CONTACT CENTER OPTIMIZATION
Artificial intelligence reads and evaluates all communication in the call center and analyzes the contact between the customer and the operator so that both parties are more satisfied at the end of the communication.
How it works
Before starting communication
AI is up and running and ready to instantly check 100% of sent emails, text messages, call transcripts and feedback.
During communication
Analysis and live feedback is ongoing: It evaluates grammar, formatting, greeting, empathy, etiquette…
After end of communication
The communication is available for analysis. Managers now have a perfect overview of the quality level of customer care and which operators need extra training.
Example from practice
Percentage of emails checked for Kiwi.com – 80,000+ incoming emails per month
Kiwi.com Challenge
On average, the quality control team was only able to evaluate 1% of all emails sent by KIWI.com operators to customers. The evaluation was almost random – there was no way to know which e-mails to focus on. The overall performance of the team of operators could also not be determined and monitored.
SentiSquare Solution
SentiSquare artificial intelligence has learned to evaluate emails based on grammar, empathy, format and greeting thanks to its natural language processing capability. It then joined the process via API and started evaluating the emails from operators in real time.
Kiwi.com results with SentiSquare
Since its deployment, SentiSquare artificial intelligence checks 100% of all emails sent. Thanks to periodic learning, it is improving all the time. KIWI.com managers now have a perfect overview of the quality level of customer care and which operators need extra training.
FREE solution and pilot project
Come with us to improve your customer care and innovate your business. We will prepare a solution for you free of charge. The pilot project could be up and running in as little as two weeks.
Contact
We don’t play games – we develop and sell only what we understand perfectly
References
Customer Feedback Analytics
Challenge: Measuring the causes of changes in customer satisfaction