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Ivie is an AI-driven user research tool that collects qualitative insights from users to aid in building better products. It processes these insights, extracting the most valuable content from each conversation and converts it into coded user insights.

Ivie intelligently maps and aggregates these insights according to best practices in product frameworks, but also allows for custom views. It provides in-depth analysis and context understanding by breaking down insights to the original transcript, and adding all known user context.

This supports user segmentation and product development. Ivie also creates structured notes from interview transcripts, highlighting important details.

The tool is trained to understand your business, it can communicate in multiple languages and is capable of detecting accents. Ivie can be customized to your company's use case and is trained to behave as a team member.

Besides, Ivie facilitates the setup of diverse research scenarios, including customer satisfaction, win-loss analysis and many more. The tool can be embedded into your user's journey and accommodates multiple research formats including exploratory research and specific research like A/B Testing feedback, churn analysis, and more.

Ivie offers quick setup, customizable options, supports multiple question types, and can be embedded into apps/web apps or sent via email. The tool is designed with privacy and security in mind; your data is encrypted and stored securely.

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Pros & Cons


  • Coded user insights
    Mappings to product frameworks
    Customizable views
    Contextual analysis
    Supports user segmentation
    Creates structured notes
    Integrates business understanding
    Multilanguage support
    Accent detection
    Customizable to company's use-case
    Facilitates diverse research scenarios
    Embeddable into user's journey
    Supports exploratory & specific research
    Quick setup
    Multiple question types support
    Embeddable in apps/web apps
    Sendable via email
    Encrypted and secure data
    Allows automated follow-up questions
    In-depth transcript analysis
    Offers multiple research formats
    Helps in product development
    Gathers qualitative user insights
    Trained to behave like teammate
    Conducts A/B Testing feedback
    Assists in churn analysis
    Built with privacy in mind
    Supports customer satisfaction analyses
    Enables win-loss analyses
    Supports wide research templates
    Customizable research design
    Can detect user accents
    Aids in brand harmonizing
    Incorporates user context understanding
    Supports various question types
    Can perform market landscape research
    Supports feature prioritization analyses
    Extracts value from each conversation
    Fully customisable
    Supports usability & design research
    Available 24/7
    Can analyze e-commerce experience
    Can execute customer persona research
    Supports concept testing research
    Runs user education research
    Performs positioning and ad-testing
    Can conduct gamification elements research
    Facilitates job-to-be-done research


  • Limited language support
    Cannot process quantitative data
    Overly complex setup
    Data privacy concerns
    Lacks offline capabilities
    Dependent on user input
    Limited integration options
    Single focused function
    Potential accent detection errors

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