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Survey Response Analyser

Example prompt: "When new rows are added to my 'Customer Feedback Q2' Google Sheet, classify each response by theme, score the sentiment, and update a summary tab with the top themes and overall satisfaction trend."

How to automate survey analysis with GloriaMundo

The Problem

After running a customer survey or NPS poll, you end up with a spreadsheet full of free-text responses that someone needs to read, categorise, and summarise. For a 200-response survey, this easily takes a full day of manual work — reading each response, deciding which theme it falls under, flagging urgent complaints, and compiling the results into something presentable. Most teams either delay the analysis for weeks or settle for a superficial skim that misses important patterns in the data.

How GloriaMundo Solves It

We build a workflow triggered by new rows appearing in a Google Sheet (or run on demand against an existing sheet). An integration step reads the new survey responses. An LLM step processes each response individually, classifying it into predefined themes (product quality, customer support, pricing, onboarding, feature requests, etc.) and assigning a sentiment score. A code step aggregates the classified data — counting theme frequencies, calculating average sentiment per theme, and identifying statistically notable shifts from previous surveys if historical data is available. The results are written back to a summary tab in the same Google Sheet, and a concise report is emailed to the team. Glass Box preview lets you review the classification logic and sample outputs before processing the full batch.

Example Workflow Steps

  1. Trigger (scheduled or manual): Runs when new survey responses are detected, or on demand.
  2. Step 1 (integration): Read new response rows from the Google Sheet.
  3. Step 2 (llm): Classify each free-text response by theme and assign a sentiment score (1-5).
  4. Step 3 (code): Aggregate theme counts, calculate average sentiment per theme, and identify the top 5 themes by volume.
  5. Step 4 (integration): Write the classified data and summary statistics back to a summary tab in the Google Sheet.
  6. Step 5 (integration): Email a concise report with the top themes, sentiment trends, and notable verbatim quotes to the team.

Integrations Used

  • Google Sheets — source of survey responses and destination for classified data and summary statistics
  • Gmail — delivers the analysis report to the team

Who This Is For

Product managers, customer success leads, and UX researchers who run regular customer surveys (NPS, CSAT, feature feedback) and need to turn free-text responses into actionable themes without spending a day on manual categorisation.

Time & Cost Saved

Manually reading and categorising 200 survey responses takes roughly 4-6 hours. Professional survey analysis tools with AI classification features cost £50-200/month. This workflow processes an entire survey batch in minutes, applies consistent classification logic across every response, and produces a ready-to-share summary. For teams running quarterly surveys, that is 16-24 hours of manual analysis replaced per year, plus faster turnaround — results are available hours after the survey closes rather than weeks later.