You collected hundreds or thousands of survey responses. Now what? Most people stare at a spreadsheet full of scales, open-ended comments, and demographic columns, unsure where to even begin.
Analyzing survey data traditionally requires stats knowledge and expensive software. With getqueryly, you skip the code. Upload your file and we tell you what it means: which groups answered differently, what trends stand out, and what people really said. We calculate from your actual file and prove it with a chart.
Whether you exported your results from Google Forms, SurveyMonkey, Typeform, or a custom tool, you likely have a CSV file with your responses. getqueryly handles all standard survey export formats. Just upload your CSV and the AI immediately understands the structure of your data, identifying question columns, response types, and skip patterns.
There's no need to reformat or clean the file first. The AI figures out what each column represents and how the data is organized.
Want to compare responses across different groups? For example, how satisfaction scores differ between age groups, or how NPS varies by customer segment.
In traditional tools, that means pivot tables and manual setup. With getqueryly, you simply ask: "How does satisfaction differ between male and female respondents?" or "Show me NPS by customer segment." We calculate from your actual data and show the result in a clear table, with a chart to prove it.
The most valuable survey insights often come from open-ended text fields. But reading through hundreds of free-text responses is tedious, and manual coding is prone to bias.
AI-powered sentiment analysis automatically categorizes text responses as positive, negative, or neutral, and can even identify specific themes and topics. Ask questions like "What are the main complaints from dissatisfied customers?" or "What do people love most about our product?" and get summarized insights drawn from every response.
Rating scales are everywhere in surveys, but analyzing them properly isn't straightforward. Averages can be misleading.
Ask getqueryly to show the distribution of responses for any question, compare scores across groups, or identify which statements have the strongest agreement. We handle the math and tell you what it means in plain English.
Common survey metrics like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES) can be calculated and segmented instantly. Just ask:
The real power of AI survey analysis is speed. What used to take days of manual spreadsheet work now takes minutes. You can run follow-up queries as new questions come to mind, exploring your data from multiple angles without starting over each time.
Stop letting survey data sit unanalyzed in a spreadsheet. Upload your results and start getting answers today.
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