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.
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Multichannel analysis of customer interactions: Calls, emails, tickets.
Unstructured customer queries into actionable insight.
Discovering hidden causal patterns across touchpoints to drive process optimization.
Reference_
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SentiSquare helps us with the analysis of customer feedbacks, which is a large amount of unstructured data. With the solution from SentiSquare, we are able to better understand customer painpoints and bottlenecks in our services and focus our improvement initiatives, where it is most needed from customer point of view. We appreciate that SentiSquare solution is user friendly and also that they provide great customer support when we need. I also find very important that they constantly develope and improve their solution.
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Through its superb text analysis, SentiSquare helps us identify opportunities and pain points from customer feedback. As one of the largest Czech ICT companies, we receive tons of feedback from our customers. With the precious & limited human resources, we are not able to process it ‘manually’ by reading each one of them. That’s where SentiSquare comes into play. It ‘reads them all’ in our stead and gives us the invaluable insight thanks to its advanced text analytics (in this regard, it’s the best tool we have encountered so far). First, it categorizes feedback into comprehensible groups, so we can track changes in trend over time and work on improvements. Second, it helps us dive into instant analyses without spending lots of time looking for the relevant feedback, as we used to. In short, SentiSquare tool is a great people & time saver.
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We chose SentiSquare to further improve our customer care. During the pilot project, SentiSquare analysed around 270 000 calls, 28 000 requests, 140 000 e-mails and 27 000 technical requests for us. As a result, we discovered new connections in our data. The insight is helping us make improvements in our daily business. We can now better anticipate customer needs and take focused measures to improve and speed up the resolution of customer queries. That makes our customers want to stay with us. I can't imagine we could do that without SentiSquare.
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.
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