Survey Analyzer
Extract themes from thousands of responses
Process open-ended survey responses at scale to identify themes, sentiment patterns, and quantitative insight clusters. Generates executive summaries and per-segment breakdowns that manual thematic analysis would take weeks to produce.
GPT-4o Mini
for 800K tokens/month · 80% input / 20% output
WHY THIS MODEL
GPT-4o Mini processes large volumes of structured data efficiently at low cost, making it the practical choice for data pipelines where throughput and economics matter more than frontier reasoning capability.
ALTERNATIVE MODELS
IMPLEMENTATION TIPS
- 1
Use a two-stage pipeline: first ask the model to assign each response to one of 10–15 themes (cheap, fast), then pass the grouped themes to a more powerful model for nuanced synthesis — this hybrid approach cuts cost by 70% vs. analyzing each response deeply.
- 2
Process responses in batches of 50 and ask for consistent theme labels — define the theme vocabulary in your system prompt and instruct the model to use only those labels to ensure responses are comparable across batches.
- 3
Include demographic metadata alongside each response in your prompt — the model can surface 'junior employees feel X but senior employees feel Y' patterns that aggregate analysis misses.