Analysis 5 Telecommunications Company

1. Analysis 5 Telecommunications Company

Faculty of Computer science
Data science and business analytics
Business Analytics
Analysis 5 Telecommunications
Company
Realized by Otrubyannikova Darya, Lyscova Elisaveta, Valami Benjamin, Kirdyashev Evgeniy
BDSBA-223
Moscow 2025

2. Data exploration

Faculty of Computer science
Data science and business analytics
Business Analytics
Data exploration
Key observation:
Closely equal distribution by gender of clients
Most clients have up to 20 months of experience
Contracts are most often monthly
Task 1
2

3. Key Patterns and Trends

Faculty of Computer science
Data science and business analytics
Business Analytics
Key Patterns and Trends
Key patterns:
Fiber optic, short contracts and active additional services (Streaming,
TechSupport) lead to revenue growth
Monthly contract is strongly associated with high churn
Regression and Random Forest confirm that customer behavior and service mix
strongly influence revenue
Task 1
3

4. Hypothesis 1

Faculty of Computer science
Data science and business analytics
Business Analytics
Hypothesis 1
Improving retention of short-term customers through personalized offers.
Description: Offer bonus packages (e.g. free access to StreamingTV or discount on
the first year) to customers with less than 6 months of service to increase loyalty
and reduce churn.
Insight: High churn rate (around 0.5) for new customers indicates the need for early
engagement.
Task 2
4

5. Hypothesis 2

Faculty of Computer science
Data science and business analytics
Business Analytics
Hypothesis 2
Increase the share of fiber customers through targeted promotions.
Description: Run campaigns for customers with InternetService_DSL or without
internet, providing for the transition to fiber with bonuses (e.g. free month of
StreamingTV) to increase revenue and share of the high-income segment.
Insight: High coefficient (24.89) and slope (0.62) Fiber shows potential for growth
growth.
Task 2
5

6. Hypothesis 3

Faculty of Computer science
Data science and business analytics
Business Analytics
Hypothesis 3
Digitalization of customer experience and automation of payments to increase
satisfaction and efficiency.
Description: Simplify customer experience through digital platforms (mobile app,
online panel) and stimulate the transition to automatic payments (Credit card
(automatic)) with bonuses to increase TotalCharges and reduce operational costs.
Insight: The positive coefficient of PaymentMethod_Electronic check (0.0157) and
Credit card (automatic) (0.0077) hints at the potential of automation. The trend
towards digitalization in 2025 supports this idea, and the current share of
PaperlessBilling can be increased.
Task 2
6

7. Hypothesis 4

Faculty of Computer science
Data science and business analytics
Business Analytics
Hypothesis 4
Expand sales of additional security and protection services through personalized
offers to increase revenue.
Description: Implement cross-selling programs by offering customers with active
internet (InternetService_DSL or Fiber optic) additional services such as
OnlineSecurity, OnlineBackup and DeviceProtection with bonuses for combining to
increase MonthlyCharges and TotalCharges.
The low usage rate of these services (36.6%-44%) with positive coefficients (5.03
for OnlineSecurity, 4.95 for OnlineBackup, 5.01 for DeviceProtection) shows that
there is potential for revenue growth.
These services add value to customers with internet, as evidenced by their
contribution to MonthlyCharges.
Task 2
7

8. Для метрик

Faculty of Computer science
Data science and business analytics
Для метрик
Business Analytics
Task 3
8

9. Telecom in 15 years: key trends and development scenarios

Faculty of Computer science
Data science and business analytics
Business Analytics
Telecom in 15 years: key trends and
development scenarios
Task 4
9