Product Concept Testing

Video interviews and AI moderation accelerate customer feedback collection and analysis for product concept testing.

Business impact

• Video concept-testing project completion time reduced from six weeks to two days — Speeds up project delivery by automating interview moderation and synthesis
• 81 percent reduction in market research costs — Lowers expenses by replacing human interviewers with AI agents at scale
• Product development time cut in half — Speeds up ideation and refinement by generating and visualizing concepts faster

Data requirements

• Video interviews with customers (Video) — Capture real-time user reactions and feedback during concept testing
• Text transcripts of interviews (Text) — Enable natural language processing to analyze and summarize responses
• Customer preference and market data (Structured) — Inform AI-generated concept ideation and refinement
• Image data from concept sketches (Image) — Support generative AI to enhance and visualize product concepts

AI methods and techniques

• Agentic AI — Conducts dynamic, adaptive interviews with participants in real time
• Generative AI — Creates and refines product concepts and visualizations from input data
• Predictive AI — Analyzes feedback to forecast product success and customer preferences

AI models and model families

GPT-4o, Claude, Midjourney

Industries

Real-world evidence

4 documented case studies on record.

Companies using this: Creative Dock, Duolingo, Loft, Nestlé.