Research Studio
Research Studio is designed to significantly reduce the time spent on user and customer research by automating the analysis process. Ideal for user researchers, product managers, marketing specialists
What is Research Studio?
Research Studio automates the analysis of user and customer research data, cutting down the time spent on manual data processing. Instead of spending hours organising interviews, surveys, and feedback, you feed your research into the platform and it handles sentiment analysis, user persona generation, and competitor analysis automatically. The tool is built for user researchers, product managers, and marketing specialists who want to spend more time gathering insights and less time analysing spreadsheets. It's particularly useful if you're not a data analyst but still need to extract meaning from customer conversations and feedback.
Key Features
Automated sentiment analysis
identifies emotional tone and attitudes across customer feedback and interviews
User persona generation
creates detailed personas from research data without manual synthesis
Competitor analysis
analyses competitor research and extracts key insights automatically
Interview transcription analysis
processes recorded or transcribed interviews to extract themes and patterns
Data organisation
structures messy research data into usable formats for decision-making
Flexible export options
outputs findings in formats suitable for presentations and reports
Pros & Cons
Advantages
- Significantly reduces time spent on data analysis and manual coding of research
- Accessible to non-researchers and those without advanced analytical skills
- Handles multiple research formats including interviews, surveys, and text feedback
- Educational pricing discounts available for students and academic institutions
Limitations
- Automation quality depends on input clarity; poorly recorded interviews or unclear feedback may produce less accurate results
- May require some manual review to validate automated findings, particularly for detailed or context-dependent insights
Use Cases
Product teams analysing user interview data to identify common problem and needs
Marketing teams extracting sentiment and themes from customer surveys and reviews
Researchers processing large volumes of qualitative feedback from multiple sources
Startups creating user personas without dedicated research resources
Companies monitoring competitor research and extracting actionable intelligence