Created
May 19, 2022 04:47
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| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| import matplotlib.ticker as ticker | |
| from src.models.coupon_distribution import * | |
| # Initialize CouponDistribution object and load data | |
| coupon_dist = CouponDistribution() | |
| coupon_dist.load_data( | |
| customer_data_path="./data/external/customers.csv", | |
| segment_prob_data_path="./data/external/visit_probability.csv") | |
| dict_dm_cost = {"dm1": 0.0, "dm2": 10.0, "dm3": 20.0} | |
| min_dist_ratio = 0.1 | |
| unit_sales = 30.0 | |
| # Run optimization | |
| coupon_dist.run_optimizer( | |
| dict_dm_cost=dict_dm_cost, min_dist_ratio=min_dist_ratio, | |
| unit_sales=unit_sales, max_budget="optimize") | |
| # Print result KPIs | |
| print(f"Budget: {coupon_dist.max_budget:.2f} USD") | |
| print(f"Profit Increase: {coupon_dist.inc_profit:.2f} USD") | |
| print(f"ROI: {coupon_dist.inc_profit/coupon_dist.max_budget:.2%}") | |
| # Budget: 18895.50 USD | |
| # Profit Increase: 406.50 USD | |
| # ROI: 2.15% | |
| # Print result KPIs if unit_sales = 40 | |
| coupon_dist.run_optimizer( | |
| dict_dm_cost=dict_dm_cost, min_dist_ratio=min_dist_ratio, | |
| unit_sales=40, max_budget="optimize") | |
| print(f"Budget: {coupon_dist.max_budget:.2f} USD") | |
| print(f"Profit Increase: {coupon_dist.inc_profit:.2f} USD") | |
| print(f"ROI: {coupon_dist.inc_profit/coupon_dist.max_budget:.2%}") | |
| # Budget: 45719.50 USD | |
| # Profit Increase: 11460.50 USD | |
| # ROI: 25.07% | |
| # Show result dataframe | |
| coupon_dist.df_seg_send_prob | |
| # Visualize result | |
| coupon_dist.visualize_optimized_results() |
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