TheySaid

TheySaid is an AI-driven feedback platform created by the team behind UserTesting, designed to revolutionize how organizations gather and understand user input by replacing traditional static surveys with interactive, conversational AI. Its core value lies in transforming mundane feedback forms into engaging dialogues, which significantly increases response rates and uncovers richer, more actionable qualitative insights that standard surveys often miss. By leveraging natural language processing, the tool facilitates a more human-like interaction, making the feedback process feel less like a chore and more like a helpful conversation for the respondent, thereby improving data quality and depth for the business.

Key features include the ability to deploy AI chatbots that conduct open-ended interviews, automatically analyze sentiment and thematic patterns from conversational transcripts, and generate summarized reports highlighting key user pain points and suggestions. The platform supports multi-language feedback collection, allows for the creation of custom conversational flows tailored to specific research goals, and provides real-time analytics dashboards to track feedback trends. It also enables teams to tag and categorize insights collaboratively, ensuring findings are easily organized and actionable across departments.

What sets TheySaid apart is its foundational expertise from building UserTesting, applying those learnings to a chat-based paradigm that captures nuanced feedback often lost in multiple-choice questions. Technically, it uses advanced large language models to understand context and probe deeper during conversations, adapting follow-up questions based on previous answers. The tool is a web-based platform with potential API access for integration into existing CRM, product management, or customer support systems like Zendesk or Intercom, allowing seamless feedback ingestion into business workflows without switching contexts.

Ideal for product managers, UX researchers, and marketing teams seeking to validate new features or improve customer satisfaction without the low engagement of long forms. Specific use cases include conducting continuous discovery interviews with beta testers, measuring post-purchase customer experience through automated check-ins, and running large-scale qualitative research for market validation at speed. It is equally valuable for startups needing agile user feedback loops and enterprises aiming to democratize insight gathering across global teams, making deep user understanding accessible and scalable.