Attention, engagement, emotion.
This is the currency of revenue growth and customer satisfaction, because emotions drive spending. These quantities have been measured only as guesses and indirect inferences. Until now.
Across multiple industries, Fortune 500 companies and their market research partners are ideally suited to leverage emotion insights derived from facial expression analysis. The insights gained from Emotient give businesses the ability to make better decisions and accelerate their revenue growth.
A Young Company with a Long Pedigree
Emotient began at the Machine Perception Lab at University of California, San Diego, and has since attracted industry leaders across the realms of business, technology and science. The Advisory Board includes Paul Ekman, Ph.D. and Terry Sejnowski, Ph.D., prominent leaders in facial behavior and machine learning, respectively.
Emotient’s facial expression coding system sets the industry standard, delivering 95%+ accuracy using real-world videos and even higher precision in formal settings. The company’s investment in deep learning methods ensure its leading performance will continue to improve.
Around this scientific core, Emotient has built a cloud-based architecture which uses neural net technology to analyze videos quickly and to scale economically. The platform is built in a modular fashion allowing it to adapt to evolving customer needs, and is equipped with a RESTful API for straightforward integration with partner and customer systems and applications.
On-Demand Measurement of Emotional Response
Emotient’s flagship service, Emotient Analytics, analyzes videos of customers as they experience marketing, products and services. It provides complete and accurate facial expression detection and frame-by-frame measurement of seven key emotions, as well as attention, engagement and positive or negative consumer sentiment. The insights gained from quantifying emotions let companies pinpoint and fix issues and improve their market performance. It is accessible directly through a browser or via the Emotient Web API.
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