Reports & Analysis
18 articles
Understand how Koji analyzes interviews and generates research reports, themes, and actionable insights.
Exporting Research Data from Koji: CSV, JSON, and Transcript Access
A complete guide to every way you can get your interview data out of Koji — from one-click CSV downloads to real-time webhook pipelines.
Chat With Your Interview Transcripts: How Koji Lets You Query 100 Customer Interviews at Once
Stop re-reading transcripts. Ask questions in plain English across your entire research corpus and get answers with cited verbatim quotes — the practical workflow for AI-powered transcript chat with Koji.
Can You Trust AI Interviewers? How Koji Prevents Hallucinations and Bias in Customer Research
A practical guide to how modern AI research platforms prevent hallucinations, model bias, and leading questions during auto-moderated customer interviews — with the verification techniques Koji uses to keep AI-generated insights faithful to the actual transcript.
How to Read Your Koji Research Report: A Section-by-Section Guide
A complete walkthrough of every section in a Koji research report — from the overview and themes to quantitative charts, key quotes, and Insights Chat — so you can extract maximum value from your findings.
AI Research Agent: How Autonomous AI Conducts User Interviews End-to-End
A practical guide to AI research agents — autonomous systems that design studies, run conversational interviews, and synthesize findings without a human moderator. Includes how Koji's agentic stack works under the hood.
AI Interviewer Tuning: How to Get Research-Grade Voice Interviews
A complete playbook for tuning Koji's AI interviewer — company context, probing depth, structured questions, and interview mode — to deliver interviews indistinguishable from a human researcher.
Viewing Interview Transcripts
How to read, navigate, and get value from your interview transcripts in Koji.
Understanding Quality Scores
Learn how Koji evaluates interview quality on a 0-5 scale and why it matters for your research and billing.
Conversation Intelligence for Customer Research: A Practical Guide
Conversation intelligence is moving from sales calls into customer research. This guide explains what it means for product, UX, and market research teams — and how an AI-native research platform applies it across every customer conversation.
AI-Generated Insights
Discover what analysis Koji automatically produces for each interview — themes, sentiment, key quotes, and findings.
Insights Chat: Ask Any Question About Your Research Data with AI
The Insights Chat is a conversational AI interface that lets you query your qualitative research data in natural language — surfacing themes, retrieving quotes, comparing segments, and answering stakeholder questions instantly, without re-reading every transcript.
Generating Research Reports
Create comprehensive aggregate reports across all your interviews — including summaries, themes, recommendations, and statistics.
Understanding Themes & Patterns
Learn how Koji identifies recurring themes across interviews and how to use them for decision-making.
Publishing & Sharing Reports
Make your research reports accessible to stakeholders, team members, and decision-makers.
Insights Dashboard
Navigate visual analytics including interview counts, completion rates, quality distributions, and participant statistics.
Real-Time Research Insights: How to See Themes, Quotes, and Quality Scores as Interviews Complete
Stop waiting weeks for analysis — modern AI research platforms surface themes, structured-question distributions, sentiment, and quality-scored quotes the moment each interview ends. Here is how real-time research insights work in Koji and how to design studies that take advantage of them.
Adaptive AI Interviews: Branching Logic That Personalizes Every Question
How AI-moderated interviews replace static survey branching with dynamic, conversational follow-ups. A practical guide to designing adaptive interview flows with Koji.
AI Auto-Tagging for Customer Interviews: Code 100 Interviews in Minutes
How AI auto-tagging compresses 40+ hours of manual qualitative coding into minutes. Covers the two-cycle coding approach Koji uses (descriptive cycle-1 + axial cycle-2), the difference between auto-tagging and thematic analysis, building a codebook the AI respects, and how to validate AI-generated tags against your standards.