Published on 28|3|2022 by Lucie Kolářová
On March 24, 2022, SentiSquare together with partners IXPERTA and Atos organized a conference in WorkLounge dedicated to innovation and analysis using artificial intelligence for call centers.
The event brought together many industry experts from contact centers, call centers, customer service departments of banks, insurance, energy, retail and more.
The speakers were Tomáš Brychcín from SentiSquare, Michal Pleyer from Atos, Tomáš Roubíček from IXPERTA.
For SentiSquare we presented the topic: Contextual call center analytics. Tomáš Brychcín, CEO of SentiSquare explained how we do it about contextual analytics of call centers. Let's take a brief look at what the attendees learned from SentiSquare's presentation at the conference:
The main ingredient of SentiSquare technology is called Distribution Semantics..
Its idea is that "Meaning comes from context". As a result, one is able to discern the meaning of an unknown word.
Distributive Semantics acknowledges the ideas of the English linguist J. R. Firth as early as the 1950s, when he uttered the famous quote:
"A word is characterized by the society in which it occurs" (J. R. Firth, 1957).
Just as the human brain works, so do the SentiSquare algorithms. They learn meanings from context. And how does Distributional Semantics help us in analyzing calls?
We face many problems in call analysis:
Information density is much thinner
Spontaneous talk (lots of ballast)
Frequent word splitting (parasitic words)
Often "non-speech" sounds are transcribed (parasitic words)
Need to perceive a much wider context than for normal text
You just can't do it without context in calls. Thanks to distributional semantics, SentiSquare technology can tackle these problems and also brings the following benefits:
Algorithms learn meanings directly from text (language independence)
Algorithms are adapted to client data (higher success rate)
We implement projects in various languages including Czech, German, English, Hungarian, Polish, Japanese, Chinese, etc.
With these capabilities, SentiSquare technology can analyze calls by knowing the true meaning of the call from the context.
Having explained the principle behind SentiSquare technology and how its approach overcomes the challenges of call analysis, we also answered the question:
According to our experience, we've put together the top reasons that drive our existing clients to call center analytics:
Identifying trends and themes in calls
Insight into customer sentiment and the way customers express themselves
Overview of dissatisfied callers
Agent performance review
Check for adherence to call scripts
Search for cross-selling opportunities
Review of successful and unsuccessful calls (subsequent call-script improvements)
Not too lax/aggressive operator?
Predicting customer churn
And finally, perhaps most importantly:
Before starting the "Contextual Analytics for the Call Center" project, we ask the question with our clients: Do you want to focus your analytics on your customers or on your operators? Or both?
What is the difference in the approaches?
Why are they calling? What is the reason for the contact?
How to express yourself.
Sentiment (satisfied/dissatisfied)? Focus on finding the problem. Was the problem resolved during the call?
What products does he/she mention?
What competitors does he mention?
Reason for rejecting the operator's offer.
Doesn't want to leave?
Did he follow the call-script?
Did the customer understand what they were saying?
Reason for declining the operator's offer?
Did he attempt to cross-sell?
Did he or she waste time?
Does he have a negative impact on customers?
How is the operator performing relative to others?
Is he improving?
What types of calls are giving him problems?
The software automatically detects everything. Your people no longer have to conduct interrogations. Instead of having a percentage of calls, you have an overview of everything that's going on in the call center.
Finally, we'd like to thank our partners IXPERTA and Atos for co-organizing this conference. We hope everyone enjoyed the conference and we will see you at the next one!
SentiSquare is a technology company that deals with customer-generated text analysis. As one of the few companies uses artificial intelligence based on principles of distribution semantics, which provides many competitive advantages, such as language independence. The company was founded in 2014 as a spin-off by team of researchers at the Faculty of Applied Sciences of the University of West Bohemia in Pilsen. SentiSquare currently supplies technology to the contact centers of large companies such as T-Mobile, E.ON or Albert.
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