Analyze 200 Video Responses in 20 Minutes with AI
RecRam AI automatically transcribes every video and adds a summary, keywords, and a sentiment label to each response, so you can search, filter, and spot patterns across hundreds of responses without watching them all.
Video Forms28-day trial · No credit card
Sound familiar?
“You ask the right questions. You get real answers. Then the footage sits in a folder because processing it manually is impossible at scale.”
Step by step guide
Analyze 200 Video Responses in 20 Minutes with AI, step by step
Video FormsGather video feedback at scale
Send a RecRam video form to your users, customers, or research panel. They record answers to open-ended questions in 1 to 3 minutes each. Works on mobile, desktop, no download needed.
Segment your ask: send separate forms to power users, occasional users, and churned users. The same question yields vastly different insights across cohorts. Segmented data is immediately actionable where aggregate data is vague
Open-ended video questions reveal what closed-ended surveys hide: "What frustrated you most this week?" uncovers specific bugs, missing features, and UX problems that a 5-point scale never surfaces
Include a screen recording question for usability research: "Show me how you currently do [task]. Record your screen as you walk through it." Observed behavior is more truthful than self-reported memory
Ask 3 questions max per form. Video fatigue sets in quickly, so 3 focused questions produces far richer data than 7 rushed ones where engagement drops after question 3.
AI processes every response automatically
Each video is transcribed automatically. The AI writes a summary, runs sentiment analysis, and extracts keywords for every response, with no manual review required.
AI Analysis lets you specify exactly what to look for: "Score each response for mentions of pricing/value, competitor alternatives, specific features, and onboarding difficulty" (custom analysis criteria, not generic sentiment categories)
Sentiment goes beyond a 1 to 5 scale: every response gets positive, neutral, and negative percentages plus an overall label, so mixed feelings show up instead of averaging out
Search and tag at scale: search transcripts for "navigation" and tag the matches, and a clear product priority emerges in minutes, not after a week of manual thematic coding
Use AI Analysis to define custom analysis criteria: "Look for mentions of pricing, onboarding difficulty, or competitor comparisons in each response."
Surface patterns and share insights
Let AI Analysis rules flag negative sentiment to find your most frustrated users. Search transcripts for specific keywords. Export AI summaries as CSV for your product team. You only watch the footage that matters.
Export filtered segments directly for product decisions: "All responses mentioning navigation issues" → CSV for the UX team. "All responses from churned users mentioning pricing" → CSV for the growth team. Data goes where it's needed without a research bottleneck
Share the actual clips: 5 customers describing the same pain point in their own words is more persuasive to leadership than 5 bullet points in a deck. Use tags to collect them in minutes
Track themes over time: run the same questions quarterly and compare how often each tag appears. Fewer navigation complaints after a redesign proves product impact with customer voice, not vanity metrics
Pick 3 to 4 responses showing the same pain point and play them as a "voice of customer" segment in your weekly product meeting. It's more persuasive than any slide deck.
Ready to run your first video feedback analysis?
Try It Free, No Credit CardConnect with your existing tools
Automatically route responses to your CRM, project management, and communication tools.
Related Use Cases
User Testing & Bug Reports
Users report bugs with vague descriptions like "it doesn't work." Your team spends hours reproducing issues.
Every bug shown on screenFeature Request Collection
Feature requests come from everywhere: Slack, email, support tickets. There's no single source of truth.
Requests shown, not just describedBeta Feedback Loops
Beta testers sign up excited, give one round of text feedback, then go silent.
Feedback at every product milestone