Our solution is bringing results_
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SentiSquare_ E-mail dispatcher saved 12 FTE.
Customers are getting swifter replies.
Additional value: Insightful meta-data for complaints department.
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NPS feedback analysis tells Albert what customers want.
Business Intelligence department saved time needed to sort through feedbacks.
Precise categorization of open-answer verbatims.
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SentiSquare helps identify lucrative churn candidates.
Precise prioritization of 1,250,000 text messages yearly.
Insight into ‘moments of truth’ and root causes.
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Identifying negative feedback.
Relaying precise data about customer complaints.
O2 gets a clear idea of what customers want improved.
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Cooperation in software development.
Recognition of important structural and meaning-carrying elements within text.
Solution deployed in 10 languages.
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Online chat analysis: automatic clustering of conversations.
Solved problem of ‘black box’ chat room that produces very little data.
ČS gets insight on emerging topics that customers bring up.
Technology_
Based on artificial intelligence and machine learning, our tools process large amounts of textual data no matter what the language.
We use deep semantics to discover and extract topics and issues hidden in textual content. This gives users a clear understanding and helps companies to enhance productivity and improve their processes.
