-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathanalysis_summary.py
109 lines (90 loc) · 3.11 KB
/
analysis_summary.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
"""
IBM Telco Customer Churn Analysis - Executive Summary
"""
def print_section_header(title):
print("\n" + "="*50)
print(title)
print("="*50)
print_section_header("EXECUTIVE SUMMARY - TELCO CUSTOMER CHURN ANALYSIS")
print("""
Dataset Overview:
- Total Customers Analyzed: 7,043
- Overall Churn Rate: 26.54%
- Average Customer Age: 46.5 years
- Average Customer Lifetime Value: $4,400.30
""")
print_section_header("KEY FINDINGS")
print("""
1. Customer Demographics:
- Gender distribution is balanced (Male: 50.48%, Female: 49.52%)
- Age groups:
* Middle Age (31-45): 27.59%
* Senior (46-60): 27.10%
* Elderly (60+): 23.60%
* Young Adult (0-30): 21.71%
- Churned customers tend to be older (avg. 49.7 years)
2. Churn Predictors (by importance):
- Churn Score (0.576)
- Tenure in Months (0.110)
- Monthly Charge (0.093)
3. Service Analysis:
- Internet Type Churn Rates:
* Fiber Optic: 40.72% (Highest risk)
* Cable: 25.66%
* DSL: 18.58% (Lowest risk)
4. Top Churn Reasons:
- Competitor had better devices (16.75%)
- Competitor made better offer (16.64%)
- Attitude of support person (11.77%)
- Unknown reasons (6.96%)
- Competitor offered more data (6.26%)
5. Financial Impact:
- Churned customers have lower CLTV ($4,149 vs $4,491)
- Higher monthly charges correlate with increased churn risk
""")
print_section_header("MODEL PERFORMANCE")
print("""
Random Forest Classifier Results:
- Overall Accuracy: 92%
- Precision:
* Non-churn (0): 93%
* Churn (1): 90%
- Recall:
* Non-churn (0): 96%
* Churn (1): 81%
""")
print_section_header("RECOMMENDATIONS")
print("""
1. Service Improvement:
- Focus on Fiber Optic service quality due to high churn rate
- Review and enhance device offerings to compete with competitors
- Implement competitive pricing strategy
2. Customer Support:
- Enhance support staff training to improve customer interaction
- Implement regular customer satisfaction surveys
- Develop proactive support protocols for high-risk customers
3. Retention Strategy:
- Develop targeted retention programs for:
* Customers with high churn scores
* New customers (low tenure)
* Customers with high monthly charges
- Create competitive counter-offers for at-risk customers
4. Product Development:
- Enhance device offerings to match or exceed competitors
- Review and optimize data plans
- Consider bundled services with improved value proposition
5. Monitoring and Prevention:
- Implement early warning system based on churn score
- Regular competitive analysis of market offerings
- Monitor customer usage patterns for early churn indicators
""")
print_section_header("VISUALIZATION REFERENCE")
print("""
Generated visualizations are saved in the 'plots' directory:
1. churn_demographics.png - Customer demographic analysis
2. value_analysis.png - Customer value and financial metrics
3. service_analysis.png - Service usage patterns
4. churn_reasons.png - Top reasons for customer churn
5. correlation_matrix.png - Relationship between variables
6. feature_importance.png - Key predictors of churn
""")