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