Finding the best customer satisfaction survey questions that work across languages can be tricky—what sounds natural in English might feel stiff in Spanish. Creating effective AI-driven, conversational CSAT surveys isn’t just about translating words. Getting meaningful feedback means recognizing that cultural nuances shape how people express satisfaction and what resonates with them. This guide will show you how to craft questions and leverage AI tools for multilingual CSAT surveys that genuinely connect with customers everywhere.
Core questions that work in any language
Some survey questions are like a universal handshake: simple, clear, and culturally neutral. Here are several great questions for multilingual CSAT—with English and Spanish examples:
How satisfied are you with your experience?
¿Qué tan satisfecho está con su experiencia?What could we do to improve?
¿Qué podríamos mejorar?How likely are you to recommend us to a friend? (Net Promoter Score)
¿Qué probabilidad hay de que nos recomiende a un amigo?What did you like the most?
¿Qué fue lo que más le gustó?
These questions work because they’re direct, easy to translate, and avoid cultural idioms. They leave little room for misunderstanding, no matter the language.
Open-ended follow-ups, such as “Please tell us more,” or “¿Puede contarnos más?”, are critical for capturing nuanced feedback—they invite stories and details, which is where the real gold hides. If you want more tailored variations, an AI survey generator helps you instantly craft culturally appropriate questions, saving time and eliminating guesswork. Simple, unbiased questions give you clean, consistent results—no matter what language your customers speak.
And remember, 71% of customers expect companies to support multiple languages, including their native one, showing just how crucial it is to go beyond English-only surveys. [1]
Making your questions culturally relevant
It’s not just about translation; how people express satisfaction varies. In some cultures, responses are more reserved, favoring understatement (“It was fine”). Others are expressive, happily sharing strong opinions (“It was amazing!”). For instance, “How would you rate your service today?” in English feels a bit more casual than its Spanish counterpart, “¿Cómo calificaría nuestro servicio hoy?”, which can sound more formal and invites more considered reflections. Sometimes, Spanish leans more polite or indirect in surveys—knowing these subtleties helps questions feel natural.
Response scales: The scale you use to measure satisfaction can also carry cultural significance. In some countries, a 5-point scale (“Very satisfied” to “Very dissatisfied”) is the norm, while in others, a 10-point scale maps better to local preferences or education systems. Choosing the right scale helps people answer honestly and comfortably.
Emotion words: Even words like “satisfied” or “happy” aren’t always direct equivalents. “Satisfied” (“satisfecho”) in Spanish feels formal and might prompt milder answers, while “happy” (“feliz”) often brings out warmer or stronger feedback.” So, if you want to measure delight, ask about “feliz” instead of “satisfecho”—small changes, big shifts in meaning.
The beauty of modern conversational surveys is that they adapt—both the AI and the language switch naturally, picking up on customers’ cultural preferences and habits. You can also review examples of in-product conversational surveys showing these principles in action.
Smart follow-ups that adapt to each language
AI-powered follow-ups keep respondent engagement high, because the AI listens in the respondent’s language and asks natural, probing questions—not robotic translations. Here’s how this feels in action:
If an English-speaking customer says, “The service was okay,” a smart follow-up might be:
What would have made it better?
This encourages specifics, turning vague feedback into actionable detail.
If a Spanish-speaking customer replies, “El servicio estuvo bien,” the AI can naturally prompt with:
¿Qué podríamos mejorar?
Notice how both follow-ups feel conversational—never forced.
AI can do this at scale. With dynamic follow-ups, you keep customers talking, dig deeper into their needs, and never lose someone due to language barriers. You can also use prompt-based instructions to tailor follow-up intent, like:
Probe gently for emotional reasons if feedback is mixed.
These adaptive follow-ups transform your survey into a genuine conversation, making every survey a conversational survey—never just a form.
This approach is proven: AI-powered conversational surveys yield more informative and relevant responses than static forms, as shown by a study of nearly 600 participants. [2]
Keeping your data consistent across languages
Multilingual feedback introduces a real challenge: how do you synthesize dozens of voices and opinions in various languages into clear, actionable insights? Specific solves this with localization features that keep question structures consistent, while allowing free-form, natural responses in any language.
Automatic language detection: When you use Specific, respondents see surveys in their app’s language—whether that’s English, Spanish, or something else—without having to choose or switch. This frictionless experience means more completions, and less risk of misunderstanding or drop-off.
Unified analysis: After collecting responses, you don’t want to juggle multiple dashboards or translators. With AI survey response analysis, open-ended answers in any language are summarized and categorized as coherent, unified insights. Teams can chat directly with the AI about these summaries—asking questions and following threads—in their preferred language.
When localization and analysis are this seamless, you capture every customer’s voice—no matter how or where they speak up. It’s no surprise that 87% of consumers are more likely to remain loyal when a company supports their preferred language. [3]
Adjusting tone for different markets
Tone is often overlooked but can make or break your survey’s credibility—and your response rates. What sounds breezy and approachable in one language might feel unprofessional or overly casual in another. Here’s a quick comparison of Formal vs. Casual tone examples:
Language | Formal | Casual |
|---|---|---|
English | We would appreciate your feedback | What did you think? |
Spanish | Agradeceríamos sus comentarios | ¿Qué te pareció? |
With Specific’s tone controls, you can instruct the AI to speak more formally or casually, aligning survey language (and AI follow-ups) to your market’s norms. It’s as simple as chatting your preferences to the AI survey editor. When the tone feels “just right,” you see better engagement—and more honest responses—which is crucial, given that 93% of customers are likely to make repeat purchases when they receive excellent service. [1]
Building your multilingual satisfaction survey
Reaching customers in their language is no longer optional—it’s a loyalty multiplier and a competitive advantage. Conversational, AI-driven surveys capture authentic feedback by meeting customers where they are, in words they naturally use. If you're not running multilingual CSAT with AI-powered follow-ups and localization, you're missing out on deeper customer insights and genuine advocacy. Don’t wait—create your own survey and start those conversations today.