Whyser

Product Introduction

1. Whyser is a qualitative research platform that uses AI-moderated user interviews to automate and scale the process of gathering customer insights. It replaces manual interview moderation with an AI agent named Pia, enabling businesses to conduct dynamic voice conversations with participants and analyze results in hours instead of weeks.
2. The core value of Whyser lies in its ability to combine the scalability of surveys with the depth of human-led interviews, making qualitative research accessible, efficient, and actionable for teams that lack time or resources for traditional methods.

Main Features

1. Whyser offers AI-moderated interviews where Pia autonomously conducts natural, voice-based conversations with participants, probing for deeper insights through follow-up questions and adaptive dialogue flows. Interviews are conducted 24/7 in over 50 languages, with real-time analysis and participant quotes directly linked to insights.
2. The platform provides a Permanent Knowledge Vault that centralizes all research findings, allowing users to query insights conversationally without manually reviewing transcripts. Every insight is backed by timestamped participant quotes, and the vault grows automatically with each study.
3. Assisted Study Setups enable users to configure research parameters in minutes using templates or custom workflows, with built-in best practices for qualitative research. The system supports audience recruitment via third-party partners or custom links embedded directly into products.

Problems Solved

1. Whyser addresses the inefficiency of traditional qualitative research, which requires weeks of planning, scheduling, and manual analysis, by automating interview moderation and insight extraction. It eliminates no-shows, scheduling conflicts, and human bias in questioning.
2. The product targets user researchers, product managers, and marketers who need rapid, scalable insights for validating concepts, identifying pain points, or monitoring brand perception but lack the bandwidth for manual interviews.
3. Typical use cases include pre-launch product validation, post-release feedback loops, competitive market analysis, advertising campaign testing, and continuous customer experience monitoring across global markets.

Unique Advantages

1. Unlike static surveys or chatbots, Whyser conducts voice-based interviews with dynamic follow-up questions, mimicking human moderators while maintaining consistency across thousands of conversations. This contrasts with tools like Typeform or SurveyMonkey, which lack adaptive probing.
2. The platform innovates with synthetic participants for study pre-testing, multilingual moderation in 50+ languages, and enterprise-grade encryption for data security. Pia applies structured probing techniques optimized for qualitative depth, such as laddering and counterfactual questioning.
3. Competitive advantages include 90% faster study completion compared to human-led interviews, 24/7 global scalability without additional staffing costs, and GDPR-compliant data handling with optional PII collection. Unlike research agencies, Whyser provides full transparency and control over study parameters.

Frequently Asked Questions (FAQ)

1. How can I trust AI to conduct reliable interviews? Whyser ensures reliability through voice-based conversations that mimic human moderators, strict topic guardrails to prevent deviation, and insights directly tied to participant quotes rather than AI-generated summaries. The system uses qualitative research best practices for probing and analysis.
2. What types of studies can I run on Whyser? The platform supports product concept testing, usability feedback, brand perception analysis, advertising campaign pre-tests, and longitudinal customer journey studies. Customizable templates are available for common scenarios like MVP validation or feature prioritization.
3. How does Whyser differ from traditional unmoderated studies? Unlike rigid task-based unmoderated tools (e.g., UserTesting), Whyser enables dynamic conversations where Pia adapts questions based on participant responses, achieving interview-level depth without requiring live moderation. Results include AI-identified thematic patterns and direct participant quotes.