Churn prediction, price sensitivity and data analysis
client_data.csv
● id = client company identifier ● activity_new = category of the company’s activity ● channel_sales = code of the sales channel ● cons_12m = electricity consumption of the past 12 months ● cons_gas_12m = gas consumption of the past 12 months ● cons_last_month = electricity consumption of the last month ● date_activ = date of activation of the contract ● date_end = registered date of the end of the contract ● date_modif_prod = date of the last modification of the product ● date_renewal = date of the next contract renewal ● forecast_cons_12m = forecasted electricity consumption for next 12 months ● forecast_cons_year = forecasted electricity consumption for the next calendar year ● forecast_discount_energy = forecasted value of current discount ● forecast_meter_rent_12m = forecasted bill of meter rental for the next 2 months ● forecast_price_energy_off_peak = forecasted energy price for 1st period (off peak) ● forecast_price_energy_peak = forecasted energy price for 2nd period (peak) ● forecast_price_pow_off_peak = forecasted power price for 1st period (off peak) ● has_gas = indicated if client is also a gas client ● imp_cons = current paid consumption ● margin_gross_pow_ele = gross margin on power subscription ● margin_net_pow_ele = net margin on power subscription ● nb_prod_act = number of active products and services ● net_margin = total net margin ● num_years_antig = antiquity of the client (in number of years) ● origin_up = code of the electricity campaign the customer first subscribed to ● pow_max = subscribed power ● churn = has the client churned over the next 3 months
price_data.csv
● id = client company identifier ● price_date = reference date ● price_off_peak_var = price of energy for the 1st period (off peak) ● price_peak_var = price of energy for the 2nd period (peak) ● price_mid_peak_var = price of energy for the 3rd period (mid peak) ● price_off_peak_fix = price of power for the 1st period (off peak) ● price_peak_fix = price of power for the 2nd period (peak) ● price_mid_peak_fix = price of power for the 3rd period (mid peak)
Note: some fields are hashed text strings. This preserves the privacy of the original data but the commercial meaning is retained and so they may have predictive power