Quelles sont les meilleures plateformes de test utilisateur pour effectuer des tests d’utilisabilité à distance ?

Recruiting a diverse group of participants is crucial for gaining comprehensive insights. Partnering with specialized agencies can help you reach underrepresented user groups, ensuring that your design caters to a broad and inclusive audience.

Recruiting the right users is critical for meaningful UX research. One technical nuance worth adding: beyond demographic filters, the best platforms also support screeners, allowing researchers to validate participants based on specific behaviors, product usage, or experience levels—ensuring higher data quality. Additionally, automated incentive handling is a big win for operational efficiency, but it’s equally important to monitor response reliability and use tools that support session replays or follow-up tasks to enrich insights. Top platforms for robust recruitment and testing: UserTesting, PlaybookUX, Lyssna (ex-UsabilityHub), and TestingTime.

If you’re building for “everyone,” you’re building for no one—and your research will reflect that. How do you define who *shouldn’t* be part of your UX research?

In remote research platforms, optimizing participant recruitment goes beyond demographic and behavioral targeting. Incorporating attitudinal and psychographic variables—such as user intent, product familiarity, and digital maturity—can significantly improve sample relevance. Applying mixed-method screening logic (e.g., branching surveys or screener tasks) helps ensure that the recruited participants truly represent the target user segments, thereby increasing the validity and reliability of the research findings.

Um ponto que sempre levo em consideração é a diversidade dos participantes. Às vezes a plataforma entrega rápido, mas o perfil acaba enviesado se você não prestar atenção nos critérios. O Maze e o PlaybookUX têm opções interessantes, mas dependendo do projeto, prefiro usar minha própria base de usuários e integrar ferramentas de gestão de incentivo, tipo Tremendous, pra garantir controle e engajamento.

Targeted user recruitment is essential for relevant insights. Platforms with filtering and incentive management streamline the process and improve feedback quality. 👍

Excelente pergunta! Em um cenário cada vez mais digital, os testes de usabilidade remotos se tornaram fundamentais para garantir experiências intuitivas e centradas no usuário. Plataformas como UserTesting, Maze, Lookback, PlaybookUX e UsabilityHub se destacam nesse processo, oferecendo recursos para capturar feedback real, analisar o comportamento do usuário e identificar pontos de melhoria com eficiência. O mais interessante é que essas ferramentas permitem testar com públicos segmentados, sem sair de casa — o que agiliza o ciclo de desenvolvimento e coloca o usuário no centro das decisões.

As plataformas que mais uso atualmente é o Maze e chatGPT. Apesar da taxa do chatgpt ser de 87% com usuários simulados, já conseguimos ter uma base para ao menos ter algumas hipóteses. Já o maze é excelente para testes remotos, com ele conseguimos ter uma base de como os usuários estão se comportando na solução.

Ótima pergunta sobre plataformas de teste remoto! Algumas das principais que vejo são: UserTesting: Ampla gama de testes e painel diverso. Lookback: Ideal para testes moderados ao vivo. Maze: Foco em testes não moderados e métricas. Optimal Workshop: Também oferece testes remotos, além de IA. Hotjar: Análise de comportamento com opções de feedback. Userfeel: Testes com feedback de "pensamento em voz alta". A escolha depende do tipo de teste, orçamento e recursos desejados. Quais outras vocês têm usado?

“Testing with just anyone is better than not testing. But testing with the right user is what drives product decisions.” In past projects, I’ve learned that precision in user recruitment matters more than the number of tests. Behavior > demographics. 👉 Co-creating recruitment criteria with the product and data team has helped me extract much stronger insights — fast.

Creating realistic and engaging test scenarios helps obtain more accurate and actionable feedback. Grounding tests in real user behavior is essential to uncover genuine usability issues.

To deepen the technical perspective: creating effective usability tests involves more than intuitive interfaces—it requires support for advanced logic, like conditional branching, task randomization, and success criteria definition (e.g., time on task, completion rates, error tracking). These features ensure richer, more reliable data from task-based testing. Another key technical layer is cross-device testing and custom metrics tracking, which let you validate how users behave in different environments and capture quantitative signals beyond self-reported feedback. Platforms like Maze, Useberry and UserTesting stand out for enabling both structured test flows and granular behavior tracking.

A clunky test design tells users more about your team’s blind spots than your product’s usability. What’s one thing you always do to make sure your usability tests reflect real user behavior?

Na minha experiência, o ponto-chave é desenhar o teste como se fosse uma conversa, não uma prova. Tentar captar o comportamento real, sem induzir. Comecei a revisar meus roteiros pensando sempre: ‘essa pergunta aqui está me levando pra onde?’. Uso muito o Maze pra fluxos simples e gosto das sugestões automáticas que ele dá pra evitar viés. Mas nada substitui um bom pré-teste com alguém neutro pra validar o roteiro antes de rodar pra valer.

Creating well-structured tests with clear, unbiased questions is key for actionable insights. Platform guidance on best practices is invaluable for reliable data. 👍

A good test isn’t the prettiest: it’s the one that triggers the right questions. Well-crafted tests lead to actionable decisions. Pro tip: run your usability test internally before going live.

Writing a good usability test is way harder than it looks, one vague task or leading question and your whole session goes sideways. The top platforms really help here with clean, flexible test builders that let you mix tasks, questions, even screen recordings without overcomplicating things. What I’ve found useful is how some tools give tips while you build, like reminding you to avoid yes/no traps or helping you word tasks more naturally. That guidance makes a big difference, especially when you're deep in the weeds. At the end of the day, the goal is to keep the test feeling real for users, if it feels like a quiz, you won’t get honest behavior.

Begin by outlining your test goals, what exactly are you trying to learn? Use platforms that support multiple task types (clicks, think-aloud, screen shares). Look for conditional logic and branching (e.g., Maze, Useberry) so you can simulate real user paths and edge cases. You don’t need fancy UI, just a clean interface for fast iteration.

Real-time observation truly adds a valuable layer to UX research, capturing spontaneous reactions, facial expressions, and non-verbal behaviors that often go unnoticed in unmoderated tests. From a technical perspective, leading platforms allow you to flag key moments, add collaborative notes, and even integrate with clipping and auto-transcription tools to speed up post-session analysis. Top platforms for this include Lookback, UserTesting, UserZoom, PlaybookUX, and Validately (now part of UserZoom), all offering strong features for live moderation, cloud recording, and team collaboration.

Real-time observation offers invaluable insights into user behavior and thought processes. Advanced tools like eye-tracking can reveal subtle usability issues that might otherwise go unnoticed.

Watching users struggle with your product live is humbling—but it’s the fastest way to build something they’ll actually love. How do you turn live user insights into quick, meaningful improvements?

Usar sessões ao vivo com o Lookback mudou muito minha forma de interpretar o feedback dos usuários. A diferença entre ler um formulário e ver a reação facial ao vivo é gritante. Muitas vezes, o usuário até completa a tarefa, mas você percebe hesitação, frustração ou surpresa só observando o comportamento corporal. Esses detalhes não aparecem nos dados frios — e são eles que mais influenciam na decisão de iterar o design.

Real-time observation offers invaluable insights into user behavior and immediate reactions. Recording sessions allows for deeper analysis later. 👍

I advocate to have a two-person tag-team… Do invite stakeholders to observe the sessions, but you want 1x moderator and 1x task-logger to be driving and capturing everything. I use Lookback and Userlytics these days but cut my teeth on Morae. It is with this tool that I learnt about the power of task-logging codes. While the moderator focuses on the research and the participant, the task-logger should be continuously smashing shortcut keys and mnemonics based on what’s happening. For example, quickly typing “B PLP Filters” would be translated post-session as a “Bug” on the “Product Listing Page”, specifically around the “Filters”, and would be auto-timestamped. You can then search and filter a CSV export for ease post-session.

O Clarity é uma ferramenta que permite observar o comportamento dos usuários durante a navegação no produto, identificando possíveis atritos e oportunidades de melhoria.

Watching a live test is therapeutic. You realize the problem was never the user. I’ve witnessed long-standing assumptions collapse in real-time sessions. Record everything, but be fully present. The most valuable insight might come from a pause… or a sigh.

There’s nothing like watching someone actually use your product in real-time. That’s where all the honest stuff comes out, the pauses, the confusion, the “wait, where do I click?” moments you’d never catch in a written response. The top platforms make live sessions super smooth, and being able to jump into those calls, ask follow-ups, and catch reactions as they happen? Game changer. Plus, having recordings means you can rewind the pain points and show your team exactly what went sideways. Way better than just saying “users were confused.” You see it, and that’s where the real fixes start.

If you're testing live, pick a platform with session streaming and moderator controls (GermainUX, UserZoom, Lookback). Watch what users do and how they react. Mute distractions, prep a discussion guide, and always record sessions for later analysis. For asynchronous tests, ensure video/screen/audio gets captured in full.

Top platforms offer robust tools for analyzing test data: automated transcriptions, sentiment analysis, and heatmaps help identify key patterns efficiently. 👍

Combining qualitative and quantitative data yields a richer, more nuanced understanding of user behavior and preferences. A mixed methods approach is often necessary to fully capture the complexity of user interactions.

Drowning in user data is easy—what separates teams is knowing what *not* to act on. How do you decide which usability insights are worth turning into roadmap priorities?

Quando comecei a fazer testes, caía na armadilha de tentar ‘anotar tudo’. Com o tempo, percebi que o valor real tá em identificar padrões — e isso exige um olhar mais estratégico. Hoje uso ferramentas como Dovetail pra centralizar insights e cruzar dados qualitativos com gravações. A transcrição automática ajuda muito, mas o que mais curto é poder taguear momentos específicos nos vídeos pra montar histórias que realmente ajudem o time a tomar decisões.

You don’t need more data, you need better questions. I’ve been there: reading every piece of feedback with no clear focus. It’s chaos. Analysis starts with a good hypothesis. Tools help, but it’s critical thinking that turns raw data into direction.

Digging through test data can get messy fast, especially when you’ve got hours of recordings, notes, and random “hmm” moments to make sense of. That’s where good platforms really shine. The solid ones help you spot patterns without losing your mind, with tools like auto-transcripts, click maps, and even mood tracking to catch the stuff you might’ve missed. What I’ve learned is that the magic isn’t just in collecting feedback, it’s in finding the signal through all that noise. When the platform helps connect the dots for you, it saves serious time and lets you actually focus on improving the experience, not just sorting through chaos.

Good platforms summarize both quantitative (completion rates, time on task) and qualitative insights (verbatim feedback, facial reactions). Use tagging and highlight reels to speed up pattern recognition. Germain UX-style tip: correlate behavioral data with system logs if you're testing in production.

Shared notes, highlight reels, and tagging features in top platforms streamline collaboration, making insights more accessible to the whole team. 👍

Effective collaboration relies on the right tools and an inclusive approach. By involving cross-functional teams early and often, you can ensure that all perspectives are considered, resulting in more robust and effective design solutions.

Collaboration shouldn’t just be about sharing findings—it should be about co-creating solutions. How do you ensure that insights from UX research actually influence product decisions?

Um ponto que aprendi na prática: o valor do teste cresce exponencialmente quando o time inteiro participa do processo. Uso muito o Dovetail pra isso — consigo marcar trechos dos vídeos e montar bobinas por tema, o que facilita demais a comunicação com PMs e devs. Às vezes, mostrar 10 segundos de vídeo tem mais impacto do que mil planilhas. Ferramentas que permitem anotação colaborativa ajudam o time a construir uma leitura coletiva dos insights.

A good insight is an insight that spreads. I’ve seen brilliant discoveries die in hidden Notion pages. The best testing tools aren’t just about data, they’re about sharing understanding. When the whole team sees the problem, solutions come faster.

UX research gets way more valuable when the whole team’s in on it, not just the researcher. That’s why I’m big on platforms that make it easy to tag moments, drop comments, and share clips without turning it into a mess of Slack threads and Google Docs. When you’ve got PMs, devs, and designers all seeing the same user pain points in real-time (or close to it), decisions move faster and feel more grounded. I’ve found that even a short highlight reel of key moments can shift a roadmap more than a 20-slide deck ever could. Good collab tools make the insights stick, and make the fixes happen.

You want real-time commenting, clip sharing, and role-based access. Look for tools that allow cross-functional teams (product, design, dev, QA) to jump in, annotate, and extract insights together. Miro-like boards or integrations with Slack, Jira, or Confluence work well.

Ensuring accessibility in testing broadens participation and reflects a commitment to inclusive design (WCAG compliance). Essential for ethical and effective research. 👍

Garantir a conformidade com padrões de acessibilidade nos testes de usabilidade é fundamental para que pessoas com deficiência possam interagir com produtos digitais de forma autônoma e digna. Mais do que uma boa prática, é um compromisso ético e social com a inclusão. Ao considerar desde o início as necessidades desses usuários, o design se torna verdadeiramente centrado nas pessoas — ampliando o impacto positivo da tecnologia na vida de quem mais depende dela para acessar informações, serviços e oportunidades.

Respecter les normes d'accessibilité dans les tests d’utilisabilité est essentiel pour permettre aux personnes handicapées d'utiliser les produits numériques de façon autonome et digne. C’est plus qu’une bonne pratique, c’est un engagement éthique en faveur de l’inclusion. En intégrant leurs besoins dès la conception, on crée des produits véritablement centrés sur l’humain.

Check if the platform itself is WCAG compliant. Then ensure it supports screen reader testing, keyboard-only navigation, and color contrast assessments. If accessibility is critical, use Fable or UserWay. Bake inclusive design into your test script... don’t bolt it on later.

✅ Testbirds → Especializado en crowdtesting para evaluar productos con usuarios reales. ✅ UserFeel → Perfecto para realizar pruebas sin necesidad de suscripción. ✅ Userlytics → Gran herramienta para reclutar participantes y realizar pruebas remotas. ✅ LookBack → Facilita entrevistas en vivo y uso compartido de pantalla. ✅ Useberry → Enfocado en pruebas de prototipos y conceptos. ✅ Lyssna → Ofrece información específica sobre UX y retroalimentación en tiempo real. ✅ Playbook UX → Ideal para pruebas no moderadas. ✅ Trymata → Enfocado en agencias y pruebas avanzadas. ✅ Optimal Workshop → Herramientas de investigación de usuarios con múltiples funcionalidades.

Depois da inteligência artificial ficou difícil não utilizar-las para testar tenho aqui algumas sugestões de plataformas: Pollfish, Attention Insight e Flowshot.ia Mas confesso que com a implementação de inteligência artificial no Figma e no Notion. Acredito ser mais vantajoso utilizar uma plataforma conhecida e dominada que aprender a usar uma nova. Assim eu otimizo o trabalho e acelero minhas entregas.