Our NLP algorithms understand the voice of customer on a big data scale.
From social search to surveys, we analyze vast sets of unstructured, un-contextualized data, decipher the expression, and deliver actionable insights.
Actionable Insights delivered through technology
Our technology is based on a decade of innovation and co-developed with leading researchers from Stanford University. We deliver emotion analytics where simple sentiment technologies just won’t cut it.
Our proprietary technology goes beyond positive/negative to decipher emotions in text, uncovering the ‘human’ in language.
We integrate emotion analytics with structured demographic information (e.g., location, age, and gender), resulting in a rich, high-signal dataset.
Built for massive scale, our technology automatically ingests vast sets of unstructured data, from Facebook and Twitter to internal surveys, search trends, and forum posts.
We build statistical profiles for different data sources and benchmark your data against them, enabling you to identify unusual ‘hot spots’ in your data.
Context-aware emotion modeling for customer insights.
His team, in collaboration with researchers at Stanford University, is leveraging the rich corpus of emotion data from Experience Project to model human expression in language.
Listen to Moritz present at the Symposium this year to learn more about the world beyond sentiment analysis: Context-aware emotion modeling for customer insights.
The experience project difference
Big data foundation for understanding emotion.
With a linguist's perspective and a statistician's toolbox, we’ve trained our algorithms on this collection of experiences to understand how people talk when they feel certain ways.
From regular English language usage to social conversations riddled with emoticons, colloquialisms, and slang, Kanjoya models the different meanings words can have based on topic and speaker.