The Scenario
A product manager ran a customer satisfaction survey continuously for 8 weeks. She set it up with weekly collection periods so she could track whether sentiment changed after the team shipped a new feature in week 4. SurveyMonkey shows her the aggregate, but she wants the week-by-week answer counts for each question in Google Sheets so she can chart the before/after and bring it to the retrospective.
The bad version:
- Open SurveyMonkey's Analyze tab, click into Trends, realize the trend chart is visual only and there is no direct export option for the time-series data.
- Try the CSV export — it gives you a flat dump of all responses, not a period-by-period breakdown.
- Manually count responses by time period for each question, entering numbers into the sheet by hand — 8 weeks times 6 questions times 4 answer options is 192 cells of manual data entry.
The retrospective is in two days. Nobody hired her to do arithmetic on a survey platform. She was supposed to be finding the story in the data.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet context, connects to SurveyMonkey's trend data endpoint, and writes the structured output — period by period, question by question — directly into the sheet.
Fetch the SurveyMonkey trend data for survey ID [X] and write the answer counts per time period for each question into this sheet — one section per question with time period labels as column headers and answer options as row labels.
What You Get
- A structured grid per question: question text as a section header, answer options as row labels, time periods as column headers.
- Answer counts filled into the grid cells — not percentages, raw counts, so you can normalize yourself if needed.
- Each question gets its own section separated by a blank row, so the sheet is chart-ready without reformatting.
What If the Data Is Not Quite Ready
You want a single pivot-table-friendly format instead of per-question sections
Fetch trend data for SurveyMonkey survey ID [X] and write it in long format: column A = question text, column B = answer option, column C = time period, column D = response count. One row per unique question/answer/period combination.
The survey ran 12 weeks but you only need weeks 4 through 10
Fetch trend data for SurveyMonkey survey ID [X], filter to time periods between 2025-10-01 and 2025-11-15, and write answer counts per period for each question in the section layout with time period headers.
You want percentage share instead of raw counts
Fetch trend data for SurveyMonkey survey ID [X] and write the answer share as a percentage per time period for each question — divide each answer count by the total responses for that period and round to one decimal. Use the same section layout with time period headers.
You need the raw trend data, a per-question sentiment score over time, and a chart-ready summary — all in one go
Fetch trend data for SurveyMonkey survey ID [X] and write the raw answer counts per period in long format to the 'Trend Raw' tab. Then calculate a weekly net sentiment score for each question (positive answers minus negative answers, divided by total) and write the scores by week to the 'Sentiment Scores' tab. Write the question texts and their overall trend direction (improving, declining, flat) to the 'Summary' tab.
Ask for the full picture in one prompt — the raw pull, the scoring calculation, and the summary table.
Try It
Get the 7-day free trial of SheetXAI and open the Google Sheet where you want the trend breakdown — then ask it to pull time-period answer counts for the survey questions you care about. For pulling flat response data instead of trend aggregates, see the spoke on bulk-exporting survey responses. For the full SurveyMonkey overview, see the hub page.