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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:

  1. 客戶最近從您的商店購買的造訪間隔
  2. 訪客向您購買的頻率
  3. 客戶花費的金額

RFM分析儀表板,顯示造訪間隔、頻率和貨幣值區段

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 Keycustomer_entity.(input)reference > Count ReferencePrimary Key

  • 已選取column: sales_flat_order.customer_emailcustomer_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 revenueNumber 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 revenueNumber 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 ordersNumber 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 ordersNumber 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 Keycustomer_entity.(input)reference > Customer Concentration.Primary Key

  • 已選取column: sales_flat_order.customer_emailcustomer_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 scoreNumber 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 revenueNumber 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

NOTE
使用的百分位數是客戶的偶數拆分(例如,20%區間會傳回1-5)。 如果您有自訂方式來權衡這些專案,請在提交票證時告知分析人員。

量度

沒有新量度!

NOTE
在建立新報表之前,請務必將所有新欄新增為量度的維度。

報表

  • 按RFM群組​ 客戶

  • 量度ANew 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ANew 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ANew 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。

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