Calculate RFM Score
Great work, you will now finish the job by assigning customers to three groups based on the MonetaryValue
percentiles and then calculate an RFM_Score
which is a sum of the R, F, and M values.
The datamart
has been loaded with the R and F values you have created in the previous exercise.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Create labels for
MonetaryValue
with an increasing range of 1 through 3. - Assign these labels to three equal percentile groups based on
MonetaryValue
. - Create new column
M
based on theMonetaryValue
percentile group. - Calculate
RFM_Score
based on the sum of R, F, and M column values.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create labels for MonetaryValue
m_labels = range(1, ____)
# Assign these labels to three equal percentile groups
m_groups = pd.qcut(datamart['MonetaryValue'], q=____, labels=____)
# Create new column M
datamart = datamart.assign(____=____)
# Calculate RFM_Score
datamart['RFM_Score'] = datamart[['R','F','M']].____(axis=____)
print(datamart['____'].head())