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Google analytics for open-text feedback
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Google analytics for open-text feedback
Etuma Feedback Categorizer (EFC) is a multi-language open-text feedback categorization service for (mostly) B to C companies. It extract the topic and sentiment of discussion. Etuma uses rule-based Natural Language Process and have created solutions for over 20 verticals. This means that there is no need for timely and costly machine learning phase. The categorization accuracy is over 90% day one. Main focus is on certain verticals in which the companies have hard time creating and sustaining loyal customers: travel and hospitality, online shops, web services, gaming and gambling.
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Pasi Tapanainen
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CEO at @Connexor. Board member in three companies. Guru in Natural Language Processing, Sentiment analysis and Text Analytics. Worked at univs, Xerox, start-ups
Matti Airas
Avatar for Matti Airas
Co-founder and VP Marketing and Sales, Etuma. First 15 years of Nokia, then ten years as entrepreneur with 3 start-ups and one exit.
Valuation

$0

Funded over

1 round

Latest round

Seed (Sep 2013)

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