The Scenario
A UX researcher on your team is starting a qualitative analysis project. She needs verbatim feedback from Canny — specifically, every comment on the top 50 most-voted posts in the Feature Requests board. She needs it in a workbook: post title, commenter name, date, and the comment text itself.
She asked for it two days ago. You've been trying to figure out how to get it to her.
The bad version:
- Open the Feature Requests board, sort by votes, click into post one
- Scroll to the comments section, copy the first comment's author, date, and text, paste into the workbook
- Repeat for every comment on that post, then click into post two
- By post four you're questioning every career decision that led here
Qualitative research is valuable. Manually extracting 400 comments from a feedback UI so that research can happen is not a good use of anyone's time.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook and, through its built-in Canny integration, exports comments at scale — pulling every reply from every post you specify, with the metadata attached.
Pull every comment on the top 50 most-voted Canny posts and write them to this Google Sheet for qualitative analysis
What You Get
- One row per comment across every post on the board
- Post Title, Comment Author, Date, and Comment Text in the columns you specified
- Date in a sortable format
- Internal team comments included unless you filter them out
What If the Data Is Not Quite Ready
You only want comments from the top 50 posts by vote count
Pull every comment on the top 50 most-voted Canny posts in the 'Feature Requests' board — write to this workbook with: Post Title, Post Vote Count, Comment Author, Comment Date, Comment Text.
Some comments are very short and likely noise — under 20 characters
Export all comments from the Canny 'Feature Requests' board — Post Title, Comment Author, Date, Comment Text. Filter out any rows where Comment Text is fewer than 20 characters.
You want to tag each comment with a sentiment label
Export all comments from the Canny 'Feature Requests' board — Post Title, Comment Author, Date, Comment Text. For each comment, classify the sentiment as 'positive', 'neutral', or 'negative' based on the Comment Text. Write the label into a Sentiment column.
Full research pipeline: export, filter, sentiment-tag, and group by post
Export all comments from the top 50 most-voted posts in my Canny 'Feature Requests' board — Post Title, Comment Author, Date, Comment Text. Filter out comments under 20 characters. Classify each remaining comment as 'positive', 'neutral', or 'negative' and write into column F. Then create a summary table starting in column H: Post Title, Total Comments, Positive Count, Negative Count, sorted by Negative Count descending.
One prompt pulls the raw data, filters the noise, adds sentiment labels, and generates a summary — so the researcher gets analysis-ready output, not a dump.
Try It
Get the 7-day free trial of SheetXAI and open a blank worksheet, then ask it to export and sentiment-tag the comments from your highest-voted Canny posts. Also see how to export the full board into an Excel workbook or the full Canny + Excel guide.