Designing Eventeer's Knowledge Base Page
Overview
Eventeer is an all-in-one community platform consisting of two products:
Eventeer for Community Manager, where organizations create and manage their communities, content, and members.
Eventeer for Community Member, where users join communities and participate in discussions and activities.
Responsibility
Research, Benchmarking
Type
Community Platform
Role
UX Researcher
Date
October, 2024
Background
As the platform continued to grow, Eventeer planned to build a Knowledge Base page as a centralized hub containing product guides, account settings, feature documentation, privacy policies, community management resources, and troubleshooting articles.
The Challenge
A knowledge base can easily become overwhelming as content grows over time. When categories are unclear and information is scattered, users struggle to find where to start, even when the answers already exist.
So, before thinking about layouts or UI, i began by asking..
How might we structure Eventeer’s knowledge base to make information easier to discover, scalable for future growth?
Benchmarking
After assessing the current knowledge base challenges, I looked into existing platforms that had already tackled similar information organization problems. I benchmarked four community platforms with large user communities and one platform with a comprehensive knowledge base to uncover how they organize, categorize, and make information easier to discover.
1. Information Architecture Analysis
I started by mapping the information architecture of each platform, from top-level categories down to individual pages, to identify common patterns in how information is organized, categorized, and surfaced to users.
Insights 💡
Here are several points that we can take from the analysis above:
Starting with high-level categories helps users build an understanding of available information before diving into details
The repeated Category → Article structure across platforms suggests that users are already familiar with this mental model when looking for answers
Platforms with more diverse user needs tend to introduce additional layers, such as user roles or sub-categories, before reaching relevant content
2. Component Analysis
After mapping the information architecture of each platform, I analyzed the components that appeared across different levels of their knowledge base to understanding which components consistently support users in discovering, navigating, and consuming information. The analysis was divided into 3 main stages:
a. Homepage : How users discover where to start
b. Category/Topic Page: How users narrow down information
c. Article Page: How users consume information and find further assistance
Research Synthesis
After benchmarking five platforms and analyzing both their information architecture and components, I synthesized the findings into a set of design principles that served as the foundation for restructuring Eventeer's knowledge base.
Provide Clear Entry Points Based on User Roles
Role-based entry points help users with different needs access information that is more relevant to their needs
Organize Content Through Clear Category Groupings
Grouping content into clear categories reduces information overload by guiding users from broad topics to specific articles. This structure also supports scalability, making it easier to accommodate new content and categories as the knowledge base continues to grow in the future
Prioritize Search Feature as a Key Discovery Tool
Providing an easily accessible search feature throughout the knowledge base supports faster discovery and reduces the effort needed to navigate through multiple content layers
Follow a Familiar Information Architecture
Most platforms use a predictable structure, such as Category → Sub-category → Article. Familiar patterns help users navigate intuitively without having to learn a new system.
Maintain Navigation Context
Use breadcrumbs to help users understand their current location and navigate easily across different levels of the knowledge base
Support Continuous Exploration
Users may need additional information after reading an article. Features such as related articles, help users continue exploring relevant content
Provide Support Paths Beyond Self-Service
While knowledge bases encourage users to find answers independently, some issues require additional assistance. Providing alternative help options, such as submitting a question or directing users to other support channels, ensures they have a clear next step when articles do not fully address their needs.
Collect Article Feedback
Gather user feedback to measure article effectiveness and identify opportunities for continuous content improvement
Information Architecture
Based on the research synthesis, I designed an information architecture that reflects users' mental models while supporting intuitive navigation, efficient content discovery, and long-term scalability.
Content Organization
Based on the defined information architecture, the knowledge base is structured into two dedicated sections: one for Community Members and another for Community Managers. This role-based organization ensures users can easily access documentation relevant to their needs, reduces information overload, and provides a scalable foundation for future content expansion
After establishing the content hierarchy, every existing article was mapped to its corresponding category and subcategory. The detailed article breakdown is illustrated below:
Lesson Learned
✨
This project changed the way I approach UX research. I learned that benchmarking is more than just comparing features, it helps uncover established user behaviors and design patterns from products solving similar problems.
✨
I also learned that content grouping should not rely solely on benchmark patterns. The proposed taxonomy is an informed hypothesis that would benefit from further validation with target users. Given more time, I would conduct a card sorting study to evaluate whether the categories align with Eventeer users' mental models and refine the structure based on their feedback
