60 Open-Ended Survey Question Examples (and How to Analyze the Answers)
60 open-ended survey question examples for customer, NPS, product, employee, event and UX surveys, plus tips for writing them and analyzing the answers.
Guides, deep dives, and updates on text analysis and AI theme discovery.
60 open-ended survey question examples for customer, NPS, product, employee, event and UX surveys, plus tips for writing them and analyzing the answers.
Compare the best Thematic alternatives for feedback and survey analysis: Apercu, Caplena, Dovetail, Qualtrics Text iQ, MAXQDA, NVivo and spreadsheets.
The best tools for analyzing open-ended survey responses by situation: AI theme tools, survey platforms, qualitative software, spreadsheets and ChatGPT.
Analyze open-ended survey responses in Excel or Google Sheets: clean the data, flag keywords, code responses, count themes and chart the results.
Use ChatGPT to analyze open-ended survey responses: step-by-step prompts for codebooks and coding, how to verify counts and quotes, and when to switch tools.
Step-by-step guide to extracting themes from G2 reviews: collect reviews, split likes and dislikes, run AI thematic analysis and turn themes into decisions.
How to code open-ended survey responses: build a codebook, apply codes consistently, group codes into nets and check reliability. Free Excel template.
How to present open-ended survey results: the best charts, how to write theme headlines, choose quotes and show the base, plus an example report structure.
Inductive coding builds codes from the data. Deductive coding starts from a predefined codebook. See examples, pros and cons, and how to combine both.
Thematic analysis shows what people talk about. Sentiment analysis shows how they feel. Learn the difference, how sentiment scores work and when to use each.
Thematic analysis explained: what it is, the six steps from Braun and Clarke, inductive vs deductive approaches, a worked example, and how AI speeds it up.
Learn how to analyze open-ended survey responses step by step: clean the data, build a codebook, code answers, count themes and present results.