In today's fast-paced world, delivering exceptional customer experiences is key to standing out in the telecommunications industry. By leveraging advanced AI models, telcos can now track customer interactions across *all touchpoints*—from calls and chats to social media and beyond. But it doesn’t stop there. AI can predict the precise actions needed to elevate customer satisfaction, ensuring every interaction is personalized, seamless, and impactful. Imagine a world where every customer feels valued and understood. That’s the power of AI-driven customer experience excellence.

1. Company Internal
1
Customer Happiness Score
Data Science & AI
Yettel Serbia:
Revolutionizing Telco Customer
Experience with AI
November 2025

2. Company Internal
Customer Care Challenges
AI as a Strategic
Enabler
o Reduces operational cost
o Improves customer satisfaction
(NPS/CSAT)
o Shortens resolution times
o Creates personalized experiences
o Unlocks proactive & predictive care
Complex Service Portfolio
(Mobile, Broadband, TV,
Bank..)
Customers expect a single point of contact
regardless of service. Agents must understand
many technologies (fiber optics, RF, DOCSIS, Wi-
Fi, VoIP).
Slow Insights Extraction
Time consuming insight generation from BSS (Billing, CRM,
Customer data) and OSS (Network configuration, provisioning,
quality metrics). Often 10–30 separate systems from different
vendors
Growing Expectation
Customers now expect telco support to
work like modern digial native apps .
Younger customers rarely want to call, and
prefer messaging apps, In-app support or
automated troubleshooting wizards
High call center volumes
Many issues are repetitive: SIM
activation, APN settings, router reboot,
billing questions. Network outages
create sudden spikes

3. Company Internal
Customer Care - Quality management and customer
satisfaction based on the sampling methodology
Next Best Action
Family of models predicting which care
activity will improve customers’
experience
Customer Happiness
Score
More advanced than CSAT or NPS –
estimates general customer happiness
and provides how customer experience
could be improved
Y.Buddy
Chatbots – both internal and external
leping customers and our agents to
optain complex information
Sonar
Internally developed ASR and text
processing tool helping to extract
insights from interactions with customer
across multiple touchpoints

4. Company Internal
SONAR – AI Automatic Speech Recognition
Audio
Two different CC
platform orovide two
different call recording
types with different
sampling rate and
channel quality
ASR
Internal data labeling.
Call augmentation
plays crucial roll.
Performance
improvement.
WER better compared
to some payed and
free off-shelf
solutions.
Text
Processing
Data labeling
performed with LLM,
and classification with
SLM – erformance
improvements.
Visualization
Different dashboards
must provide detailed
insights.
Anomaly detection will
help focus on
important changes.
E2E platform for ASR, text processing
and visualiyation

5. Company Internal
Y.Buddy – Chatbots
Customer Facing
o Multi-agent chatbots
o Built with both internally developed
LLM/SLM and vendor provided
models
o Help customer troubleshoot issues
and explore complex telco portfolio
o Provide dynamic personalized
information
o Perform provisioning
o Easy scalable chatbot platform
Internal
o Help agents navigate through
detailed internal procedures
o Lower time required to provide the
answer to customer
o Analyze information from multiple
systems
o Provide next best action

6. Company Internal
Customer Happiness Score
Profiling
Different customer profiles will be
influenced with differently by the same
events
BSS
Analyzing billing, tariff plans, voice and
data consumption estimate customer
satisfaction
Customer interactions
Analyze all written and verbal
interactions with customer evaluate
topics and sentiment
Service
Provide score estimation per customer
based on service quality

7. Company Internal
Next Best Action
AI Models
Churn model,
Customer happiness,
Sonar and many
other models provide
insights
Real-time
All systems must be
capable to perform
inference and
provide insights in
real-time
Presentation
AI guided support
must be presented in
structured and easy
to read form
Action
Process must suggest optimal
care or troubleshoot actions
across different channels. Every
actions must be recorded and
used as feedback loop for further
model improvments

8. Company Internal
8
Thank you!
Djordje Hirs