This evaluative research case study was completed during the SVA MFA Interaction Design program. I redesigned the information architecture of Alaska's two coronavirus resource websites into one united system that would better serve the residents and visitors of Alaska. My redesigned sitemap was informed by a content analysis, user interview, and card sorting, and validated through tree testing.
Content audit ◦ User interview ◦ Open card sort ◦ Tree test ◦ Affinity mapping
Content analysis visualization ◦ Similarity matrix ◦ Dendrogram ◦ Sitemap ◦ Desktop + mobile wireframes
Optimal Workshop's OptimalSort and Treejack ◦ Miro ◦ Figma ◦ Google Sheets ◦ Zoom
Independent project. Not affiliated with the state of Alaska.
Completed in three weeks in December 2020
Residents of Alaska do not have one centralize resource for information about the coronavirus pandemic. Instead, they have two redundant websites published by their state. The State of Alaska Department of Health and Social Services (DHSS) COVID-19 website and the State of Alaska's COVID-19 website serve the same purpose, featuring information about the virus, the state's health orders and alerts, and safety guidance for individuals and businesses. The websites appeal to the same audiences but utilize different organization systems to share the same information.
Residents and visitors of Alaska including parents, business owners, health care professionals and journalists. According to the U.S. Census Bureau, Alaska is home to an estimated 731,545 people. The population is 65.3% white and the largest minority is American Indian and Alaska Native at 15.6%. Tourism is the second largest industry in the state, after the oil and gas sector.
I was lucky enough to speak to Louis Rosenfeld about this project, which was guided by his book, Information Architecture. Using his self-described “Lou Lens”, he helped me think about the underlying politics that may result in the dual coronavirus websites from the Alaska government. He also prompted me to think like an IA consultant and consider how I would approach the research if I had access to the analytics and search logs of the websites. Lou said that quantitative data can tell you what the users want, qualitative results tell you why they want it, and together they tell a full story. When we discussed strategy, Lou said that it should be the position of an organization to meet the needs of users in a long term and sustainable way.
I conducted a remote interview with a 67-year-old woman who has lived in Juneau, Alaska for four decades to get a better understanding of the COVID-19 information she values and the challenges that may be unique to Alaska.
To get a sense of how people seek and organize COVID-19 information, I recruited users to do an open card sort conducted with Optimal Workshop’s OptimalSort software. 10 people in the U.S. completed the study, sorting 28 cards into a median of 5 categories each. The similarity matrix shows how often two cards were paired together and hints at potential groupings. The dendrogram uses the best merge method to show which card groupings have the strongest agreement among participants.
Coronavirus resource websites from all 50 states and D.C
While COVID-19 resource sites are not competing against one another, they do have the same goal of allowing a state government to share information with their constituents. I reviewed the state-run coronavirus websites from all 50 states and the District of Columbia. I noticed patterns among the sites that communicated most effectively. They featured:
Based on the insights from the open card sort, user interview, and competitive analysis, I used affinity mapping to cluster information and form categories. I color-coded based on the original categories from both websites to see any shifts in how the information is categorized. The spreadsheets from my content audit helped me generate a sticky note for each item on the homepages of both websites. Sorting also helped to reveal redundancies and inconsistency terminology. The resulting main categories were: prevention, testing, exposure, vaccine, data, updates, guidance for various groups of people, contact info, and more resources.
Based on my assessment, the State of Alaska COVID-19 website and the Alaska Department of Health and Social Services COVID-19 website should be combined into one resource hub that makes coronavirus information easy to navigate and understand. The existing sites attempt to offer all resources to all groups of people at once, with varying levels of organization ranging from ambiguous to audience-specific. By presenting links to over 100 pages on each of their sites, including linking to one another, the State of Alaska is sowing confusion during a time when access to trusted information is a matter of public health.
The following recommendations can help better organize the information on the two sites into one united system that presents the most pertinent information first and structures the rest in a way that is easy to find by the appropriate people.
Design a top level-navigation system that helps users quickly access the most sought-after information.
Design an organization system with intuitive labels that groups relevant information. Create an area for audience-specific information. Be cautious of overusing the terms "COVID-19", "resources", "information", and "guidance" in labeling.
Utilize a working search function that is placed in an easy-to-find spot and is accessible on every page.
My redesign of the information architecture of Alaska's two COVID-19 resource websites combines them into one resource that makes it easy for users to find the latest updates, recognize the symptoms of COVID-19, find a testing site, tips for prevention, and guidance for specific groups of people. Each page would feature a search bar, a navigation with access to core categories and a footer with more information should they still have questions.
Creating a sitemap and then tree testing it helped me see what was working and what was leading to some confusion. I was able to iterate on my proposed sitemap based on the results. For example, when searching for information for high-risk groups, one third of the tree test participants first checked under "Guidance for..." before finding the correct page under "Prevention". This helped me decide to cross-list the "High-Risk Groups" page under both categories, so that the most vulnerable people are sure to find the information specifically for them.
Competitive analysis helped inform my choices when creating a wireframe. While all of the information is available via the navigation menu, the homepage layout can help emphasize certain categories so that users don't have to look far for the information they seek. I was sure to design with responsiveness in mind, since the current DHSS site is not responsive.
Embrace the challenges. I went looking for a website in need of some IA help, and chose Alaska's DHSS COVID-19 site because at first it confused me. Once I started digging in, I realized that there was a second site serving the same purpose and knew I couldn't ignore it. Analyzing and combining all of the content on two sites made for an even more unique challenge. The amount of information presented between the websites was overwhelming, and I learned to accept that feeling as I continued with my research until I felt confident enough to tackle it head on during the affinity mapping stage.
The right research tools. Learning to use Optimal Workshop's tools was one of the highlights of this project for me. They provide so many ways to analyze and understand the findings. The free account comes with limitations, like only being able to include 10 participants and a maximum of 30 cards, so I had to be thoughtful about the people I recruited and cards I wrote. If I was working with a longer timeframe and the full suite of tools, I would recruit participants who lived in or visited Alaska across more representative demographics. I learned how to do tree testing towards the end of this project, but now I see how it could be useful in the beginning as well to test the effectiveness of the existing IA and later compare the results to the solution.
Think like the stakeholders. This project was completed without buy-in from officials in Alaska. I emailed the webmaster and called the information hotline, but was unsuccessful in connecting with the right people. When the hotline recording said that they were inundated with calls and their voicemail box was full, I wondered if a more effective website would help people find the answers to their questions before resorting to calling. If I was able to team up with the state government, I would want to incorporate the officials' goals for the website, use the search logs and analytics to understand what information was most sought after by the users, and get a better sense of the political challenges of publishing a public health resource during a pandemic.