What are the best tools for conducting user research to inform information architecture decisions?

For user research informing information architecture, tools like Optimal Workshop, Treejack, and Usability Hub are effective. They offer features like card sorting and tree testing to gather insights into user mental models and optimize information structures for better usability.

algumas ferramentas bem úteis s?o: - maze para pesquisas com protótipo - miro ou figjam para boards colaborativos - microsoft forms - para pesquisas quantitativas, card sorting - stackspot para gerar resultados compilados as transcri??es de pesquisas qualitativas e metricas de canal

1. Cognitive mapping techniques: Amazon used card sorting and tree testing to understand users' mental models and redesign its website's navigation and categories, resulting in reduction in customer support calls. 2. Behavioral analytics over self-reported data: Netflix uses behavioral data (viewing history, search queries) to personalize its content recommendations and information architecture user-wise 3. Context-driven ethnographic research: IKEA conducts observational studies to understand how customers use and organize their living spaces, informing its store layouts 4. Semantic analysis techniques: Airbnb used NLP and sentiment analysis of customer reviews to identify key themes, informing the redesign of its search filters

Conducting user research to inform information architecture (IA) decisions requires a combination of qualitative and quantitative tools. I'd suggest the combination of following: - User Interviews (Zoom, Microsoft Teams, Google Meet) - Surveys and Questionnaires (SurveyMonkey, Google Forms, Typeform) - Card Sorting (OptimalSort, UXtweak, UsabilityHub) - Tree Testing (Treejack (part of Optimal Workshop), UXtweak, UserZoom) - Usability Testing (UserTesting, Lookback, Maze) - Analytics and Heatmaps (Google Analytics, Hotjar, Crazy Egg) - A/B Testing (Optimizely, VWO (Visual Website Optimizer), Google Optimize) - Journey Mapping (Smaply, Miro, Lucidchart) - Feedback Tools (Qualaroo, Usabilla, Feedbackify)

Google Forms is a straightforward tool that allows you to easily create, distribute, and analyze surveys. It's perfect for collecting user feedback, preferences, and behaviors without much hassle. For more advanced features, consider SurveyMonkey. It offers a robust platform with various survey design options and powerful data analysis tools. Typeform offers an engaging and interactive survey experience with its conversational interface, making it easier to capture detailed responses. Qualtrics is another powerful tool, providing advanced survey features and analytics, ideal for more complex research needs.

In my view, the true power of user interviews lies in our ability to empathize with the target audience—understanding their daily lives and the tasks they need to accomplish. By immersing ourselves in their world, we can grasp not just the 'what' and the 'how,' but more crucially, the 'why' behind their interactions with the platforms. This empathy enables us to make wiser decisions about Information Architecture, ensuring that it is build to how people think. It's about creating a structure that users move through intuitively, feeling that every part of their journey has been anticipated and designed with their needs in mind.

At the beginning of the interview process, it is important to build rapport with the participants, such as sharing more detailed information about the project with them which could affect their trust in the researcher and the information they are about to see. The trust they have in the researcher and the information could have a big impact on the feedback they provide.

User interview allow observing users in their actual environment to captures genuine behaviors and interactions. AI will never replace contextual understanding in interviews! :)

One time at work, I found user interviews particularly insightful when redesigning our website's information architecture. By engaging directly with users, we uncovered specific frustrations and motivations that surveys hadn't revealed. This deep qualitative feedback was crucial in making informed decisions about structuring our content, ultimately leading to a more intuitive and user-friendly experience.

Claramente la entrevista abierta es la mejor herramienta para llevar a cabo una investigación de usuarios. La clave es dejar hablar a cada usuario, tratando de no interrumpir y observando detalladamente sus respuestas. Allí es donde encontramos los patrones mentales comunes que ordenan nuestra arquitectura de la información. En base a la coincidencia de partones entre usuarios, podremos clasificar y ordenar o incluso ampliar lo que nos falta en nuestro producto.

In my experience, usability testing has been invaluable for refining our information architecture. Observing users interact with our product revealed unexpected navigation issues and confusion points, which we could address directly to make the design more intuitive and aligned with user expectations. By testing with a diverse group of users, we ensured that our IA was accessible and user-friendly for a wide audience.

Imagine a business has received feedback about difficulty finding products on their website. Analytics show high bounce rates on category pages and low conversion rates. By leveraging usability studies, a plan to redesign the IA is made to make product discovery easier. Through think aloud protocol, and post-task interviews, invaluable insights on user pain points are gathered. Adjustments based on these findings might include renaming categories, reorganizing hierarchy, simplifying navigation paths, or improving filtering systems. A second round of usability testing is conducted, if necessary. The iterative process of usability studies ensures that adjustments are based on concrete user data, leading to more effective solutions.

Las pruebas de usabilidad son la manera más práctica para ver si el dise?o del producto funciona correctamente o si alguna parte resulta confusa. También es necesario que lo prueben personas con diversas discapacidades para asegurar que es accesible e inclusiva.

When conducting user research to inform information architecture decisions, UserTesting & Optimal Workshop can be employed to gather valuable insights. They observe how users interact with a prototype or existing product to identify usability issues.

Projective techniques like card sorting are very effective in iterating on information architecture, on a behavioral, contextual, or feature level This is because we get to understand how users group and associate terms and information, which will eventually drive user behavior and mental models for intuitive navigation of the product itself.

Card sort is a great method to improve information architecture. When we don't have an existing IA or unsure if the current IA is clear to users, we can start with open card sort first, because it can reveal users mental model on how they group and label things. Then use a closed or hybrid card sort to evaluate the IA informed by the open card sort.

?- With open card sorting, users group things however they think makes sense, revealing how they see the world. - And then with Closed card sorting we let everyone test your pre-made categories against how users would actually sort things. It's all about understanding how users think to build a system that works for them and fins the most efficient option.

Card sorting is great. It helps us understand how users may group certain elements of the product architecture. Like how may they put, log out, settings, edit profile, all under "My Account" This helps us to navigate through the final output of the Information Architecture.

Realizar Card Sorting con los usuarios ayuda mucho a entender como piensan en relación a la información que se necesita estructurar para construir una buena Arquitectura de Información. Si ya se cuenta con una base tentativa usar Card Sorting cerrado es muy recomendable para acercarse a una definición de organización. Si estamos en una etapa de descubrimiento el Card Sorting abierto puede ayudar a encontrar nuevas luces sobre términos, palabras, jerarquías que no se habían considerado pero que pueden ser muy útiles.

Analytics are crucial for understanding users' interactions, but to fully grasp their behavior, we must combine them with qualitative insights. While metrics show what users do (or don't do), qualitative research reveals why they do it (or don't do it). This holistic approach ensures our IA choices are both data-driven and user-centered, addressing not just the symptoms but the root causes of usability issues.

In my experience, Journey Mapping has been a game-changer for refining Information Architecture. In one project, we struggled to understand why users were dropping off at a critical step in the application process. After we created the CJM, we were able to visualize the user's entire path, which highlighted a major bottleneck that wasn’t obvious during regular testing. This allowed us to streamline the specific part of the flow, significantly improving user satisfaction and conversion rates. Journey Mapping has consistently proven its worth in turning abstract user data into tangible improvements in my projects.

Let us assume that user is a customer entering the shopping mall, now either the user has come with a specific purpose in mind or they just want to explore options for a specific niche. It is the job of the architect to fulfill requirements for both the users, hence we need to plan a good user journey & keep our primary features accessible. While exploring these primary features, users will by default come across secondary features; hence, keeping our UI clean & intuitive. Cherry on the cake: UI architects can change design way more easily that shopping mall owner ??

In my experience Tree Testing, Similar to card sorting but more focused on validating the hierarchy itself, tree testing involves users navigating through a simplified text version of your site structure without visual design elements. This method helps in pinpointing navigation issues and refining the categorization in your information architecture.

Here are the key points highlighting why Maze is the best tool for conducting user research, User-friendly interface for easy test creation and execution Remote testing capabilities for global participant access Supports various methods: usability testing, tree testing, card sorting, surveys Detailed analytics, heatmaps, and quantitative metrics for robust analysis Seamless integration with design tools like Figma, Adobe XD, and Marvel Collaboration features for sharing tests, live sessions, and real-time feedback Scalable and flexible for projects of varying sizes Researcher-friendly features like participant recruitment, incentive management, and scheduling tools