
Customer Service Analytics
Customer Service Analytics
DU Case study
100%
100%
Visibility on calls
Visibility on calls
23%
23%
Productivity increase
Productivity increase




Project Overview
Industry
Telecoms
AI Solution
Customer Service Analytics
Quick Brief
Du were looking to acheive full visibility on the operations of their call centres and retail stores by analysing the ongoing performance of customer service teams in both Arabic and English.
Customer Pain Points
No in-depth visibility or analytics
Underperformance going unoticed
Team productivity unoptimised
What We Delivered
We used computer vision and transcription analytics to give Du Telecoms extensive visibility into the performance of customer service operators and retail assistants.
End Results
Enhanced customer service
Managerial decision making enabled
New visibility on customer behaviour
Introduction
du is one of the two largest telecoms operators in the UAE. They operate a large call centre and numerous physical stores to manage the ongoing queries and requests of over 8 million customers.
They are the fastest growing telecoms company in the region and were looking for ways to maintain the high level of service they are known for as they continued to expand both within the UAE and to new markets.
Solution
Using the latest in computer vision emotion detection and Speech-to-Text transcription models, we were able to build a solution that could track the performance of team members and provide extensive product and customer feedback. The solution contains three core components:
Sentiment Analysis
Calls are recorded, transcribed using ASR and analysed with custom trained sentiment analysis models in both Arabic and English.
Facial Analysis
We use the latest computer vision models to track facial expression, and fatigue so that staff can have their performance mapped.
Screen Capture Analysis
From analysing the user’s screen, we are able to measure domain & IT system knowledge + gaps and system issues.

Result
A comprehensive understanding of all staff/customer engagements and the ability for team performance to be accurately monitored across the entire business.
Project Overview
Industry
Telecoms
AI Solution
Customer Service Analytics
Quick Brief
Du were looking to acheive full visibility on the operations of their call centres and retail stores by analysing the ongoing performance of customer service teams in both Arabic and English.
Customer Pain Points
No in-depth visibility or analytics
Underperformance going unoticed
Team productivity unoptimised
What We Delivered
We used computer vision and transcription analytics to give Du Telecoms extensive visibility into the performance of customer service operators and retail assistants.
End Results
Enhanced customer service
Managerial decision making enabled
New visibility on customer behaviour
Introduction
du is one of the two largest telecoms operators in the UAE. They operate a large call centre and numerous physical stores to manage the ongoing queries and requests of over 8 million customers.
They are the fastest growing telecoms company in the region and were looking for ways to maintain the high level of service they are known for as they continued to expand both within the UAE and to new markets.
Solution
Using the latest in computer vision emotion detection and Speech-to-Text transcription models, we were able to build a solution that could track the performance of team members and provide extensive product and customer feedback. The solution contains three core components:
Sentiment Analysis
Calls are recorded, transcribed using ASR and analysed with custom trained sentiment analysis models in both Arabic and English.
Facial Analysis
We use the latest computer vision models to track facial expression, and fatigue so that staff can have their performance mapped.
Screen Capture Analysis
From analysing the user’s screen, we are able to measure domain & IT system knowledge + gaps and system issues.

Result
A comprehensive understanding of all staff/customer engagements and the ability for team performance to be accurately monitored across the entire business.
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© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.
© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.
© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.
© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.
© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.