A way to sort items according to similarity
Use this template to reveal patterns by sorting items based on similarities. This helps to define commonalities that are not necessarily obvious.
This design thinking method allows you to draw insights and new ideas out of otherwise disparate pieces of information. Discerning patterns among data is also a useful way to tame complexity.
Identify themes and patterns in customer feedback or the user experience
Simplify complex datasets by grouping items into themes
Reveal relationships between items or themes that may not be obvious
Collaborate to make more informed decisions based on the data
To run a successful affinity clustering exercise, follow the steps below.
Add data to the template in the form of sticky notes, broken out by topic or participant. This can take the form of research data, user feedback, notes from a retrospective — anything where you have a large dataset to analyze.
Have your team look over the data points and assign them to clusters based on themes. As you do this, look for what patterns emerge. Define each theme or category with a sentence or description.
Once the themes have emerged from your clustering exercise, the natural next step is to use your findings to inform further decision-making. What action items or next steps do your themes suggest?
To run a successful affinity clustering workshop with your team, you should:
Include as much data as possible before beginning your workshop so that your team has the best opportunity to identify connections and relationships, further informing the themes that emerge
Use color coding and tags for sticky notes to help keep track of how your data have moved as you group each item into themes, and the arrange tool to create clean grids once you’re done shifting content around the canvas
Use anonymous voting to help determine the top priorities and action items that result from your investigation
Try clustering the idea post-it notes into new groups and changing the number of clusters to find different trends or uncover new pain points
Affinity clustering, also known as affinity diagramming or KJ method, is a design thinking technique used to organize and prioritize ideas generated during a brainstorming or ideation session. It involves grouping similar ideas into clusters or categories based on their relationships to each other. Affinity clustering is commonly used in project management, product development, and other collaborative settings to facilitate decision-making, problem-solving, and innovation.
The purpose of an affinity diagram is to organize and make sense of a large number of ideas or data points generated during a brainstorming or ideation session. By grouping similar ideas together based on their relationships, an affinity diagram helps to identify patterns, themes, and insights that may not be immediately apparent when looking at individual ideas in isolation.
This can help teams make better decisions, prioritize ideas, and develop more effective solutions to complex problems.
Additionally, the process of creating an affinity diagram is often highly collaborative, allowing team members to work together to find common ground and develop a shared understanding of the problem or opportunity at hand.
Mural is the only platform that offers both a shared workspace and training on the LUMA System™, a practical way to collaborate that anyone can learn and apply.