Customer Research Insights & Guides
Frameworks, methodology deep-dives, and practitioner guides for teams running AI-moderated customer research. From win-loss analysis to churn diagnosis to shopper insights — built on experience with hundreds of customer conversations.
Teams using AI-moderated research report 95% faster time-to-insight with qualitative depth at quantitative scale...
Browse Insights & Guides
AI-Moderated Customer Interviews for Banks: Running 200 Studies in 72 Hours
How banks use AI-moderated interviews to run customer research at scale. Covers compliance considerations, banking use cases, and how the Intelligence Hub enables cross-study insights.
AI-Moderated Patient Interviews: Running 200 Studies in 48 Hours
How AI-moderated interviews work for healthcare patient research at scale — covering HIPAA compliance, emotional laddering for patients, quality at scale, and the Intelligence Hub for longitudinal insights.
Fintech Onboarding Churn: How to Surface the Real Reasons Customers Leave
Analytics show where fintech users drop off. Qualitative research reveals why. Learn how to design churn studies that surface the trust, friction, and expectation gaps driving early-stage attrition.
Healthcare Insights: HIPAA-Compliant Voice Research Protocols
How AI voice interviews maintain HIPAA compliance for healthcare research. Covers data handling, consent protocols, de-identification, and secure research infrastructure.
Healthcare Research Turnaround: From 8 Weeks to 72 Hours
How healthcare teams compress research timelines from 8 weeks to 72 hours with AI-moderated interviews. Parallel interviewing, real-time synthesis, and practical examples.
Insurance Claims Experience Research: From Friction to Loyalty
How insurers use qualitative research to understand the claims experience, reduce complaint rates, and improve renewal intent. A practitioner guide to claims journey mapping and emotional experience research.
Medical Device User Research: From Concept to Clinical Adoption
How medical device companies run user research from concept testing through post-launch adoption, including pre-market validation, usability studies, procurement interviews, and adoption tracking.
Patient Experience Research: A Complete Guide for Health Systems
A practitioner's guide to designing and running patient experience research programs that produce actionable insights across the care journey.
Treatment Adherence Research: How to Surface the Real Barriers
Why patients don't follow treatment plans and how to research the real barriers using emotional laddering, adherence-stage segmentation, and AI-moderated interviews at scale.
Win-Loss Analysis for Financial Products: Why Customers Choose (or Leave)
How banks and fintechs use win-loss analysis to uncover real decision drivers behind product selection, switching, and competitive losses. Trust, pricing perception, and hidden deal-breakers.
AI Consumer Research in Chinese: Mandarin Market Guide
Native Mandarin AI-moderated interviews for China and Chinese-speaking markets. 5-7 level laddering. Results in English.
AI Consumer Research in English: When Default Isn't Enough
English is the global default for AI research — but when should you switch to native-language interviews? A practical framework.
Deep Dives by Research Area
Structured collections of our best thinking, organized by discipline.
AI-Powered Research
When to use AI moderation, how it compares to human-led research, and the platforms leading the shift to conversational intelligence.
- Agentic Market Research: The Complete Guide →
- What Is Agentic Consumer Insights Research? →
- Agentic AI vs. Traditional Market Research →
- Best Agentic Research Tools and Platforms (2026) →
- How to Connect AI Agents to Consumer Research via MCP →
- Your AI Agent Is Confidently Wrong About Your Customers →
- Building the Customer Truth Layer: A Technical Guide →
- Best Voice AI Tools for Consumer Research in 2026 →
Research Methodology
Laddering techniques, qual-quant blending, and the frameworks behind research that actually drives decisions.
Customer Intelligence Systems
Building institutional memory that compounds across studies, teams, and years — so research insights never go to waste.
Data Quality & Panel Integrity
Bot contamination, panel bias, and the data quality crisis reshaping how teams think about research sourcing.
Industry Trends
Strategic shifts in the consumer research landscape — where the industry is heading and what it means for insights teams.
Research Operations
Scaling research teams, managing capacity, and the operational frameworks that turn insights functions into strategic assets.
Common questions
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