Computer Vision in Research

Also known as: Vision AI, Image Recognition for Research, Visual Intelligence

Application of visual AI models to analyze images and video in research: facial coding, packaging analysis, shelf analysis.

Computer Vision in market research refers to the use of AI models capable of analyzing and extracting information from images and video to obtain consumer and market insights.

Most relevant applications: (1) Facial Coding—analysis of facial expressions to measure emotional responses to ads, packaging, or product concepts; (2) Eye Tracking—gaze tracking to understand which visual elements capture attention; (3) Shelf Analysis—automatic evaluation of product presence and position on shelf from photos; (4) Automated Packaging Test—analysis of the visual impact of packaging designs in simulated shelf contexts; (5) Social media image analysis—extracting brand insights from Instagram, Pinterest, etc.

Models like GPT-4o, Gemini 1.5 Pro, and Claude 3 have multimodal capabilities that are making computer vision more accessible to market researchers without deep technical expertise.