:

“Adjust the tone for our Spanish survey to sound more casual, and reduce follow-ups on question 5 for French users to just one."

Conversational format helps clarify misunderstandings—if a respondent seems confused, the AI can restate or rephrase until they feel comfortable. Try this direct in the AI survey editor for language-specific tweaks.

Start collecting global feedback today

Clear, culturally-tuned feedback questions help you unlock authentic insights—no matter the language. Conversational surveys let people share honestly, making feedback feel natural in every region, and removing friction from multilingual experiences.

Ready to reach your entire global audience? Create your own survey and discover how Specific’s conversational approach handles cultural nuances automatically—we make it simple to truly understand what your users, customers, or stakeholders are telling you, worldwide.

Great feedback begins with questions every voice can answer.

Create your survey

Try it out. It's fun!

Sources

  1. checkmarket.com. Multilingual survey best practices: response order and data consistency

  2. surveysensum.com. Blog: Tips on creating multilingual surveys

  3. forstasurveys.zendesk.com. Best Practices for Multi-Language Surveys

  4. checkmarket.com. Importance of testing translations before launch

Adam Sabla - Image Avatar

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.