Affinity Diagram

Mastering the Affinity Diagram in UX/UI Design

An affinity diagram, also known as a KJ Method, is a powerful tool used in UX/UI design to organize and categorize large amounts of qualitative data. It helps teams to visually cluster ideas, opinions, and insights into related groups, facilitating clearer understanding and informed decision-making during the design process.

What is an Affinity Diagram?

An affinity diagram is a visual method of organizing data, typically generated during brainstorming sessions, user research, or usability testing. It involves grouping related items into clusters based on their natural relationships, allowing designers to identify patterns and insights that might not be immediately apparent.

How to Create an Affinity Diagram

  1. Gather Data: Collect all relevant qualitative data from various sources, such as user interviews, surveys, or brainstorming sessions. Write each piece of data on a separate sticky note or card.
  2. Generate Ideas: Encourage team members to generate as many ideas or observations as possible without initial judgment or categorization.
  3. Sort Ideas: Spread out all the sticky notes or cards on a large surface. Begin grouping related items together based on their natural relationships. This step should be done collaboratively to ensure diverse perspectives.
  4. Label Clusters: Once the items are grouped, label each cluster with a header that describes the common theme or insight. These headers help in understanding the main categories and their significance.
  5. Analyze and Prioritize: Review the clusters to identify key themes, insights, and priorities. This analysis helps in making informed design decisions and identifying areas that need further exploration.

Benefits of Using Affinity Diagrams

  1. Enhanced Collaboration: Affinity diagrams foster teamwork and collaboration by involving all team members in the data organization process.
  2. Clear Visualization: They provide a visual representation of data, making it easier to see patterns, relationships, and gaps.
  3. Better Decision-Making: By organizing data into logical groups, affinity diagrams help teams make more informed and objective decisions.
  4. Improved Understanding: They help in synthesizing large amounts of information, leading to a better understanding of user needs, pain points, and preferences.

Best Practices for Affinity Diagrams

  1. Inclusive Participation: Involve all relevant stakeholders in the process to ensure diverse insights and perspectives are considered.
  2. Stay Open-Minded: Avoid premature categorization or judgment of ideas. Allow natural relationships to emerge during the sorting process.
  3. Use Physical or Digital Tools: Depending on the team’s preferences and resources, use either physical sticky notes or digital tools like Miro, Mural, or Trello.
  4. Facilitate Discussion: Encourage open discussion and debate to ensure all viewpoints are considered and to refine the categorization.

Applications of Affinity Diagrams in UX/UI Design

  1. User Research Synthesis: Organize and synthesize data from user interviews, surveys, and usability tests to identify common themes and insights.
  2. Brainstorming Sessions: Structure and prioritize ideas generated during brainstorming sessions to focus on the most promising concepts.
  3. Feature Prioritization: Group and prioritize features or requirements based on user needs and business goals.
  4. Problem-Solving: Identify root causes of usability issues or design problems by clustering related observations and feedback.

Tools for Creating Affinity Diagrams

  1. Miro: A collaborative online whiteboard platform that allows teams to create and organize affinity diagrams in real-time.
  2. Mural: Another digital workspace that facilitates collaboration and the creation of affinity diagrams.
  3. Trello: A project management tool that can be adapted for organizing and categorizing ideas using cards and lists.


Affinity diagrams are an essential tool in UX/UI design for organizing and making sense of qualitative data. By clustering related items into meaningful groups, designers can uncover patterns and insights that inform better design decisions. This collaborative and visual approach not only enhances understanding but also drives effective problem-solving and innovation.

Ondrej Zoricak
Ondrej Zoricak