A large multinational client asked us: Does our proposed Information Architecture structure align with how users think? Will users be able to find what they are looking for within this site design?
When creating a digital product, it’s critical to think about how to structure your content in a way that users can easily find what they’re looking for - from what information is displayed on the homepage to where they log in to their account. This not only enhances their user experience, but also improves loyalty and retention.
Information Architecture (IA) serves as the blueprint for organizing and presenting information so that users can quickly and intuitively access what they need when they need it.
UX research can help determine if your Information Architecture is working as intended or if it could use improvement.
Our client sought to develop a new organizational structure for its IA due to frequent complaints of navigation issues and a complex range of site structures across multiple systems and platforms. They wanted the new IA to be easy for users to navigate, while also being scalable across the organization in order to create consistency across their multiple online systems.
They partnered with AnswerLab to evaluate the mental models of potential and current site users and determine whether the categories made sense. Then, with a validated set of categories, our client planned to apply the new structure to other platforms across the organization.
We answered:
Our team of UX researchers conducted a multiphase research study utilizing quantitative research methods. Our research objectives included:
- Determine whether the proposed IA aligns with users’ mental models
- Identify any categories in the proposed IA that are unclear
- Evaluate the findability and organization of topics
First, we conducted a closed card sort method to understand potential users’ mental models and whether the proposed categories made sense. During the card sort, participants sorted 30+ items into pre-determined categories. Next, we conducted a tree test with participants who completed multiple tasks covering a range of topics to validate the findings from phase one, while also evaluating the findability and organization of the topics.
Each phase included 100+ participants who fit the profile of potential users of our client’s site in terms of their roles and responsibilities, company size, and annual revenue. Given the high-touch B2B nature of the respondents, our Research Operations team utilized a custom recruit method in partnership with one of our recruiting partners.
>> Case Study: Streamlining Development Pre-Launch with Mixed Methods UX Research
Outcome:
Both the card sorting and tree test methods surfaced valuable insights to inform the client’s new IA, including menu categorization and naming conventions, creating confidence in the new structure.
Some of our findings included:
- Support of the proposed new Information Architecture
- Prioritized categorization for the site menu
- Insights on naming conventions and category titles
- Clarity on items that needed to be in more than one category
- The potential need to explore workflows further with qualitative research utilizing individual user interviews
Throughout the entire study, the client engaged a large group of stakeholders composed of members from a range of internal teams, including UX and product, as well as design and content marketing strategy. This broad mix of stakeholders resulted in an extensive discussion of the results and brainstorming for the next steps—including an appetite to continue researching as they iterate for maximum impact.
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Quantitative UX research can support you throughout the product development process to accomplish a range of goals including:
- Testing assumptions and patterns
- Benchmarking metrics and behaviors
- Making comparisons across user segments
- Making informed decisions on large-cost questions
- And more
Learn more about how utilizing quantitative research methods can drive future development decisions.
