Q: How to estimate customer lifetime value in daily increments using BG/Gamma Gamma Models (spend model) in Python? I am calculating customer lifetime value and this estimation is performed in monthly increments. I would like to calculate CLV in increments of 7 days, 14 days etc.. using the model parameters (see below), do i convert days into month, for i.e., 7 days = 0.23 months ...
print(ggf.customer_lifetime_value(
    bgf, #the model to use to predict the number of future transactions
    summary_with_money_value['frequency'],
    summary_with_money_value['recency'],
    summary_with_money_value['T'],
    summary_with_money_value['monetary_value'],
    time=12, # months
    discount_rate=0.01 # monthly discount rate ~ 12.7% annually
).head(10))

I tried to convert days into months for 7 days, 14 days but I would like confirmation (peer) / fellow Data Scientists, ML experts to confirm/ not confirm.
