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RFM分析
本主题将演示如何设置一个功能板,以允许您按回访间隔、频度和货币排名对客户进行分段。 RFM分析是一种营销技术,它考虑客户行为,帮助您确定外联的分段。 它包含三个方面:
- 客户最近从您的商店购买的回访间隔
- 他们向您购买的频率
- 客户花费的金额
只有在新架构上具有Adobe Commerce Intelligence Pro计划时(例如,如果在Data Warehouse Views菜单下具有Manage Data选项),才能配置RFM分析。 可从 Manage Data > Data Warehouse 页面创建这些列。 下面提供了详细说明。
快速入门
您需要首先上传一个文件,其中只包含值为1的主键。 这允许为分析创建一些必要的计算列。
您可以使用此文章和下面的图像来格式化您的文件。
计算列
如果您的企业允许客户订购,则需作进一步的区分。 如果是,则可以忽略customer_entity表的所有步骤。 如果不允许来宾订单,请忽略sales_flat_order表的所有步骤。
要创建的列
-
Sales_flat_order/customer_entity表 -
Customer's last order date -
Column type:
Many to one > Max -
Pat:
sales_flat_order.customer_id > customer_entity.entity_id -
已选择column:
created_at -
Filter:
Orders we count -
自客户上次订购日期起 秒- Column type: - “同一张表>年龄
-
已选择column:
Customer's last order date -
(输入)计数引用
-
Column type:
Same table > Calculation -
输入:entity_id -
Calculation:
**case when A is null then null else 1 end** -
数据类型:Integer -
计数引用 表(这是您上传的编号为“1”的文件)
-
客户数量
-
Column type:
Many to One > Count Distinct -
Path:
ales_flat_order.(input) reference > Count reference.Primary Key或customer_entity.(input)reference > Count Reference。Primary Key -
已选择column:
sales_flat_order.customer_email或customer_entity.entity_id -
Customer_entity 表
-
客户数量
-
Column type:
One to Many > JOINED_COLUMN -
Path:
customer_entity。(输入)参考>客户集中。Primary Key -
已选择column:
Number of customers -
(输入)
Ranking by customer lifetime revenue -
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Customer's lifetime revenue -
按客户存留期收入排名
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer lifetime revenue,Number of customers -
Calculation:
case when A is null then null else (B-(A-1)) end -
数据类型:Integer -
客户的货币得分(以百分位数为单位)
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer lifetime revenue,Number of customers -
Calculation:
Case when round((B-A+1)*100/B,0) <= 20 then 5 when round((B-A+1)*100/B,0) <= 40 then 4 when round((B-A+1)*100/B,0) <= 60 then 3 when round((B-A+1)*100/B,0) <= 80 then 2 when round((B-A+1)*100/B,0) <= 100 then 1 else 0 end -
数据类型:Integer -
(输入)按客户存留期订单数排名
-
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Customer's lifetime number of orders -
按客户存留期订单数排名
-
列类型: – “相同表>计算” -
Inputs: - (输入)按客户存留期订单数 排名,客户数
-
Calculation: - 当A为null时为null,否则(B-(A-1))结束
-
Datatype: — 整数
-
客户的频率得分(按百分位数)
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer lifetime number of orders,Number of customers -
Calculation:
Case when round((B-A+1)*100/B,0) <= 20 then 5 when round((B-A+1)*100/B,0) <= 40 then 4 when round((B-A+1)*100/B,0) <= 60 then 3 when round((B-A+1)*100/B,0) <= 80 then 2 when round((B-A+1)*100/B,0) <= 100 then 1 else 0 end -
数据类型:Integer -
自客户上次订购日期以来按秒排名
-
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Seconds since customer's last order date -
客户的回访间隔分数(按百分位数)
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer lifetime number of orders,Number of customers -
Calculation:
Case when (A * 100/B,0) <= 20 then 5 when (A * 100/B,0) <= 40 then 4 when (A * 100/B,0) <= 60 then 3 when (A * 100/B,0) <= 80 then 2 when (A * 100/B,0) <= 100 then 1 else 0 end -
数据类型:Integer -
客户的回访间隔分数(按百分位数)
-
Column type:
Same table > Calculation -
Inputs:
Customer's recency score (by percentiles),Customer's frequency score (by percentiles),Customer's monetary score (by percentiles) -
Calculation:
case when (A IS NULL or B IS NULL or C IS NULL) then null else concat(A,B,C) end -
数据类型: String -
引用计数 表
-
Number of customers:
(RFM > 0) -
Column type:
Many to One > Count Distinct -
Path:
sales_flat_order.(input) reference > Customer Concentration. Primary Key或customer_entity.(input)reference > Customer Concentration.Primary Key -
已选择column:
sales_flat_order.customer_email或customer_entity.entity_id -
Filter:
Customer's RFM score (by percentile)不等于000 -
Customer_entity 表
-
Number of customers:
(RFM > 0) -
Column type:
One to Many > JOINED_COLUMN -
Path:
customer_entity.(input) reference > Customer Concentration.Primary Key -
已选择column: -
Number of customers -
客户的回访间隔分数
(R+F+M) -
Column type:
Same table > Calculation -
Inputs: -
Customer's recency score (by percentiles),Customer's frequency score (by percentiles),Customer's monetary score (by percentiles) -
Calculation:
case when (A IS NULL or B IS NULL or C IS NULL) then null else A+B+C end -
数据类型:Integer -
(输入)按客户的整体RFM得分排名
-
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Customer's recency score (R+F+M) -
Filter:
Customer's RFM score (by percentile)不等于000 -
按客户的整体RFM分数排名
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer's overall RFM score,Number of customers (RFM > 0) -
Calculation:
case when A is null then null else (B-(A-1)) end -
数据类型:Integer -
客户的RFM组
-
Column type:
Same table > Calculation -
Inputs:
(input) Ranking by customer lifetime revenue,Number of customers -
Calculation:
Case when round(A * 100/B,0) <= 20 then '5. copper' when round(A * 100/B,0) <= 40 then '4. bronze' when round(A * 100/B,0) <= 60 then '3. silver' when round(A * 100/B,0)<= 80 then '2. gold' else '1. Platinum' end -
数据类型:Integer
量度
无新量度!
报告
-
按RFM分组 客户
-
量度
A:New customers -
Metric:
New customers -
Filter:
Customer's RFM score (by percentiles) Not Equal to 000 -
Time period:
All time -
Interval:None -
隐藏图表
-
Group by:
Customer's RFM group -
分组依据:Email -
Chart type:Table -
有五个回访间隔分数的客户
-
量度
A:New customers -
Metric:
New customers -
Filter:
Customer's recency score (by percentiles) Equal to 5 -
Time period:
All time -
Interval:None -
Chart Type:Scalar -
隐藏图表
-
分组依据:Email -
Group by:
Customer's RFM score (R+F+M) -
Chart type:Table -
具有一个回访间隔分数的客户
-
量度
A:New customers -
Metric:
New customers -
Filter:
Customer's recency score (by percentiles) Equal to 1 -
Time period:
All time -
Interval:None -
Chart Type:Scalar -
隐藏图表
-
分组依据:Email -
Group by:
Customer's RFM score (R+F+M) -
Chart type:Table
在编译所有报告后,您可以根据需要将报告组织在功能板上。 结果可能类似于上面的示例仪表板,但生成的三个表只是您可以执行的客户分段类型的示例。