- Before the meeting
- Generating sticky notes
- Organizing the sticky notes into groups

Steps in the Affinity Diagramming Process

- For ideation workshops, ideas will often be sorted by the team after they are generated, all within the same workshop
- For organizing research findings, team members can choose to sort the notes after each participant's interview/test session and again after all the sessions are done  

Variations in the Affinity Diagramming Process

Affinity diagramming is primarily used by teams for organizing:
- Observations or ideas from a research study
- Ideas that surface in design-ideation meetings
- Ideas about UX strategy and vision

Uses of Affinity Diagramming

- Software (CAQDAS)
- Journaling
- Affinity Diagram Techniques 


3 Common Types of Data Analysis Methods

Affinity Diagramming refers to the process of organizing related facts, ideas, or observations into distinct categories.

University of Michigan - Ann Arbor

Methods used by UX researchers to analyze and interpret data that is collected.

Data analysis and interpretation methods in UX research

https://www.nngroup.com/articles/affinity-diagram/ 

"Affinity Diagramming for Collaboratively Sorting UX Findings and Design Ideas" (Kara Pernice)

Affinity Diagramming

- The process where understanding is built out of a collection of data.

- The process is ill defined and complex due to involving data that is incomplete, and can be deceptive or wrong. 

Sensemaking within User Research

While working with a large interdisciplinary team, everyone needs to be on the same page about user needs and behaviors, project goals, and all the different parts involved in a project. This common understanding by the team is commonly built by mapping. Mappings help a team make sense of and describe various parts and processes associated with a product or project.

UX mapping methods

Thematic analysis is a specialized nonstatistical technique used in qualitative research to analyze relatively unfiltered data by focusing on the prominent themes that emerge. Researchers use this method to deeply understand participant experiences rather than relying on numerical statistics.

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