segment_expectation_calculator.py

import pandas as pd

# Example historical data for segments
historical_data = {
    'Customer Segment': ['Consumer', 'Corporate', 'Home Office'],
    'Historical Frequency': [5000, 3000, 2000],
    'Benchmark Percentage': [40, 35, 25],  # Market research
    'Business Goal Percentage': [50, 30, 20],  # Strategic goals
}

# Current total customer frequency
current_total = 10000

# Create a DataFrame
df = pd.DataFrame(historical_data)

# Historical-based expected values
df['Historical Expected'] = (df['Historical Frequency'] / df['Historical Frequency'].sum()) * current_total

# Market research-based expected values
df['Market Research Expected'] = (df['Benchmark Percentage'] / 100) * current_total

# Business goals-based expected values
df['Business Goals Expected'] = (df['Business Goal Percentage'] / 100) * current_total

# Display the results
print(df[['Customer Segment', 'Historical Expected', 'Market Research Expected', 'Business Goals Expected']])