How can you use IA to scale your digital products?

The IA communicates the core value of the product. Here are a few points to consider for product scalability: 1. Scalable IA with Core Jobs: As your product grows and evolves, the IA should adapt accordingly. It should clearly communicate the new value and provide a clear entry point for users to access that value. 2. Extensibility for First-Party and Third-Party Values: Some digital products, especially super apps, integrate various services and third-party offerings. The IA should be designed to accommodate these extensions. 3.Enable personalized IA through User Behavior Learning. A well-thought-out IA solves for value discovery, usability, as well as lays the foundation for a scalable and successful digital product.

How can you use IA to scale your digital products? IA might be the core subject of the digital product, the bonus on the latest feature or the technology enabling less human intervention... when it comes to scaling, first thing that comes to mind is an industrialization that overcomes custom made solutions. IA main strength is self-sufficiency so once the need to apply IA is correctly identified and most of all correctly deployed, scalability is one step away.

"Information architecture isn't a map, it's a journey" Imagine you're building a website for foodies. What are the key destinations? Mouthwatering recipes, sure, but also guides to exotic ingredients, restaurant reviews, and maybe even a forum for heated spice debates! But how do you arrange them for maximum deliciousness? Think user first. Picture your target audience, what are they searching for? Cater your IA to their needs. Find the sweet spot between simple and complex can be tricky. Remember, flexibility is key By addressing these questions and more, you'll craft an IA that's not just a map, but a delightful journey for your users, leading them straight to their information feast.

O uso de IA em gestão de projetos em Agência de Publicidade: A Inteligência Artificial oferece vantagens significativas para a gestão de projetos em agências de publicidade, incluindo planejamento e programação eficientes, monitoramento de progresso em tempo real, alocação otimizada de recursos, previsão de riscos e facilitação da colaboração e comunicação entre equipes e stakeholders. Essas soluções promovem eficiência, precisão e adaptação às mudanças, impulsionando o sucesso dos projetos publicitários.

IA goals and principles play a pivotal role in shaping the non-functional requirements of the IT landscape. They delineate interconnectivity paradigms among applications, whether through streaming, batch processing, request/response, or event-based mechanisms. Additionally, they provide clear guidelines on information flow within the organization, facilitating the avoidance of circular flows. Moreover, IA principles streamline the requirement gathering process for new projects by setting expectations regarding information flow and the ultimate external interfaces objectives that must be achieved.

Before crafting your IA, it's crucial to delve into understanding your users and their interaction context. Employ methods like interviews, surveys, or usability tests to grasp user behaviors, preferences, and pain points. Factor in external influences such as market trends and competitors to ensure your IA aligns with user needs and business goals. This research-driven approach ensures your IA meets user expectations and technical demands.

Is it me or is this part often undervalued or overlooked? Perhaps the most useful so you are aiming at intentional audiences. It’s been my experience that people in interviews behave different than when in their known environment doing what they do. To research culture, a level of ethnography comes to mind. Seems we won’t really know who would use IA and to what extent until we get in there and show how useful it is to mark and label things to build new contexts.

The design and flexibility in your Information Architecture is what makes it possible to enhance further and scale well to user feedback, product market and plugin to latest widgets to multiply functionality for example AI enablement of say an HMS or insight with the hotel reservation portal already built. So, decide your IA carefully to make it reusable/extendable.

Comprendre vos utilisateurs est la clé de l'accompagnement. Il n'y a rien de pire qu'une IA qui nous fait perdre du temps. Pour gagner du temps grâce à l'IA vous devez d'abord en dépenser beaucoup en UX et en compréhension des objectifs finaux de vos utilisateurs. Ne vous focalisez jamais sur un retour ou un besoin pour construire votre pensée, prenez de la hauteur à chaque fois. L'esprit de vos utilisateurs est dirigé par ce qu'ils connaissent déjà et les contournements qu'ils ont mis en place dans des utilisations précédentes pour arriver à leur fins. Leur objectif final doit être votre priorité, le chemin pour y arriver doit être pavé par vous.

One way I would use AI to scale digital products would be through implementing 'recommendation engines'. The AI-powered recommendation engines would provide personalised content or product suggestions based on user behaviour and preferences. This could enhance user engagement and increases the likelihood of conversion.

Often, less is more. Consider the quickest path to get the user to their goal and see what is not necessary that could be eliminated.

This situation is why I love nature. Nature offers tons of conceptual examples of framing your context for the purpose of navigation. If you consider how a tree moves material root to leaf, then you can apply that generalized transportation concept to your situation. Perhaps it’s moving your product to the destination, perhaps it’s the production of the product such as the process a leaf uses for photosynthesis, or the path from your customer to discover your product. That is the flow of work which as in nature is always looking for the most efficient routes to continue existing. If true then IA structure would continuously evolve as well. Would it be better to build in processes to highlight the importance of IA in the decision chain?

Once you understand your users and context, it's time to structure your IA content and functionality. This forms the framework of your digital product, ensuring clear organization and efficient user navigation. Content Inventory: Create a comprehensive list of all content within your product, including different formats like text, images, videos, and interactive elements. Navigation: Design intuitive navigation systems like menus, tabs, and breadcrumbs that allow users to easily find the desired information. you can structure your IA effectively, creating a well-organized and user-friendly experience.

Be sure to conduct open and/or closed card sorts, as well as tree tests with your users to understand how they think about and mentally categorize your products or services. You can conduct these studies online or in-person, and there are a variety of tools out there to help facilitate this activity. Always test with real, representative users and not your internal audience (unless you're designing an intranet), to ensure you're getting the most accurate insights from these studies. These insights can help you model a first version of an IA so you can then test this model with users.

Effective structuring of information architecture (IA) involves meticulous analysis and organization of content and functionality. Techniques like content inventory and audit help assess the existing content, while content modeling and information mapping aid in organizing them based on attributes and relationships. Choosing navigation systems like menus, tabs, or filters optimizes user interaction. This structured approach ensures a logical hierarchy, facilitating smooth navigation and enhancing user experience.

IA elements and categories are established to be re-used in all domain specific projects overtime. Without required labelling and description, lot of context gets lost and teams realy on there own interpretation to assign them in the right way. This also reduces direct dependency on IA architect to always explain and re-explain these elements to every change in the organization. Further speaking, IA elements and categories form the backbone of organizations data lineage and data dictionary process and this is then further supported by proper labelling.

I have liked the idea of but have not implemented yet, the idea of labeling incentives for people to have reason to update information and tribal knowledge. Then add some kind of upvote or clarity trial by a membership community with skin in the game to understand information in context. Today, I (perhaps poorly) assume if this part is completed it’s because a single person on the team is willing to label a ton of stuff on the behalf of others because they understand the concept of indexes.

Set clear goals for your IA testing, like enhancing navigation, boosting user engagement, or improving information findability. Involve both users and stakeholders from the beginning to grasp their requirements and preferences throughout the design phase. Make sure to record insights from your IA testing process thoroughly. This documentation is invaluable for guiding future changes.

N'oubliez pas de demander des retours sur la qualité des réponses. Attention un like (souvent associé à un j'aime) ne signifie pas que la réponse générée est pertinente. Il faut rechercher des moyens de correctement évaluer les réponses (notamment sur les outils LLM). On peut être satisfait de la réponse mais elle peut être erronée.

In Erica Hall’s book just enough research She emphasizes the importance of conducting effective research that is both time and cost efficient. Consider running two research studies at once to generate the most value from your feedback. For example, conducting one on one interviews in one group and tree testing in another group creates data that complements and informs each other.

This is not a statement about AI, but a statement that everyone should have in their life. Iteration iteration, iteration. Like your own personal skills, it’s important to focus on the growth of any product and tool. AI is a tool that can support your product and it needs the same attention. If you stop looking for ways to grow in business others will surpass you. Every step forward, no matter how small, enriches our lives with new experiences, knowledge, and opportunities. Let us nurture our curiosity, cultivate our passions, and dare to step outside our comfort zones. It will lead to these new opportunities and new discoveries.

Il ne faut pas oublier que l'IA est un programme qui fonctionne sur l'orientation en fonction de statistiques. Il faut vérifier et adapter en permanence l'IA pour la rendre efficace et toujours pertinente. L'IA est comme un enfant qui grandi, ses parents doivent l'orienter, lui apprendre les limites et les lieux d'expression pour en voir émerger la beauté.

In the rush to meet business demands, design tweaks often unfavorably impact a product's information architecture. It's vital for designers to sync content changes with structural adjustments. With every content/information change, I recommend considering the following questions: 1. Does this change affect user navigation? It’s important to consider if the new or edited content implicates end-user flow and navigation. 2. Does this change span multiple sections? If so, consider rearchitecting to combine sections to streamline user experience. 3. Does this change improve the product’s navigation or address a particular disparity? Changes should be considered against necessity as each change implicates preestablished user behavior.

All organizations experience continuous changes in their business value chain and IT landscape. This directly influences the frequency of changes to the company's information architecture (IA) landscape. Without regular maintenance and, more importantly, evolution of the IA landscape, it becomes outdated, and teams gradually cease relying on it for guidance. Moreover, the technology landscape is constantly evolving. Therefore, elements from new technologies must be systematically incorporated into the landscape once they are proven beneficial through innovation projects.

Integrate AI-driven predictive analytics into your digital products to anticipate user needs, trends, and behaviors. Leverage predictive models to forecast demand, optimize inventory, or recommend personalized content, driving better decision-making and enhancing user experiences.

Information Architecture (IA) is often underestimated, yet it serves as a foundational step in fully understanding any design challenge with a core focus on making desired content accessible to users. Interpretations of content can vary significantly, especially within cultural contexts, as formal meanings intersect with industry or demographic-specific jargon. Establishing consistent and uniform IA aims to mitigate confusion in these interpretations, ensuring clarity and coherence across diverse experiences. Nowadays, with the advancement of AI, complex navigations can be simplified and jargon more accessible. IA may become more about maintaining a harmonised interpretation, and less of e.g. uniform use of specific words.

Most of this article brings up the idea on focusing in a single use-case for using AI. The most important part of any company is to constantly iterate and look for new ways to improve customer happiness, improve employee happiness, and get more efficient at doing business. AI has the potential, like any tool, to do all of that. Look at the tools that area are starting to hit the market with AI taking notes doing zoom meetings, or AI that helps organize a customer calendering. Not all of this means you need to build the tool but integrate with 3rd parties that can help solve the day-to-day tasks all companies have. It’s a place to look into those efficiencies and give you time to focus on the bigger picture.

I love to approach my publications understanding that not all my readers are professionals in such field of knowledge, which will make me delve into what Information Architecture (IA) is... Information architecture refers to the organization and structuring of information within a system, website, or application to enhance user understanding and navigation. It involves designing the layout, categorization, and relationships between different pieces of information to create a logical and user-friendly structure. Information architecture aims to ensure that users can easily find what they're looking for, fostering a positive user experience and efficient interaction with the information presented.

In my experience, jumping in early and harnessing the power of the early initiators and adaptors is significant. Training and learning to help others has helped me more than waiting for the entire structures to be built.