Creating user-friendly information architecture, so people can find the disability accommodations they need.

Duration: 10 hour project

My Role: Lead UX Researcher, Lead UX Writer; recruitment of 39 users for card sorting tasks

My team: Myself and one UX Designer

 

The client

Invisible Strengths, a social networking/jobs platform for public health professionals. Invisible Strengths aims to connect BIPOC/LGBTQIA and disabled job seekers with inclusive work environments.

 
 

The task

Within the Invisible Strengths app, users will be able to use search filters to look for jobs based on the disability accommodations that an employer can provide; our task was to create an easy-to-navigate set of categories titles, to organize and label the many workplace accommodations an employer might offer.

 

Deliverables

  • Competitive and comparative analysis

  • Card sorting data, from 2 rounds of card sorting completed via UXMetrics with 39 users total

  • Research-backed recommendations for category names to be used in the “Accommodations” search filter


 
 

What I learned

  • How to use card sorting to understand a user’s mental model

  • Information architecture principles: shallow vs deep hierarchies, how to handle information that fits well in many different categories, etc.

Project Overview

The challenge: how can we create intuitive category titles for an infinite set of items?

The Americans with Disabilities Act requires most workplaces in the US to provide applicants with any reasonable accommodation they need to access a job or job application. This means the list of workplace accommodations is endless, and ever-expanding. The challenge for my team was this: how can we create category titles that are specific enough for users to navigate intuitively, but also broad and flexible enough that the categories can house new pieces of data as the app matures and new accommodations are added to each category? 

The solution:

Based on our user research, we created ten broad categories with titles that focus on the need that the accommodations within the category address. We also wrote the category titles to be flexible enough to accommodate an ever-growing list of items. The final category titles were based on two card sorting tasks I conducted with 39 users, to understand the target user base’s mental models for this type of information. The final category titles we created had a 70% rate of agreement for users who tested them, and will be used for the MVP of the Invisible Strengths app. 

Case Study

Initial research: what is the information architecture of similar sites?

I started this project by doing a competitive and comparative analysis of other platforms where users filter through different kinds of disability accommodations — a disability resource hub, an HR tech platform, and another jobs platform. I chose this approach because I wanted to get a sense of how other platforms categorize accommodation information, see if there were any trends, and get insight into how users might already be finding this kind of information.

Once we had a sense of the different kinds of categories users created, we had to choose which one to make our recommendations based on. So we took a step back to put ourselves in the shoes of the Invisible Strengths user. One of Invisible Strengths’s business goals is to be an educational tool for disabled people who might not know what accommodations ask for. Based on this target user group, we know that the audience for this app likely will not be experts on all the different accommodations they could possibly ask for, or what format those accommodations come in — but what they will know is their own experience and the specific obstacles they might face, like “I’m looking for job but I’m worried because I have low vision.” Based on the needs of this user population, we decided it made sense to pursue the goal-based category model.

Card sort 1: Uncovering users’ mental models

After this comparative research, the bulk of my work for this project was direct engagement with the target user population, through two remote card sorts. I chose the card sort methodology because, since the list of accommodations is ever-expanding, it was extremely important to learn more about the mental models of our potential users to create an intuitive search and filter experience. How would they group accommodations? Would there be widespread agreement or would there be many different ways to categorize?

I recruited 23 users through Facebook affinity groups and email groups for professionals, and created an open card sort via uxmetrics.com. The cards listed different disability accommodations, and users were asked to sort them into categories and label the categories.

Our first card sort yielded the insight that users tended to categorize accommodations in two different ways.

The first way that users tended to categorize accommodations was by goal, i.e. what kind of task the accommodation might help with. These users made categories labels like “Organizational Assistance,” or “Time Management Assistance,” and put any time management aid in there, whether that’s a physical clock or a software. The second trend was for users to categorize accommodations was by format, i.e. what kind of tool the accommodation is. These users made categories called “Office Supplies” or “Software.”

Image courtesy of uxmetrics.com

The big question: Which categorization system should we recommend?

Card sort 2: Validating and testing goal-based categories

For our second card sort, we drafted a goal-based category system to test agreement rates among users. This was a closed card sort – we created fixed “buckets” with category titles like “Organizational Assistance” and “Time Management Tools,” and instructed users to sort accommodations into the “bucket” where they thought it belonged.

I recruited 16 participants for this card sort, and when the results came in, the agreement rate was about 70% — high enough to validate that our category system was intuitive to users.

Image courtesy of uxmetrics.com

Based on our competitor analysis and direct user research, we delivered the following:

  • A clear, data-backed category system: ten broad category titles that focused on the need that the accommodation addressed and were flexible enough to accommodate an ever-growing list of items

  • The recommendation that Invisible Strengths include a search bar at the top of the accommodations filters, based on Nielsen Norman guidance on usability and information architecture standards

  • The recommendation that accommodations should be listed in any category that they feasibly belong in — because based on our card sort data, users will look for these accommodation in multiple places

Final deliverables

Impact on product

Invisible Strengths took our recommendations into account, and the category titles we created for this project will be used for the MVP of the Invisible Strengths app that is currently being built.