The Scenario
You are a UX researcher. You ran a usability study over three weeks and collected 300 responses in Typeform. The study used five rating questions (scored 1–5) and five open-ended questions asking respondents to explain their ratings.
The product team wants a summary. Not the raw data, a proper summary table showing average score per question, top verbatim comments per question, and the response rate breakdown by week.
The stakeholder presentation is tomorrow at 2 PM.
The slow version:
- You export the CSV, import it into Google Sheets
- You write AVERAGE formulas for each rating question, clean up blank rows first
- You read through three hundred open-text responses across five questions, manually copying the most representative ones into a separate doc
- You build a pivot for response counts by submission week
- It is 11 PM and the formatting is still not quite right
- You present a half-finished table and apologize for the rest.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your spreadsheet that pulls the Typeform responses and builds the summary table for you, so you are not writing formulas at 11 PM.
Open the SheetXAI sidebar and type:
Get all responses from Typeform form ID xyz789 and build a summary table in this sheet: one row per question with average score (for rating questions), response count, and the 5 most common text answers (for open-ended questions). Put the raw responses in a tab called Raw and the summary in a tab called Summary. Also add a tab called Weekly Breakdown with a row per week showing submission count and average overall score.
SheetXAI fetches all 300 responses, writes the raw data into the Raw tab, builds the Summary table with averages and top verbatim comments per question, and adds the Weekly Breakdown tab. The presentation is ready before midnight.
What You Get
Three tabs, ready for the stakeholder call:
- Raw tab — every response, one row per submission, one column per question
- Summary tab — one row per question with average score (rating questions), response count, and top 5 verbatim text answers (open-ended questions)
- Weekly Breakdown tab — submission count per week and average overall satisfaction score per week
The top verbatim comments are pulled from the actual responses, not paraphrased or invented. You can point to the quote and tell the stakeholder which row it came from.
If the product team wants the open-ended comments grouped by theme, ask SheetXAI to cluster them. It adds a Theme column to the Summary tab.
What If the Data Is Not Quite Ready
Research exports are full of edge cases. SheetXAI handles them in the same prompt.
When responses include a mandatory question that many people skipped
Some questions had a skip logic path and a chunk of respondents never saw them. You do not want "N/A" to pull down the average.
Get all responses from Typeform form ID xyz789. For each rating question, calculate the average only from rows where the respondent actually answered that question. Show the response count and skip count separately in the Summary tab.
When the stakeholder wants top comments grouped by satisfaction tier
The product team wants to see what low-raters (1–2) said differently from high-raters (4–5) in the open-ended questions.
Build the summary table with response counts and averages per question. For the open-ended questions, separate the top 5 comments from respondents who gave an average rating of 1–2 from those who gave 4–5. Label the groups "Low satisfaction" and "High satisfaction" in the Summary tab.
When you need to compare this study to a previous round
You ran the same usability study six months ago. The previous form ID is old789.
Get all responses from Typeform form IDs xyz789 (current study) and old789 (previous study). Build a comparison table in a tab called Comparison showing average score per question for each study, side by side, with a column showing the change (current minus previous).
When the raw responses need cleanup before summarization
Some respondents typed into the text fields with inconsistent capitalization, trailing spaces, or filler responses like "N/A" or "none."
Get all responses from Typeform form ID xyz789. For each open-ended field, clean the text responses: trim whitespace, convert to sentence case, and remove responses that are blank or only contain "N/A," "none," or "n/a." Then build the summary table with the cleaned responses and list the top 5 verbatim answers per open-ended question.
The pattern: describe what clean looks like and what the summary should contain, and SheetXAI does the cleaning and the aggregation in one pass.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet, then ask it to pull Typeform responses and build whatever summary your stakeholders need. The Typeform integration is included in every SheetXAI plan. See also how to export raw responses for NPS analysis or the Typeform in Google Sheets overview.