Kanjoya’s proprietary technology goes beyond simple positive and negative sentiment to decipher emotions, human factors, and nuance in language.
We integrate emotion analytics with structured demographic information (e.g., location, age, and gender) to provide rich, high-signal guidance that improves business results.
We benchmark your data against the statistical profiles for different data sources, enabling you to identify ‘hot spots’, unusual activity, and key trends in your business.
Built for massive scale, Kanjoya’s NLP technology automatically ingests vast sets of unstructured data, from Facebook and Twitter to surveys, search trends, and forum posts.
Moritz Sudhof, Senior NLP Engineer and Algorithmic Lead at Kanjoya, manages the development of Kanjoya’s sentiment, emotion, and experience modeling technology.
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.
Sentiment Analysis relies on a simplistic classification system that only allows information to be designated as positive, negative, or neutral. These simple classifiers are often insufficient for anything but the most basic phrases. In contrast, Kanjoya Perception utilizes advanced natural language processing to identify a full range of emotions in unstructured text. Perception is able to handle nuance within polarity, conflicting polarity, and promoter/detractor detection and allows customers to understand and predict human behavior with a much higher degree of accuracy than sentiment analysis products.
Perception can handle any type of unstructured text as well as data integrated from multiple structured and unstructured sources. Common data types for Perception customers include open-ended survey responses; reviews from sites like Yelp, Trip Advisor, and mobile app stores; social sites, such as Facebook and Twitter; enterprise networks like Yammer; and text from help-desk systems.
Perception includes a consumer-based UI to encourage a broad range of users across the enterprise. Training requires less than an hour, and the setup of new data streams generally requires less then 2 minutes.
Kanjoya Perception is built to handle vast amounts of data and can scale to handle the biggest enterprise deployments. Dozens of Fortune 500 companies already rely on Kanjoya to support their marketing, customer experience, and HR analytics requirements.
Perception customers get the best results from datasets ranging from 500 rows to as high as five million social media messages.