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RFM分析
本主題將示範如何設定儀表板,讓您依據客戶造訪間隔、頻率和貨幣排名來劃分客戶。 RFM分析是一種行銷技術,會考量客戶行為,協助您判斷外聯的分段。 它說明三個方面:
- 客戶最近從您的商店購買的造訪間隔
- 訪客向您購買的頻率
- 客戶花費的金額
只有在新架構上有Adobe Commerce Intelligence Pro計畫時(例如,如果在Data Warehouse Views功能表下有Manage Data選項),才能設定RFM分析。 可從 Manage Data > Data Warehouse 頁面建立這些資料行。 詳細指示如下。
快速入門
您必須先上傳只包含主索引鍵(值為1)的檔案。 這允許建立一些分析所需的計算欄。
您可以使用此文章及下方影像來格式化您的檔案。
計算欄
如果您的企業允許訪客訂購,則需作進一步的區分。 若是如此,您可以忽略customer_entity資料表的所有步驟。 如果不允許客體訂單,請忽略sales_flat_order資料表的所有步驟。
要建立的欄
-
Sales_flat_order/customer_entity資料表 -
Customer's last order date -
Column type:
Many to one > Max -
Pat:
sales_flat_order.customer_id > customer_entity.entity_id -
已選取column:
created_at -
Filter:
Orders we count -
自客戶上次訂購日期起 秒- Column type: - 「相同表格>年齡
-
已選取column:
Customer's last order date -
(輸入)計數參考
-
Column type:
Same table > Calculation -
輸入:entity_id -
Calculation:
**case when A is null then null else 1 end** -
資料型別:Integer -
計數參考 資料表(這是您以數字「1」上傳的檔案)
-
客戶數量
-
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 -
已選取column:
sales_flat_order.customer_email或customer_entity.entity_id -
Customer_entity 表格
-
客戶數量
-
Column type:
One to Many > JOINED_COLUMN -
Path:
customer_entity。(輸入)參考資料>客戶集中度。Primary Key -
已選取column:
Number of customers -
(輸入)
Ranking by customer lifetime revenue -
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Customer's lifetime revenue -
依客戶期限收入排名
-
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 -
資料型別:Integer -
客戶的貨幣分數(依百分位數)
-
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 -
資料型別:Integer -
(輸入)依客戶期限訂單數排名
-
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Customer's lifetime number of orders -
依客戶期限訂單數排名
-
欄型別: – “相同表格>計算” -
Inputs: - (輸入)依客戶期限訂單數 排名,客戶數
-
Calculation: - 當A為Null然後為Null時,否則(B-(A-1))結束
-
Datatype: — 整數
-
客戶的頻率分數(依百分位數)
-
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 -
資料型別:Integer -
自客戶上次訂購日期起的秒數排名
-
Column type:
Same table > Event Number -
Event owner:
(input) reference for count -
Event rank:
Seconds since customer's last order date -
客戶的造訪間隔分數(依百分位數)
-
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 -
資料型別:Integer -
客戶的造訪間隔分數(依百分位數)
-
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 -
資料型別: String -
計數參考 資料表
-
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 -
已選取column:
sales_flat_order.customer_email或customer_entity.entity_id -
Filter:
Customer's RFM score (by percentile)不等於000 -
Customer_entity 表格
-
Number of customers:
(RFM > 0) -
Column type:
One to Many > JOINED_COLUMN -
Path:
customer_entity.(input) reference > Customer Concentration.Primary Key -
已選取column: -
Number of customers -
客戶的造訪間隔分數
(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 -
資料型別:Integer -
(輸入)依客戶的整體RFM分數排名
-
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)不等於000 -
依客戶的整體RFM分數排名
-
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 -
資料型別:Integer -
客戶的RFM群組
-
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 -
資料型別:Integer
量度
沒有新量度!
報表
-
按RFM群組 客戶
-
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 -
隱藏圖表
-
Group by:
Customer's RFM group -
群組依據:Email -
Chart type:Table -
具有5個造訪間隔分數的客戶
-
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 -
隱藏圖表
-
群組依據:Email -
Group by:
Customer's RFM score (R+F+M) -
Chart type:Table -
具有一個造訪間隔分數的客戶
-
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 -
隱藏圖表
-
群組依據:Email -
Group by:
Customer's RFM score (R+F+M) -
Chart type:Table
編譯所有報表後,您可以視需要在控制面板上組織報表。 結果看起來可能像上面的範例儀表板,但三個產生的表格只是您可執行的客戶細分型別的範例。