5.3 Churn, duration and price
The final step in the data exploration consists in analysing the relationship between the Monthly_Charges
, Churn_Label
and Tenure_Months
variables as they play an important role in the modelling strategy we adopt to estimate customer value.
Looking at figure 5.4, monthly charges seem to be higher for churners than for retained customers as the density is more right-oriented. High fees might be a driver of customer churn.
Besides, the low p value related to the Anova test between CLTV
and Churn_Label
indicates that customer lifetime value is statistically different between churner and retained clients.
F statistic | Df1 | Df2 | p-value | |
---|---|---|---|---|
Churn_Label | 271.58 | 1 | 7030 | 6.8e-60 |
The following histograms are interesting to the extent that the distribution of Tenure_Months
depends on the churn status. From figure 5.5, one can note an inflation of low and high values for retained customers. The distribution appears to be more homogeneous for retained clients than for churners. These lasts’ tenure months distribution is decreasing and looks like a Poisson distribution with an inflation of low values.
Eventually, figure 5.6 depicts the average monthly charges per number of months in the portfolio. One can notice an increasing evolution between the average monthly fees and the number of months. In other words, it might be assumed that customers with longer lifetimes bring in more money to the firm.