┌─────────────────────────────────────────────────────────────────────────────┐
│                    DIGITAL BANKING CUSTOMER JOURNEY                       │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │    AWARENESS      │    CONSIDERATION    │    ACQUISITION            │   │
│  │  (Discover the    │  (Research and     │  (Open account,           │   │
│  │   bank)           │   compare)          │   apply)                  │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │    ONBOARDING     │    USAGE           │    RETENTION               │   │
│  │  (Welcome, setup, │  (Daily banking,   │  (Loyalty, advocacy,      │   │
│  │   first deposit)  │   transactions)    │   cross-sell)              │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │    ADVOCACY        │    DEPARTURE                                    │   │
│  │  (Recommend,       │  (Account closure,                             │   │
│  │   refer)           │   churn)                                       │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                         DESIGN THINKING PROCESS                           │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐   │
│  │   EMPATHISE │    │   DEFINE    │    │   IDEATE    │    │   PROTOTYPE │   │
│  │  (Understand │ -> │  (Define the│ -> │  (Generate  │ -> │  (Create    │   │
│  │   users)     │    │   problem)  │    │   solutions)│    │   solutions)│   │
│  └─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘   │
│                                                                             │
│                              ┌─────────────┐                              │
│                              │   TEST      │                              │
│                              │  (Test and  │                              │
│                              │   iterate)  │                              │
│                              └─────────────┘                              │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 1, LESSON 3: CUSTOMER EXPERIENCE AND JOURNEY MAPPING
# ===================================================================

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("CUSTOMER EXPERIENCE AND JOURNEY MAPPING")
print("="*70)

# ----------------------------------------------------------------
# PART A: CUSTOMER JOURNEY MAP
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Customer Journey Map")
print("-"*60)

# Define journey stages
stages = ['Awareness', 'Consideration', 'Acquisition', 'Onboarding', 
          'Usage', 'Retention', 'Advocacy', 'Departure']

# Define touchpoints for each stage
touchpoints = {
    'Awareness': ['Social Media Ads', 'Google Search', 'Word of Mouth', 'Articles'],
    'Consideration': ['Website', 'Reviews', 'Comparisons', 'Branch Visit'],
    'Acquisition': ['Online Application', 'KYC Process', 'Email Confirmation', 'Verification'],
    'Onboarding': ['Welcome Email', 'App Download', 'First Deposit', 'Card Activation'],
    'Usage': ['Mobile App', 'Online Banking', 'Payments', 'Transfers'],
    'Retention': ['Personalised Offers', 'Rewards', 'Customer Service', 'Newsletters'],
    'Advocacy': ['Referral Program', 'Reviews', 'Social Sharing', 'Testimonials'],
    'Departure': ['Account Closure', 'Feedback Survey', 'Final Communications']
}

# Define emotions for each stage (scale -2 to +2)
emotions = {
    'Awareness': 1,
    'Consideration': 0,
    'Acquisition': -1,
    'Onboarding': 0,
    'Usage': 2,
    'Retention': 1,
    'Advocacy': 2,
    'Departure': -2
}

# Define pain points for each stage
pain_points = {
    'Awareness': ['Not finding relevant information', 'Confusing messaging'],
    'Consideration': ['Overwhelming choices', 'Lack of transparency'],
    'Acquisition': ['Lengthy application', 'Complex KYC'],
    'Onboarding': ['Delayed activation', 'Confusing interface'],
    'Usage': ['Slow transactions', 'App crashes'],
    'Retention': ['Generic offers', 'Poor customer service'],
    'Advocacy': ['No referral incentives', 'Limited sharing options'],
    'Departure': ['Difficult closure process', 'Lack of feedback channels']
}

# Create journey map DataFrame
journey_data = []
for stage in stages:
    journey_data.append({
        'Stage': stage,
        'Touchpoints': ', '.join(touchpoints[stage]),
        'Emotion': emotions[stage],
        'Pain Points': ', '.join(pain_points[stage]),
        'Opportunities': f'Improve {stage.lower()} experience'
    })

journey_df = pd.DataFrame(journey_data)
print("Customer Journey Map:")
print(journey_df.to_string(index=False))

# ----------------------------------------------------------------
# PART B: EMOTIONAL JOURNEY VISUALISATION
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: Emotional Journey Visualisation")
print("-"*60)

# Plot emotional journey
fig, ax = plt.subplots(figsize=(12, 6))

# Create color map for emotions
colors = ['red' if e < 0 else 'green' if e > 0 else 'gray' for e in emotions.values()]

bars = ax.bar(emotions.keys(), emotions.values(), color=colors, alpha=0.7)
ax.axhline(y=0, color='black', linestyle='-', alpha=0.3)
ax.set_ylabel('Emotional Score')
ax.set_title('Customer Emotional Journey')
ax.grid(True, alpha=0.3)

# Add value labels on bars
for bar, value in zip(bars, emotions.values()):
    ax.text(bar.get_x() + bar.get_width()/2, value + (0.1 if value >= 0 else -0.3), 
            str(value), ha='center', va='bottom' if value >= 0 else 'top', fontweight='bold')

plt.tight_layout()
plt.savefig('emotional_journey.png', dpi=300, bbox_inches='tight')
plt.show()
print("Emotional journey visualisation saved as 'emotional_journey.png'")

# ----------------------------------------------------------------
# PART C: CX METRICS DASHBOARD
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: CX Metrics Dashboard")
print("-"*60)

# Define CX metrics
cx_metrics = {
    'NPS': {'Value': 45, 'Target': 55, 'Status': 'On Track'},
    'CSAT': {'Value': 82, 'Target': 85, 'Status': 'On Track'},
    'CES': {'Value': 2.3, 'Target': 2.0, 'Status': 'Needs Improvement'},
    'Churn Rate': {'Value': 8, 'Target': 5, 'Status': 'Needs Improvement'},
    'CLV': {'Value': 2500, 'Target': 3000, 'Status': 'On Track'},
    'FCR': {'Value': 78, 'Target': 85, 'Status': 'On Track'}
}

# Create DataFrame
cx_df = pd.DataFrame(cx_metrics).T
print("CX Metrics Dashboard:")
print(cx_df.to_string())

# ----------------------------------------------------------------
# PART D: NPS DISTRIBUTION
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: NPS Distribution")
print("-"*60)

# Simulate NPS survey responses
np.random.seed(42)
n_responses = 1000
responses = np.random.choice([-1, 0, 1], n_responses, p=[0.2, 0.3, 0.5])
# 0-6 = Detractors, 7-8 = Passives, 9-10 = Promoters
# Simplified: -1 = Detractor, 0 = Passive, 1 = Promoter

detractors = sum(responses == -1)
passives = sum(responses == 0)
promoters = sum(responses == 1)

nps = (promoters - detractors) / n_responses * 100

print(f"NPS Results:")
print(f"  Promoters: {promoters} ({promoters/n_responses*100:.1f}%)")
print(f"  Passives: {passives} ({passives/n_responses*100:.1f}%)")
print(f"  Detractors: {detractors} ({detractors/n_responses*100:.1f}%)")
print(f"  NPS: {nps:.1f}")

# Visualise NPS distribution
fig, ax = plt.subplots(figsize=(10, 6))
categories = ['Detractors', 'Passives', 'Promoters']
counts = [detractors, passives, promoters]
colors = ['red', 'gray', 'green']

bars = ax.bar(categories, counts, color=colors, alpha=0.7)
ax.set_ylabel('Number of Responses')
ax.set_title(f'NPS Distribution (NPS = {nps:.1f})')
for bar, count in zip(bars, counts):
    ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 10, 
            str(count), ha='center', va='bottom', fontweight='bold')
ax.axhline(y=n_responses/3, color='black', linestyle='--', alpha=0.3, label='Average')
ax.legend()
ax.grid(True, alpha=0.3)

plt.tight_layout()
plt.savefig('nps_distribution.png', dpi=300, bbox_inches='tight')
plt.show()
print("NPS distribution visualisation saved as 'nps_distribution.png'")

# ----------------------------------------------------------------
# PART E: CUSTOMER PERSONA TEMPLATE
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART E: Customer Persona Template")
print("-"*60)

persona_template = """
--- CUSTOMER PERSONA ---

NAME: ________________________________

DEMOGRAPHICS:
- Age: _______________
- Occupation: _______________
- Location: _______________
- Income: _______________

BEHAVIOUR:
- Banking Habits: _______________
- Digital Literacy: _______________
- Financial Goals: _______________

PAIN POINTS:
1. ________________________________
2. ________________________________
3. ________________________________

GOALS AND NEEDS:
1. ________________________________
2. ________________________________
3. ________________________________

PREFERENCES:
- Communication Channels: _______________
- Banking Channels: _______________
- Product Interests: _______________

JOURNEY:
- Awareness: _______________
- Consideration: _______________
- Acquisition: _______________
- Usage: _______________
- Retention: _______________
"""

print("Customer Persona Template:")
print(persona_template)

# Example persona
example_persona = """
--- EXAMPLE PERSONA ---

NAME: Sarah Chen

DEMOGRAPHICS:
- Age: 28
- Occupation: Marketing Manager
- Location: San Francisco
- Income: $85,000

BEHAVIOUR:
- Banking Habits: Mobile-first, uses banking app daily
- Digital Literacy: High, tech-savvy
- Financial Goals: Save for a house, invest for retirement

PAIN POINTS:
1. High fees on traditional accounts
2. Complex and confusing products
3. Slow response times for customer service

GOALS AND NEEDS:
1. Simple, transparent banking
2. Low fees and competitive rates
3. Easy to use mobile app
4. Financial guidance and insights

PREFERENCES:
- Communication Channels: Push notifications, email
- Banking Channels: Mobile app, online banking
- Product Interests: Savings accounts, investment options, budgeting tools

JOURNEY:
- Awareness: Heard about bank through social media
- Consideration: Compared with other digital banks
- Acquisition: Opened account online in 10 minutes
- Usage: Uses app for daily transactions and savings
- Retention: Appreciates personalised offers and insights
"""

print("\nExample Persona:")
print(example_persona)

# ----------------------------------------------------------------
# PART F: CX IMPROVEMENT PRIORITIES
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART F: CX Improvement Priorities")
print("-"*60)

cx_priorities = pd.DataFrame({
    'Priority': ['High', 'High', 'Medium', 'Medium', 'Low'],
    'Area': [
        'Digital Onboarding',
        'Mobile App Performance',
        'Personalisation',
        'Customer Service Response Time',
        'Branch Experience'
    ],
    'Impact (1-10)': [9, 8, 7, 7, 5],
    'Effort (1-10)': [6, 4, 7, 5, 8],
    'Action': [
        'Simplify KYC, reduce time to under 5 minutes',
        'Optimise app performance, reduce crash rate',
        'Implement ML for personalised offers',
        'Implement AI chatbot for 24/7 support',
        'Integrate digital and branch experiences'
    ]
})

print("CX Improvement Priorities:")
print(cx_priorities.to_string(index=False))

# ----------------------------------------------------------------
# PART G: SUMMARY AND RECOMMENDATIONS
# ----------------------------------------------------------------

print("\n" + "="*70)
print("PART G: Summary and Recommendations")
print("="*70)

print("""
Customer Experience – Key Takeaways:

1. CX is a critical competitive differentiator in digital banking.
2. Journey mapping helps identify pain points and opportunities.
3. Design thinking provides a framework for improving CX.
4. Personalisation enhances customer engagement and loyalty.
5. Key metrics: NPS, CSAT, CES, Churn Rate, CLV.
6. Customer personas help design targeted experiences.
7. Continuous improvement is essential for CX excellence.

Recommendations:
  - Map your customer journey and identify pain points.
  - Create detailed customer personas.
  - Implement personalisation capabilities.
  - Measure CX metrics regularly and act on insights.
  - Invest in design thinking capabilities.
  - Continuously gather and act on customer feedback.
""")

print("="*70)
print("END OF LESSON 3 – MODULE 1")
print("="*70)