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RFM 模型是衡量客户价值和客户创利能力的重要工具和手段；
应用场景：客户关系管理(CRM) 分析模型；

指标：

• 最近一次消费 (Recency)
• 消费频率 (Frequency)
• 消费金额 (Monetary)

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22.2 案例

import pandas as pd
import numpy as np
import time

data = pd.read_csv('RFM_TRAD_FLOW.csv',encoding='gbk')
# print(data)

# print(data.head())
data['time']=data['time'].map(lambda x:time.mktime(time.strptime(x,'%d%b%y:%H:%M:%S')))
# print(data)、
group_obj = data.groupby(['cumid','type'])
R = group_obj[['time']].max()


#转透视表
r_trans = pd.pivot_table(R,index='cumid',columns='type',values='time')
# print(r_trans)

r_trans[['Special_offer','returned_goods']] = r_trans[['Special_offer','returned_goods']].apply(lambda x:x.replace(np.nan,min(x)),axis=0)
# print(r_trans)

r_trans['r_max'] = r_trans[['Normal', 'Presented','Special_offer']].apply(lambda x:max(x),axis=1)
# print(r_trans)


# F

F = group_obj[['transID']].count()
print(F)

f_trans = pd.pivot_table(F,index='cumid',columns='type',values='transID')
# print(f_trans)
#
f_trans[['Special_offer','returned_goods']] = f_trans[['Special_offer','returned_goods']].fillna(0)
# print(f_trans)

f_trans['returned_goods'] = f_trans['returned_goods'].map(lambda x:-x)
# print(f_trans)
f_trans['f_total'] =f_trans.apply(lambda x:sum(x),axis=1)
print(f_trans)



# M

M = group_obj[['amount']].sum()

m_trans = pd.pivot_table(M,index='cumid',columns='type',values='amount')
# print(f_trans)
#
m_trans[['Special_offer','returned_goods']] = f_trans[['Special_offer','returned_goods']].fillna(0)
# print(f_trans)
# print(f_trans)
m_trans['m_total'] =m_trans.apply(lambda x:sum(x),axis=1)
print(m_trans)

### 合并
RFM = pd.concat([r_trans['r_max'],f_trans['f_total'],m_trans['m_total']],axis=1)
print('##################')
print(RFM)

RFM['r_score' ]= pd.cut(RFM.r_max,3,labels=[0,1,2])
RFM['f_score' ]= pd.cut(RFM.f_total,3,labels=[0,1,2])
RFM['m_score'] = pd.cut(RFM.m_total,3,labels=[0,1,2])

print(RFM)

def rfm_label(x,y,z):
    if x==2 and y==2 and z==2:
        return '重要价值客户'
    elif x==2 and (y in [0,1]) and z ==2:
        return '重要发展客户'
    elif (x in [0,1]) and y==2 and z==2:
        return '重要保持客户'
    elif (x in [0,1] ) and (y in [0,1]) and z ==2:
        return '重要挽留客户'
    elif x==2 and y==2 and (z in [0,1]):
        return '一般价值客户'
    elif x ==2 and (y in [0,1] and (z in [0,1])):
        return '一般发展客户'
    elif (x in [0,1]) and y==2 and (z in [0,1]):
        return '一般保持客户'
    elif (x in [0,1]) and (y in [0,1]) and (z in (0,1)):
        return '一般挽留客户'


RFM['标签']=RFM[[ 'r_score', 'f_score', 'm_score']].apply(lambda x:rfm_label(x[0],x[1],x[2]),axis=1)
print(RFM)

#选择满足条件的行
# pd.read_sql_query()
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