How do you measure the value of information architecture for user experience?

Do we want to define IA goals? Or is it that IA supports the UX goals instead? In the end, you need the IA of your product or website to resonate with the mental model of your users to ensure a delightful experience. I’d probably refocus this a bit into understanding the gap between the current IA and the ideal one. That’s the end goal

In my experience, well defined "Jobs to be Done " are excellent methods for helping understand if an IA is effective. If users are unable to achieve their goals easily, then it shines a light on IA / wayfinding improvements to be made.

Measuring the quality of IA is also very important to ensure that users can easily find, understand, and interact with the information on a digital platform. Here are some key metrics and methods: - Conduct usability tests with representative users to evaluate the IA's effectiveness in helping them find information - Use card sorting exercises to gather insights into how users naturally group and categorize content - Perform tree testing by giving users a task and a simplified version of the IA structure to see how easily they can locate specific content. -Measure the time users spend on specific tasks or navigating through sections of your website or app. Faster task completion times indicate efficient IA.

Been studying Machine Learning (quantitative approach)… great tool to not only “learn patterns” but also to predict behaviors… combine this with a Jobs to be done approach (quantitative approach with stated and unstated needs), and you’ll be already ahead of the game!

Pattern recognition unlocks both user intuition and engineering capacity. Finding efficiencies and framing information into repeatable frameworks (such as list>detail>edit) can be a good starting point as an objective to simplify an existing product.

"Information Architecture (IA) and User Experience (UX) are distinct but inherently complementary elements in digital design. IA establishes the structural framework, organizing content for optimal accessibility, while UX orchestrates the complete user journey, addressing usability, visual design, interactive functionality, and emotional engagement. In essence, they represent two intertwined aspects of the same digital ecosystem, working collaboratively to create a holistic and technically sound digital solution."

From what I read, there is no mention whatsoever of secondary data; everything described is primary. Secondary data can be potentially helpful when organizing your IA and comparing metrics.

I suggest to structure the measurement methods between quantitative and quantitative and expand on the advantages of each to help practitioners chose the appropriate method

From my perspective, sourcing and analysing whatever data is available is a great start to identify problem areas but to really get to the bottom of why there is not substitute for observing & talking with users

Measuring time on task, directness of task completion, task success are all viable metrics depending on what your data is telling you about the current state of affairs with your Information Architecture. It's also important to understand user confidence. A user who fails a task, but is confident that they completed indicates a problem. A user who completes a task correctly, but has low confidence that it was completed is also a problem.

Most importantly, creating documentation capturing research, findings and decisions will help technical and non technical teams implement information architecture designs. It is not a bad idea to submit documentation for stakeholder review as a RFC or Request For Comment. Soliciting feedback from technical stakeholders is essential for IA feasibility. All too often, designs for a frontend experience cannot be implemented due to technical constraints.

If a product or service doesn't have a good in-market exemplar to map against the brief probably too complex. When designing something genuinely de-novo: IA can, and should, be opinionated. A mistake I see often is borrowing a pattern and applying it to a completely different set of goals. Sometimes, the introduction of friction can enforce user-behaviour towards the desired business outcome (even if the users' commentary of the experience may not be positive). The goal shouldn't be to get users to "like" the experience, it should be objective towards the desired outcome.

IA studies will give you insight, but they will not lead you to a single conclusion about how to set up your taxonomy or labeling. My best advice is to produce many multiple models that the data is leading you to and conduct subsequent studies to home in on what is going to work best given the goals, constraints, and tradeoffs for your project.

The goal of information architecture is to organize content in a way that makes it easy for users to learn, adapt to, and navigate a product quickly and with minimal difficulty.?Information Architecture contributes greatly to designing an efficient and easy-to-use product.

Consider not measuring your Information Architecture at all. It could be a complete waste of time if your product is on the smaller side.

I’d add an example of the expected outcome. Otherwise the article seems somehow superficial. For example, after you carry the card sorting and validate the IA with tree testing, the result can inform the navigation structure, you’ll learn what resonates with your users in terms of labels and structures. This, supported by shadowing and interviews will help product builders inform the end navigation menu

Consider how your business and engineering teams are organised. A great IA balances intuitive informational and service structure, with the pragmatic challenges of building and maintaining a product across a business. During design, recognise that users are also the people who build and maintain this information, so research and recognise who will be responsible for each part of your IA and consider how the organisational or engineering structure can be leveraged to ensure your IA is sustainable.

UX architecture begins its value by directly impacting how users perceive and interact with digital products. It's like the blueprint of a building – it sets the foundation for a positive user experience. Without a well-thought-out architecture, users may struggle to navigate, find information, or complete tasks, leading to frustration and potentially driving them away from the product or website. In contrast, a thoughtful UX architecture can make interactions smooth, efficient, and enjoyable for users, which is crucial for the success and adoption of digital products.