All too often, product teams limit their user research too close to home. With budget constraints, a lack of resources to work with a regional team, and the complexities of translation, conducting multilingual user research inevitably takes a backseat. The result? You miss out on cultural nuances that make the fine line between an average and winning user experience as you expand globally.
Fortunately, AI-led research methods can help you scale your research even in markets where you don’t speak the native language. We created this step-by-step guide to guide you through how you can conduct multilingual AI-led research across regions where they speak multiple different languages (even if you don’t speak those languages yourself).
Why you should consider multilingual user research Multilingual user research broadens the scope of your insights programme and can help you guide your product development efforts if you’re scaling your product across different countries. It allows you to eliminate guesswork, derisk assumptions, and reduce biases about users from different regions to create a tailored product experience that users will love.
Here are some more ways multilingual user research can level up your development efforts:
Discover product-market fit in new markets : User research is critical for understanding how well your product fits in a new market outside your home base. Multilingual research studies can uncover region-specific pain points and guide your product strategy based on insights gained from each region. Map diverse user expectations and experiences : With multilingual research, you can get a pulse of your users in different parts of the world. By running research studies in each users native language, you’ll uncover how expectations and experiences differ among users in different regions. You can use these findings to create a more culturally aware user experience for each market. Iterate your product strategy: Multilingual user research is equally valuable after you enter a new market. You can create feedback loops to continuously interview users and learn more about their preferences and experiences. This can then inform your product strategy in each market.Improve localization efforts to gain a competitive edge : Multilingual research takes you closer to your users, helping you understand local differences in how your product and messaging is perceived. This will help you grow faster than competitors that provide more poorly adjusted products that don’t take into account local differences in opinions, languages and expectations. Limiting user research to your domestic market means you’re potentially designing your product in a way that isn’t optimal for your actual and potential users. A multilingual approach allows you to create customer journeys that take the differences between customers in different markets into account as your product scales internationally.
How to conduct research in new markets with multilingual AI-led studies Conducting multilingual research doesn’t have to feel like rocket science. We created this step-by-step guide to help you collect data from users across the world with multilingual AI-led studies. Let’s break down each step.
Setting up your study 1. Define the goal of your research study
Taking stock of your existing user data is a good starting point when designing a multilingual research study. You can define a clear and informed problem statement based on what you already know about your customers.
Once you’ve reviewed your current knowledge about customers, you can strategically outline your objectives for your research study. These goals will also determine the right research method for your study. Consider the most important insights you need and work backward from there to decide exactly what data you need to test your assumptions and reach your goal. Here are a few questions to ask yourself:
2. Decide your participant recruitment approach
Once you’ve outlined your research goals and study approach, you have to determine who you want to recruit for your study.
The catch is that if you’re trying to do research that is representative of multiple markets: people from different cultures will have varied perspectives on a subject. If you want to understand local differences in perceptions, attitudes and experiences across markets, you’ll need to recruit participants from those markets.
When you’re ready to kick-start your research, you can recruit participants effortlessly with Wondering’s Participant Panel , where you can:
Access a database of 120,000 pre-screened testers Apply over 250 filters to narrow your search Recruit from a global panel of 33 countries Roll out a study & get responses in hours Conducting your study in different languages with AI 3. Create interview studies in your native language
You’ve done all the legwork to plan a multilingual research study—now what? 👀
The next step is setting up your study. If you’re using Wondering for your study, you can create a study in a few seconds using our AI-powered study builder. Simply describe your research goal, and Wondering’s study builder will build a first version of your study for you. Simply type in your research goal into the study builder, and hit generate . The resulting study may include a combination of open-ended questions, design tests , multiple choice questions, rating scales, and other question formats, which you can then easily customize to make sure the study meets your needs.
But how do I adopt my study to be suitable for participants that speak different languages? This is where AI-powered translations become useful. Wondering supports studies in 10+ languages, so you can create your study in a language you’re comfortable with, and Wondering will then automatically translate the study for your participants to the language they speak. You control what language your participants can complete your study in using the following settings:
Pre-selected language: You can select a specific language to run your study. This works best when you’re interviewing users in a single country or region. Automatic translation : Wondering will detect and automatically translate the language based on each participants’ location and settings. This works best when you’re recruiting participants across markets, and where it’s likely that the participants will speak multiple different languages. Wondering uses state-of-the-art large language models to instantly translate your study in real-time, helping you interview users in a wide range of languages within hours.
4. Use AI-powered moderation to interview participants in their native languages
Once your Wondering study is ready to ship, you can:
Roll it out directly within your website, to get in-the-moment insights from real customers using your product Share it with Wondering’s global panel of 120k+ testers Create a shareable link to share through other channels As participants complete your study in their own language, you’ll start seeing your responses come in. Wondering’s adaptive AI moderator will ask intelligent follow up questions based on participants’ responses. These questions are also automatically translated to a respondent’s native language to create user interview-style conversations that help you capture insights at scale.
After the study is complete 5. Automatically transcribe, translate, and analyze responses with AI
After you’ve collected the data you need in your research study, the next step is analyzing all the data to extract actionable insights.
Typically, you’d need:
One tool to transcribe all responses Another to translate the data Another to analyze it Wondering can eliminate this hassle and do all the heavy lifting with its AI analysis .
You can see every response automatically transcribed and translated back to English in real time.
Once all the responses are in and your study is closed, Wondering can also identify key themes in user responses and summarize the overall feedback for every question. You can review supporting quotes and audio notes for each theme to quickly contextualize this qualitative data and derive insights.
6. Action and share your key insights
The final step is converting your research data into meaningful insights and sharing them with relevant team stakeholders.
While Wondering will identify recurring themes and patterns in your data, you (and your team) can connect the dots to make strategic decisions and define action items based on these findings.
For example, let’s say you’re conducting research for an eCommerce app with users in Japan and the United States. Wondering’s AI analysis tells you that users in the US prefer self-service support options like FAQ while Japanese users prefer personalized customer service.
You can use these insights to guide further research, and guide your customer support strategy across these regions.
Say goodbye to guesswork with multilingual user research Multilingual user research is the key to making sure your product can continue to scale internationally. Still, many research teams find that conducting international research studies is prohibitively expensive and difficult to pull off. It doesn’t have to be .
With Wondering, you can create, ship, and analyze a research study in a range of languages in minutes. Don’t take our word for it—sign up to test it for yourself .
