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.

© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.

© 2025 Perlon AI Ltd (DBA as Perlon Labs). All rights reserved.