How can user research improve your IA decisions?

Just my POV, but these contributory articles are a waste of time and poorly managed by LinkedIn. I get invites every day, and in most cases, the invitations have minimal relevance to expertise or background. Perhaps the LI team should turn off the AI and read some expert profiles. Just saying...!

To design systems and services that work for people (AND that will succeed in the marketplace), we must deeply understand what people need and want, where they live, work, and play. We get towards this understanding through conducting user research.

A itera??o com o usuário é fundamental para conseguir feedbacks sobre as hipóteses de negócios . Outro ponto importante é trazer personas que ser?o usuários da sua solu??o para o processo de discovery

I have the feeling that by contributing to articles this way, I am actually feeding ChatGPT and the like. Anyone who can give information on what these contributions are used for and how?

User research is essential to structure IA into user-friendly content flow by letting users to group, categorize, and name related content, defining hierarchy within each category. All together leads to logical information architecture well understood by users and to intuitive navigation within product content.

Your new Job: A famous Zoo has decided to open in your city or town. They ask you to design the layout of the zoo. But what animals go in which places? Where do people expect Bears, or owls to be? What are these groups of animals called? What stuff goes together and what names do people use? In order to design the Information Architecture of the zoo (all the names, places, groups of things and the overall layout map) we need to ask people things: What do they call the animals or groups of animals? Where would they expect them to be in the zoo? Not designing an information architecture (e.g. website navigation) is like someone designing a zoo without asking the visitors. Doing the research saves time and cost getting this right!

Really not quite sure why we’re focusing on just one state but I deeply feel user research is important for everyone, not just Iowa. You’re welcome.

User research is critical for shaping intuitive and effective Information Architecture (IA), much like a tailor crafting a suit to fit an individual perfectly. It involves delving into the minds and behaviors of users, understanding their needs, preferences, and how they categorize and process information. This deep understanding is vital for designing an IA that aligns with users’ mental models, expectations, and behaviors, much like how a chef tastes the food while cooking, to ensure the flavors are just right. By closely aligning the IA with how users naturally think and interact with content, user research helps avoid common pitfalls such as information overload or confusing navigation paths.

3 Concepts to Keep Upfront when doing AI Design 1. Purpose: What’s the reason for the user to use the system? This will likely change as the user and system grow with each other. 2. Value: What does the system provide to the user that improves their life meaningfully? 3. Trust: Can the user trust the system and its underlying business rules to do what the user needs to do?

If you have no previous data, IA without user research is just a guessing game. Designers and IA architects usually have a pretty good hot take on what users will do, but the research will help to solidify and make updates based on real feedback from users.

Two simple actions: (1) why do you want to define your IA again and (2) tree testing. (1) This is a combination of who your audience is, how they behave and what they need from your product or service AND what do you want to offer and what your main features or services are (your product strategy) (2) make sure you research you proposed IA through tree testing. Is the main navigation without any doubts flowing to the next steps to compete a user task. Tree testing is they way to to test if the content is in the right place of your architecture. ??

Be open-minded and get inspired by market research in 3 simple steps: 1/start with qualitative studies (user interviews, group interviews, focus groups) to discover new problems to solve; do not try to validate your own hypotheses in order not to be affected by confirmation bias; only after you have discovered the problem and present your solution (or with the help of AI which has become easy to use in these times) 2/ validate this through quantitative studies, then 3/ go into the technical details of how you will put them into practical ui/ux details. And finally, don't forget to keep researching users' reactions, you can still discover new behaviors...

Good User Research provides: Insight Generation: Generates insights that help designers understand the context in which their product or service will be used. Validation and Iteration: Can validate or invalidate design assumptions and hypotheses. User Segmentation and Persona Development: Helps identify different user segments and develop user personas. Rigorous and Systematic: User research should be rigorous and systematic, employing various research methods and tools to collect reliable and valid data. This includes surveys, interviews, observations, and usability testing, among others. Overall, user research is essential for designing products and services that meet users' needs and provide meaningful and engaging experiences.

While user interviews, surveys, card sorting, tree testing, and usability testing are all valuable, the real challenge is interpreting this data through the lens of behavioral science. This is where behavioral psychology comes into play - understanding the cognitive biases and heuristics that influence user behavior. For example, a user might say they prefer a certain feature because of social desirability bias, but their actual usage patterns, as observed in usability testing, might tell a different story. Ultimately, the goal is to not just create a product that users can navigate, but one that aligns with their natural behaviors and cognitive patterns, leading to a more intuitive and satisfying user experience.

The optimal user research approach for Intelligent Automation (IA) entails a multifaceted strategy. Initiate with surveys and interviews to understand user needs, behaviors, and pain points. Utilize analytics for quantitative insights and prototype testing for real-world observations. Embrace iterative feedback loops and collaborate with diverse user groups for inclusivity. This methodical, user-centric process ensures the development of AI systems that genuinely enhance user experiences and adapt seamlessly to evolving needs. It's a dynamic journey, not just about data collection but a relentless pursuit of excellence in Intelligent Automation.

It is crucial to align the findings with the initial objectives and assess whether it validates or invalidates the hypotheses. Then identify the actionable insights from the research to make decisions, and iterate.

To optimize user research for Intelligent Automation (IA), leverage surveys, interviews, and analytics for nuanced insights into user needs. Employ iterative refinement, using feedback loops to fine-tune IA applications based on user responses. Collaborate with diverse user groups for inclusivity, treating user research as a dynamic guide in the evolution of IA. Synthesize data to paint a holistic picture of user expectations, fueling innovation and transforming IA into a tool that profoundly impacts the human experience. It's about turning user insights into actionable steps, propelling IA towards excellence in a constantly evolving technological landscape.

Para analisar e aplicar pesquisas de usuários em tecnologias de IA, é essencial coletar dados diversos e representativos. Use métodos qualitativos e quantitativos para entender a intera??o dos usuários com a IA. Implemente ferramentas de IA para análise de sentimentos e transcri??o de entrevistas, obtendo insights mais profundos. Analise os dados coletados para identificar padr?es e tendências, usando algoritmos de IA. Essa análise ajuda a entender as necessidades e expectativas dos usuários, orientando o desenvolvimento de produtos de IA mais eficazes e centrados no usuário. Por fim, integre os insights da pesquisa no design e na itera??o dos sistemas de IA para garantir que eles atendam efetivamente às necessidades dos usuários.

A big risk of research is to rely on it too much. Some organizations have gotten trapped in a cycle of endless focus groups, A/B testing, and usability studies. Ultimately this can freeze innovation. While those practices all have a valuable time and place, don’t forget that innovation often comes from taking a risk based out of your own experience and intuition and bringing it to market quickly. From there, measure the metrics that matter - like sign ups, usage, and retention and let that be your feedback. Try this in your next product launch: have a round table with experienced minds, establish a way to test your idea in 2 weeks, do it, get some users, and measure your traction. Ultimately this is how companies scale and succeed.

Para conduzir pesquisas de usuários em tecnologias de IA, defina objetivos claros, empregue métodos mistos (qualitativos e quantitativos) e diversifique os participantes para representatividade. Utilize ferramentas de IA, como análise de sentimentos, e considere o contexto de intera??o. Desenvolva protótipos ágeis, aplicando transcri??o automatizada baseada em IA para análise eficiente. Explore algoritmos preditivos para ajustar modelos de IA. Itere continuamente com feedbacks, integrando insights diretamente no design para alinhamento contínuo com as necessidades dos usuários.

A good and a rational way is to explore information architecture from a cause-and-effect approach. Such an approach allows examining the effect of design and architecture on user behavior and outcomes. DEMETAL approach is one of the best quantitative tool that can be very effectively used where elements can be grouped together in a matrix and then analyzed that what parameters at design level can influence the outcomes and upto the degree influence can have an impact.

Content strategy changes as per the product. You need to understand who is your user before you start putting the pieces together. Your end users may vary from the general public to technical managers and so you need to create the flow of information accordingly. Think like, you are going to teach a piece of content to a 10-year-old kid and a 50-year-old. Your approach to educating both age groups will be different and this is why it is important to know who your users are.

Effective user research for Intelligent Automation (IA) involves clear goal definition, diverse user representation, and a mix of qualitative and quantitative methods. Use iterative testing for refining IA applications based on user feedback. Embrace a collaborative approach with cross-functional teams and prioritize empathy. Regularly update research strategies to align with evolving user behaviors. Consistent communication and feedback loops are crucial for iterative refinement. Document findings for informed future iterations, ensuring a continuous and user-centric improvement process.

Generally speaking having a deeper understanding of why and how people really look to find and do something is essential. Beyond the principles of simplicity, or low cognitive load, we often find humans need friction in order to find reassurance and support decision making. I've never completed user research and not learned something about myself as well as the people I am trying to help. From reasoning how we create habit forming through to bizarre acts of reassurance seeking or the need for unexpected information, it's always a game-changer when done right.

User research is critical to all aspects of AI. AI isn't going to replace humans, however, humans who can use AI will replace those that don't.

Creating a lasting impression that showcases your brand’s identity and clarifies your value proposition need to be balanced with responding to customer needs and preferences as soon as they become known. Continuous user research helps keep this balance and maintains your IA relevant and beloved.

One way of observing users from an IA perspective is to make an example with an IKEA warehouse. User research is conducted in relation to the different rooms, i.e. bathroom, living room, bed room - understanding the users needs. Then when we work to realize the researched user needs we go to the storage.

A pesquisa de usuário é uma prática essencial no processo de design centrado no usuário, ajudando a garantir que os produtos e servi?os sejam projetados com base nas necessidades e expectativas dos usuários reais.