Sora Prompt for Survey Analysis
Survey analysis is a major challenge for marketing, HR, and research professionals. With hundreds or even thousands of responses to process, extracting relevant insights manually is time-consuming and prone to interpretation bias. Sora transforms this complex task into a structured, fast process. By feeding it your raw survey data, the AI identifies statistical trends, detects correlations between variables, and synthesizes open-ended responses into actionable themes. Whether you are analyzing a customer satisfaction survey, an internal employee engagement survey, or a market study, Sora helps you move from raw data to strategic decisions. The tool particularly excels at processing qualitative responses, where it spots patterns that the human eye might miss. By combining quantitative and qualitative analysis, Sora produces comprehensive reports that directly support your decision-making.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a data analyst specialized in survey research. Perform a comprehensive analysis of the following survey results.
Survey Data:
[Paste survey results here — table, CSV, or raw responses]
Context:
- Survey objective: [e.g., measure customer satisfaction]
- Population surveyed: [e.g., 500 active customers for 6+ months]
- Collection period: [e.g., January 2026]
Requested Analysis:
- Executive Summary: summarize the 3 to 5 key findings in non-technical language.
- Quantitative Analysis: calculate means, medians, standard deviations, and distributions for each closed question. Identify statistically remarkable results.
- Qualitative Analysis: group open-ended responses by recurring themes, classify them by frequency and sentiment (positive, neutral, negative).
- Correlations: identify links between demographic variables and responses.
- Segments: detect typical respondent profiles with distinct behaviors.
- Recommendations: propose 5 concrete, prioritized actions based on the results.
Present the results with structured tables and textual visualizations when relevant.
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Why this prompt works
This prompt works by assigning an expert role (data analyst), which anchors Sora in a rigorous methodological framework. The six-step structure guides the AI through a complete analytical process, from executive summary to actionable recommendations. The contextual block (objective, population, period) provides the essential metadata so the analysis is relevant and not generic.
Use Cases
Variants
Expected Output
You will receive a structured analysis report including an executive summary readable by non-technical staff, descriptive statistics for each question, and a thematic categorization of open-ended responses with sentiment analysis. The report will also include correlations between respondent profiles and answers, identified behavioral segments, and five strategic recommendations prioritized by impact and ease of implementation.
Frequently Asked Questions
What data format works best to submit my survey to Sora?
CSV or markdown table format yields the best results. Structure your data with one row per respondent and one column per question. Include clear column headers. For small surveys (under 50 responses), you can paste a table directly. For larger surveys, prefer CSV format and paste the data in chunks if necessary. Avoid PDF formats or screenshots, which lose the data structure.
How do I get Sora to analyze open-ended survey responses?
Explicitly request a thematic analysis of verbatim responses. Sora will group responses by recurring themes, assign a sentiment (positive, neutral, negative) to each theme, and rank themes by frequency. For best results, specify the desired number of themes (e.g., 5 to 7) and ask for representative quotes for each theme. If your survey relates to a specific field, mention the business context so the analysis is more relevant.
Can Sora compare results from multiple waves of the same survey?
Yes, by providing the data for each wave with the corresponding dates. Request a longitudinal analysis by specifying the periods to compare. Sora will identify significant changes, upward or downward trends, and breakpoints. To optimize this analysis, use exactly the same questions across waves and clearly indicate which period matches which data. Specify whether you want variations in percentage or absolute value.
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ChatGPT Prompt for Analyzing a Survey
Survey analysis is a crucial step for transforming raw data into actionable insights. Whether you collected responses via Google Forms, Typeform, or any other tool, ChatGPT can help you identify trends, segment respondents, and draw relevant conclusions in minutes. Where an analyst would spend hours cross-referencing variables and writing a report, AI significantly speeds up the process while maintaining methodological rigor. This prompt is designed to guide ChatGPT through a structured analysis of your survey results: synthesis of quantitative data, interpretation of open-ended responses, identification of significant correlations, and formulation of concrete recommendations. It works equally well for a customer satisfaction survey, a market study, or an internal questionnaire. The proposed approach combines descriptive statistical analysis and thematic qualitative analysis, offering you a complete and nuanced view of your results without requiring advanced data science skills.