More Than AI Moderation: Rigorous Quant and Rich Qual, Working as One

More Than Just AI Moderation

AI-moderated interviews aren't new. Tools that run smart conversations at scale have been around for a while.

But here's the gap: most treat qual as a standalone exercise. You get synthesized themes, maybe some basic rating scales – and when you need rigorous quant, you're in a different tool. When you need both connected, you're stitching.

AI Moderated Video Questions work differently. Adaptive, AI-led video interviews embedded directly into rigorous quantitative studies. Qual and quant designed together from the start. 2-3x deeper responses than standard open-ends. And researchers shaping the output — not just AI generating summaries.

It's not just moderation. It's quant and qual working as one system.

The Problem: Data vs. Context

Insight teams are stuck between two worlds. Quantitative surveys deliver scale and statistical confidence, but they don't explain why. Qual interviews deliver depth, but they don't scale and often don't connect back to your structured data.

So teams run separate studies, export from multiple tools, and spend days stitching the story together manually. The quant lives in one place. The qual lives in another. And the full picture? That's on you to assemble. By the time you've synthesized everything, the window for decision-making has often passed. Stakeholders needed answers last week.

Knit solves this by bringing quant and qual together so insight teams can get both credibility and context, and deliver decision-ready insights while they still matter.

What Makes This Different

AI Moderated Video Questions are embedded directly into quantitative studies. Same respondents. Same study. Same dataset.

Deeper than surveys.

AI-moderated video with real-time probing. Follow-ups based on what the respondent actually says, not a fixed script. The conversation goes where the insight is. The result: 2-3x richer responses that surface what you didn't know to ask about.

More scalable than traditional qual.

Run hundreds of conversations overnight. No scheduling, no moderator fatigue, no weeks of fieldwork. Go from survey to story in a week or less.

More credible than standalone AI qual.

AI-Moderated Video Questions are connected directly to quantitative data. When you present findings, the qual illuminates the quant, not just sits beside it. That's the difference between data your stakeholders question and insights they act on.

Decision-Ready Insights, Not Just More Data

The goal isn't more research. It's research that drives decisions. AI Moderated Video Questions are designed to deliver decision-ready insights where the findings are clear, credible, and actionable the moment they land. Here's what that looks like:

• Connected findings. "73% rated price as their top barrier and here's what that actually means in their own words."
• Faster time to insight. One study instead of two. One analysis instead of stitching reports together. Days, not weeks.
• Stories that stick. Quant earns credibility. Qual creates resonance. Together, they move stakeholders to action.

When qual and quant work as one system, you're not just delivering data, you're delivering answers.

How It Works

AI Moderated Video Questions are built into the survey workflow:

1. Define your goals. Set research objectives, your AI interviewer's persona, and guardrails for the conversation.
2. Respondents engage on camera. Within the survey, participants respond to video questions, just like they would with a human moderator.
3. AI probes intelligently. Based on each response, the AI asks personalized follow-ups, digging into the "why" behind the "what."
4. Everything connects. Questions are fully integrated with Knit's thematic analysis for automated tagging and reporting, and you can easily create showreels directly from responses.

Everything—from survey to synthesis and story—lives in one system.

Use Cases

• Exploratory research. Surface unexpected insights through AI conversations, then validate them quantitatively in the same study.
• Concept and creative testing. Get quantitative performance metrics alongside rich qualitative feedback on why concepts resonate (or don't).
• Segmentation. Understand not just how segments differ numerically, but what drives those differences, in their own words.
• Post-experience feedback. Capture structured satisfaction data and detailed experience narratives without running two separate studies.

See It In Action

Want to see how quant + qual integration delivers decision-ready insights?

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