Case Study: smileML achieves real-time user sentiment analysis with Google for Education

smileML analyzes user reactions every quarter-second with Google for Education

smileML, a startup founded by Shannon Anderson and Ethan Petersen, faced the challenge of obtaining genuine, unbiased user feedback for their mobile app. The traditional process of conducting live user testing was time-consuming, expensive, and difficult to scale. They needed a better way to capture and analyze user reactions in real time. This led them to partner with Google for Education and leverage Google Cloud's AI tools.

The solution implemented using Google for Education involved building a software development kit (SDK) that uses a facial recognition algorithm running on Google Compute Engine. The SDK records and analyzes user emotional responses during testing, with data streamed through BigQuery for real-time dashboards. This allowed smileML to provide product developers with immediate, quantitative feedback on user sentiment. Google for Education's platform, including Firebase, provided an affordable and scalable infrastructure that automated processes and reduced operational stress for the startup.

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