Here are 4 ways I analyze unstructured data:<\/p>\n
1. Put data into a spreadsheet<\/strong><\/h2>\nWhen I’m conducting lots of interviews or workshops, I paste the verbatim participant quotes into a spreadsheet. Each participant gets a row. Each interview question gets its own column.<\/p>\n
To save myself a step, I sometimes type my interview notes directly into a spreadsheet (rather than in a Word document).<\/p>\n
Now, I can easily sort, filter, and code the data.<\/p>\n
2. Create word clouds<\/strong><\/h2>\n![\"word](\"http:\/\/juneux.com\/blog\/wp-content\/uploads\/2016\/06\/word_cloud.jpg\")
<\/p>\n
Before hand coding unstructured data, it can be enlightening to first use a word cloud tool. It\u2019s easy to see which words pop<\/strong><\/em> using this tool and figure out which keywords to focus on when I return to my spreadsheet.<\/p>\nPrior to using the word cloud tool, I usually do additional data cleaning. For example, I will change supported, supportive, and support to all say \u201csupportive,\u201d and then run the raw text through the word cloud tool. Now, instead of splitting the vote 3 ways, the concept of \u201csupportive\u201d gets the attention it deserves.<\/p>\n
A note of caution… a word cloud is an analysis tool<\/em>, not analysis output<\/em>. Creating a word cloud isn’t the end of the analysis. Why<\/strong><\/em> do people feel anxious? Amazing? Confused? Deeper work is needed to understand what’s really going on.<\/p>\n3. Create affinity maps\u00a0using sticky notes<\/strong><\/h2>\nSometimes the number of themes is too overwhelming to report in a meaningful way. Who wants to look at a bullet point list of 50 themes? No one.<\/p>\n
When this happens, I’ll write each theme or idea onto a separate sticky note. Next, I arrange the stickies on a wall, and then group similar ideas together.<\/p>\n
Now, I can roll up dozens of themes into 3 to 5 key takeaways and create a findings report with more impact.<\/p>\n
4. Create\u00a0a mind map<\/strong><\/h2>\nThis is exactly the same method as No. 3, just digitized.<\/p>\n
When I’m collecting hundreds of insights over a long period of time or across multiple studies for the same project, then this is my go-to method. As I go through my notes or participant verbatims, I add and organize new insights to a mind map.<\/p>\n
My preferred mind mapping tool is MindMeister. What’s yours?<\/p>\n
In Conclusion<\/strong><\/h2>\nWhen interviewing customers, be sure to build in extra time after each session to:<\/p>\n
\n- Reflect.<\/li>\n
- Clean up your notes.<\/li>\n
- Conduct recap sessions with other observers.<\/li>\n
- Capture your overall impressions about the participant.<\/li>\n
- Take a photo of the participant (to keep all of them straight in your head).<\/li>\n<\/ul>\n
These extra steps will help make analysis easier AND help create richer, more vibrant customer stories for the findings report.<\/p>\n\n\n
Related Articles<\/h2>\n\n\n- Discovering Hidden Insights with Kano Analysis: A Case Study<\/a><\/li>\n
- ESAT & CSAT: A Survey Alignment Love Story<\/a><\/li>\n
- UX Research Toolbox: Anatomy of a Compelling Narrative for Your UX Research Reports<\/a><\/li>\n
- Data Overload? How to Manage the Flow of CX Insights Effectively<\/a><\/li>\n
- Bias-Free UX Research: Innovative Approaches to Mitigating Bias in the Research Process<\/a><\/li>\n<\/ul>\n\n\n
<\/p>\n
Before hand coding unstructured data, it can be enlightening to first use a word cloud tool. It\u2019s easy to see which words pop<\/strong><\/em> using this tool and figure out which keywords to focus on when I return to my spreadsheet.<\/p>\n Prior to using the word cloud tool, I usually do additional data cleaning. For example, I will change supported, supportive, and support to all say \u201csupportive,\u201d and then run the raw text through the word cloud tool. Now, instead of splitting the vote 3 ways, the concept of \u201csupportive\u201d gets the attention it deserves.<\/p>\n A note of caution… a word cloud is an analysis tool<\/em>, not analysis output<\/em>. Creating a word cloud isn’t the end of the analysis. Why<\/strong><\/em> do people feel anxious? Amazing? Confused? Deeper work is needed to understand what’s really going on.<\/p>\n Sometimes the number of themes is too overwhelming to report in a meaningful way. Who wants to look at a bullet point list of 50 themes? No one.<\/p>\n When this happens, I’ll write each theme or idea onto a separate sticky note. Next, I arrange the stickies on a wall, and then group similar ideas together.<\/p>\n Now, I can roll up dozens of themes into 3 to 5 key takeaways and create a findings report with more impact.<\/p>\n This is exactly the same method as No. 3, just digitized.<\/p>\n When I’m collecting hundreds of insights over a long period of time or across multiple studies for the same project, then this is my go-to method. As I go through my notes or participant verbatims, I add and organize new insights to a mind map.<\/p>\n My preferred mind mapping tool is MindMeister. What’s yours?<\/p>\n When interviewing customers, be sure to build in extra time after each session to:<\/p>\n These extra steps will help make analysis easier AND help create richer, more vibrant customer stories for the findings report.<\/p>\n\n\n3. Create affinity maps\u00a0using sticky notes<\/strong><\/h2>\n
4. Create\u00a0a mind map<\/strong><\/h2>\n
In Conclusion<\/strong><\/h2>\n
\n
Related Articles<\/h2>\n\n\n