store-customer-crm-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "aaa708b0",
   "metadata": {
    "papermill": {
     "duration": 0.020078,
     "end_time": "2024-09-20T15:34:58.843365",
     "exception": false,
     "start_time": "2024-09-20T15:34:58.823287",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# STORE CUSTOMER CRM ANALYSIS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29799ee4",
   "metadata": {
    "papermill": {
     "duration": 0.019249,
     "end_time": "2024-09-20T15:34:58.881899",
     "exception": false,
     "start_time": "2024-09-20T15:34:58.862650",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## What will you learn from this project?\n",
    "* Data Preparation\n",
    "* Data Cleaning\n",
    "* RFM Analysis\n",
    "    * Calculate RFM Metrics\n",
    "    * Calculate RFM Scores\n",
    "    * Creating & Analysing RFM Segments\n",
    "* CLTV Analysis\n",
    "    * Average Order Value\n",
    "    * Purchase Frequency\n",
    "    * Repeat Rate & Churn Rate\n",
    "    * Profit Margin\n",
    "    * Customer Value\n",
    "    * Customer Lifetime Value\n",
    "    * Segmentation"
   ]
  },
  {
   "attachments": {
    "082319b9-245f-4643-9123-b09a05fbc514.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "165db27b",
   "metadata": {
    "papermill": {
     "duration": 0.019385,
     "end_time": "2024-09-20T15:34:58.920496",
     "exception": false,
     "start_time": "2024-09-20T15:34:58.901111",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Introduction\n",
    "* ***RFM Analysis:*** It is a technique used to segment customer behaviour. It helps to determine marketing and sales strategies by segmenting customers based on their buying habits.\n",
    "    * Recency (Yenilik): It is the period from the customer's last contact with the company, that is, from the customer's last purchase to today.(Recency = Today's date - Last purchase date)\n",
    "    * Frequency (Sıklık): Shows how often the customer shops.\n",
    "    * Monetary (Parasal Değer): It is the total expenditure made by the customer in their shopping.\n",
    "\n",
    "* ***Customer Lifetime Value (CLTV):*** is considered to be the monetary value that a customer will bring to a company during its relationship and communication with that company.\n",
    "\n",
    "![crm.png](attachment:082319b9-245f-4643-9123-b09a05fbc514.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af978749",
   "metadata": {
    "papermill": {
     "duration": 0.019253,
     "end_time": "2024-09-20T15:34:58.959193",
     "exception": false,
     "start_time": "2024-09-20T15:34:58.939940",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id=\"content\"></a>\n",
    "## Analysis Content\n",
    "1. [Python Libraries](#1)\n",
    "2. [Data Content](#2)\n",
    "3. [Read & Analyse Data](#3)\n",
    "4. [Data Distributions](#4)\n",
    "5. [Data Preparation (Box Plot Analysis)](#5)\n",
    "6. [Data Cleaning & Analysis](#6)\n",
    "7. [RFM (Recency, Frequency, Monetary)](#7)\n",
    "8. [RFM Scores](#8)\n",
    "9. [RFM Segmentation](#9)\n",
    "10. [RFM Analysis (Heatmap)](#10)\n",
    "11. [CLTV (Customer Lifetime Value)](#11)\n",
    "12. [CLTV Scores](#12)\n",
    "13. [CLTV Segmentation](#13)\n",
    "14. [CLTV Analysis](#14)\n",
    "15. [Conclusion](#15)"
   ]
  },
  {
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    "<a id='1'></a>\n",
    "## Python Libraries\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Next [Content](#2)"
   ]
  },
  {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/online-retail-ii/online_retail_II.xlsx\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session\n",
    "\n",
    "import datetime as dt\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import re\n",
    "import itertools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29cbf6f1",
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     "status": "completed"
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   "source": [
    "<a id='2'></a>\n",
    "## Data Content\n",
    "* This Online Retail II data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers.\n",
    "    \n",
    "    * ***InvoiceNo:*** Invoice number. Nominal. A 6-digit integral number uniquely assigned to each transaction. If this code starts with the letter 'c', it indicates a cancellation. \n",
    "    * ***StockCode:*** Product (item) code. Nominal. A 5-digit integral number uniquely assigned to each distinct product. \n",
    "    * ***Description:*** Product (item) name. Nominal. \n",
    "    * ***Quantity:*** The quantities of each product (item) per transaction. Numeric.\t\n",
    "    * ***InvoiceDate:*** Invice date and time. Numeric. The day and time when a transaction was generated. \n",
    "    * ***UnitPrice:*** Unit price. Numeric. Product price per unit in sterling (Â£). \n",
    "    * ***CustomerID:*** Customer number. Nominal. A 5-digit integral number uniquely assigned to each customer. \n",
    "    * ***Country:*** Country name. Nominal. The name of the country where a customer resides.\n",
    "\n",
    "* Online Retail II Official Website: https://archive.ics.uci.edu/dataset/502/online+retail+ii\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#1)\n",
    "<br>\n",
    "> Next [Content](#3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c924c51f",
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   "source": [
    "<a id='3'></a>\n",
    "## Read & Analyse Data\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#2)\n",
    "<br>\n",
    "> Next [Content](#4)"
   ]
  },
  {
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   "execution_count": 2,
   "id": "b121a990",
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    "# Read Data\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "\n",
    "df = pd.read_excel(\"/kaggle/input/online-retail-ii/online_retail_II.xlsx\", sheet_name=\"Year 2010-2011\")"
   ]
  },
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   "cell_type": "code",
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Invoice</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>Price</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.550</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.750</td>\n",
       "      <td>17850.000</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
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       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
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       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Invoice StockCode                          Description  Quantity  \\\n",
       "0  536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1  536365     71053                  WHITE METAL LANTERN         6   \n",
       "2  536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3  536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4  536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "          InvoiceDate  Price  Customer ID         Country  \n",
       "0 2010-12-01 08:26:00  2.550    17850.000  United Kingdom  \n",
       "1 2010-12-01 08:26:00  3.390    17850.000  United Kingdom  \n",
       "2 2010-12-01 08:26:00  2.750    17850.000  United Kingdom  \n",
       "3 2010-12-01 08:26:00  3.390    17850.000  United Kingdom  \n",
       "4 2010-12-01 08:26:00  3.390    17850.000  United Kingdom  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_retail = df.copy()\n",
    "# Show five row of data\n",
    "df_retail.head()"
   ]
  },
  {
   "cell_type": "code",
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    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Quantity</th>\n",
       "      <td>541910.000</td>\n",
       "      <td>9.552</td>\n",
       "      <td>-80995.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>80995.000</td>\n",
       "      <td>218.081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InvoiceDate</th>\n",
       "      <td>541910</td>\n",
       "      <td>2011-07-04 13:35:22.342307584</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2011-03-28 11:34:00</td>\n",
       "      <td>2011-07-19 17:17:00</td>\n",
       "      <td>2011-10-19 11:27:00</td>\n",
       "      <td>2011-12-09 12:50:00</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>541910.000</td>\n",
       "      <td>4.611</td>\n",
       "      <td>-11062.060</td>\n",
       "      <td>1.250</td>\n",
       "      <td>2.080</td>\n",
       "      <td>4.130</td>\n",
       "      <td>38970.000</td>\n",
       "      <td>96.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <td>406830.000</td>\n",
       "      <td>15287.684</td>\n",
       "      <td>12346.000</td>\n",
       "      <td>13953.000</td>\n",
       "      <td>15152.000</td>\n",
       "      <td>16791.000</td>\n",
       "      <td>18287.000</td>\n",
       "      <td>1713.603</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "                 count                           mean                  min  \\\n",
       "Quantity    541910.000                          9.552           -80995.000   \n",
       "InvoiceDate     541910  2011-07-04 13:35:22.342307584  2010-12-01 08:26:00   \n",
       "Price       541910.000                          4.611           -11062.060   \n",
       "Customer ID 406830.000                      15287.684            12346.000   \n",
       "\n",
       "                             25%                  50%                  75%  \\\n",
       "Quantity                   1.000                3.000               10.000   \n",
       "InvoiceDate  2011-03-28 11:34:00  2011-07-19 17:17:00  2011-10-19 11:27:00   \n",
       "Price                      1.250                2.080                4.130   \n",
       "Customer ID            13953.000            15152.000            16791.000   \n",
       "\n",
       "                             max      std  \n",
       "Quantity               80995.000  218.081  \n",
       "InvoiceDate  2011-12-09 12:50:00      NaN  \n",
       "Price                  38970.000   96.760  \n",
       "Customer ID            18287.000 1713.603  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe basic statistics of data\n",
    "df_retail.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "595a7f52",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 541910 entries, 0 to 541909\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count   Dtype         \n",
      "---  ------       --------------   -----         \n",
      " 0   Invoice      541910 non-null  object        \n",
      " 1   StockCode    541910 non-null  object        \n",
      " 2   Description  540456 non-null  object        \n",
      " 3   Quantity     541910 non-null  int64         \n",
      " 4   InvoiceDate  541910 non-null  datetime64[ns]\n",
      " 5   Price        541910 non-null  float64       \n",
      " 6   Customer ID  406830 non-null  float64       \n",
      " 7   Country      541910 non-null  object        \n",
      "dtypes: datetime64[ns](1), float64(2), int64(1), object(4)\n",
      "memory usage: 33.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# Information about data\n",
    "df_retail.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dded113",
   "metadata": {
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   },
   "source": [
    "<a id='4'></a>\n",
    "## Data Distributions\n",
    "* Unique Values\n",
    "* Distribution of Remaining Features\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#3)\n",
    "<br>\n",
    "> Next [Content](#5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "efb22834",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:09.945761Z",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Invoice             0\n",
       "StockCode           0\n",
       "Description      1454\n",
       "Quantity            0\n",
       "InvoiceDate         0\n",
       "Price               0\n",
       "Customer ID    135080\n",
       "Country             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Null Values\n",
    "df_retail.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4223"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Description: Product (item) name. Nominal\n",
    "# Nunique Value for Description\n",
    "df_retail[\"Description\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "77bc13c4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:10.162221Z",
     "iopub.status.busy": "2024-09-20T15:36:10.161356Z",
     "iopub.status.idle": "2024-09-20T15:36:10.221842Z",
     "shell.execute_reply": "2024-09-20T15:36:10.220844Z"
    },
    "papermill": {
     "duration": 0.083689,
     "end_time": "2024-09-20T15:36:10.224028",
     "exception": false,
     "start_time": "2024-09-20T15:36:10.140339",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quantity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20713</th>\n",
       "      <td>-400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4 PURPLE FLOCK DINNER CANDLES</th>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50'S CHRISTMAS GIFT BAG LARGE</th>\n",
       "      <td>1913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOLLY GIRL BEAKER</th>\n",
       "      <td>2448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I LOVE LONDON MINI BACKPACK</th>\n",
       "      <td>389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Quantity\n",
       "Description                             \n",
       "20713                               -400\n",
       " 4 PURPLE FLOCK DINNER CANDLES       144\n",
       " 50'S CHRISTMAS GIFT BAG LARGE      1913\n",
       " DOLLY GIRL BEAKER                  2448\n",
       " I LOVE LONDON MINI BACKPACK         389"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Description: Product (item) name. Nominal\n",
    "# Item Count\n",
    "df_retail.groupby(\"Description\").agg({\"Quantity\":\"sum\"}).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "729c3962",
   "metadata": {
    "papermill": {
     "duration": 0.019853,
     "end_time": "2024-09-20T15:36:10.263767",
     "exception": false,
     "start_time": "2024-09-20T15:36:10.243914",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='5'></a>\n",
    "## Data Preparation (Box Plot Analysis)\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#4)\n",
    "<br>\n",
    "> Next [Content](#6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2d63e7a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:10.305845Z",
     "iopub.status.busy": "2024-09-20T15:36:10.304886Z",
     "iopub.status.idle": "2024-09-20T15:36:10.313086Z",
     "shell.execute_reply": "2024-09-20T15:36:10.312094Z"
    },
    "papermill": {
     "duration": 0.031669,
     "end_time": "2024-09-20T15:36:10.315333",
     "exception": false,
     "start_time": "2024-09-20T15:36:10.283664",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create Total Price for Customer Prices\n",
    "df_retail[\"TotalPrice\"] = df_retail[\"Quantity\"] * df_retail[\"Price\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7f08bcac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:10.357475Z",
     "iopub.status.busy": "2024-09-20T15:36:10.356817Z",
     "iopub.status.idle": "2024-09-20T15:36:10.455849Z",
     "shell.execute_reply": "2024-09-20T15:36:10.454856Z"
    },
    "papermill": {
     "duration": 0.122537,
     "end_time": "2024-09-20T15:36:10.457975",
     "exception": false,
     "start_time": "2024-09-20T15:36:10.335438",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Invoice</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>536365</th>\n",
       "      <td>139.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536366</th>\n",
       "      <td>22.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536367</th>\n",
       "      <td>278.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536368</th>\n",
       "      <td>70.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536369</th>\n",
       "      <td>17.850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         TotalPrice\n",
       "Invoice            \n",
       "536365      139.120\n",
       "536366       22.200\n",
       "536367      278.730\n",
       "536368       70.050\n",
       "536369       17.850"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Invoice First 5 Row Review\n",
    "df_retail.groupby(\"Invoice\").agg({\"TotalPrice\":\"sum\"}).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f0c57f57",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:10.499689Z",
     "iopub.status.busy": "2024-09-20T15:36:10.499004Z",
     "iopub.status.idle": "2024-09-20T15:36:13.249687Z",
     "shell.execute_reply": "2024-09-20T15:36:13.248590Z"
    },
    "papermill": {
     "duration": 2.773914,
     "end_time": "2024-09-20T15:36:13.251978",
     "exception": false,
     "start_time": "2024-09-20T15:36:10.478064",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Before Data Cleaning\n",
    "plt.figure(figsize=(12,8))\n",
    "df_retail.boxplot()\n",
    "plt.title(\"Box Plot Before Data Cleaning\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9cc11c9a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:13.299131Z",
     "iopub.status.busy": "2024-09-20T15:36:13.298727Z",
     "iopub.status.idle": "2024-09-20T15:36:14.030266Z",
     "shell.execute_reply": "2024-09-20T15:36:14.029258Z"
    },
    "papermill": {
     "duration": 0.759788,
     "end_time": "2024-09-20T15:36:14.032809",
     "exception": false,
     "start_time": "2024-09-20T15:36:13.273021",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Data Cleaning: Removing invoices for returned goods\n",
    "df_retail = df_retail[~df_retail[\"Invoice\"].str.contains(\"C\", na=False)] \n",
    "df_retail = df_retail[df_retail[\"Price\"] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "12e595cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:14.076789Z",
     "iopub.status.busy": "2024-09-20T15:36:14.076036Z",
     "iopub.status.idle": "2024-09-20T15:36:16.822434Z",
     "shell.execute_reply": "2024-09-20T15:36:16.821419Z"
    },
    "papermill": {
     "duration": 2.770849,
     "end_time": "2024-09-20T15:36:16.824681",
     "exception": false,
     "start_time": "2024-09-20T15:36:14.053832",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# After Data Cleaning\n",
    "plt.figure(figsize=(12,8))\n",
    "df_retail.boxplot()\n",
    "plt.title(\"Box Plot After Data Cleaning\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d40f167",
   "metadata": {
    "papermill": {
     "duration": 0.021012,
     "end_time": "2024-09-20T15:36:16.867144",
     "exception": false,
     "start_time": "2024-09-20T15:36:16.846132",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='6'></a>\n",
    "## Data Cleaning & Analysis\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#5)\n",
    "<br>\n",
    "> Next [Content](#7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "18da64b8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:16.911075Z",
     "iopub.status.busy": "2024-09-20T15:36:16.910686Z",
     "iopub.status.idle": "2024-09-20T15:36:17.020139Z",
     "shell.execute_reply": "2024-09-20T15:36:17.019153Z"
    },
    "papermill": {
     "duration": 0.133977,
     "end_time": "2024-09-20T15:36:17.022280",
     "exception": false,
     "start_time": "2024-09-20T15:36:16.888303",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Invoice             0\n",
       "StockCode           0\n",
       "Description         0\n",
       "Quantity            0\n",
       "InvoiceDate         0\n",
       "Price               0\n",
       "Customer ID    132220\n",
       "Country             0\n",
       "TotalPrice          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Null Values\n",
    "df_retail.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "96357c74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.067304Z",
     "iopub.status.busy": "2024-09-20T15:36:17.066341Z",
     "iopub.status.idle": "2024-09-20T15:36:17.293394Z",
     "shell.execute_reply": "2024-09-20T15:36:17.292376Z"
    },
    "papermill": {
     "duration": 0.252006,
     "end_time": "2024-09-20T15:36:17.295697",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.043691",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Invoice        0\n",
       "StockCode      0\n",
       "Description    0\n",
       "Quantity       0\n",
       "InvoiceDate    0\n",
       "Price          0\n",
       "Customer ID    0\n",
       "Country        0\n",
       "TotalPrice     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop Null Values\n",
    "df_retail.dropna(inplace=True)\n",
    "df_retail.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1890a7e0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.341536Z",
     "iopub.status.busy": "2024-09-20T15:36:17.340837Z",
     "iopub.status.idle": "2024-09-20T15:36:17.362320Z",
     "shell.execute_reply": "2024-09-20T15:36:17.361334Z"
    },
    "papermill": {
     "duration": 0.046645,
     "end_time": "2024-09-20T15:36:17.364576",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.317931",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18532"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Invoice Count\n",
    "df_retail[\"Invoice\"].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6172d2da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.410791Z",
     "iopub.status.busy": "2024-09-20T15:36:17.410370Z",
     "iopub.status.idle": "2024-09-20T15:36:17.471052Z",
     "shell.execute_reply": "2024-09-20T15:36:17.470032Z"
    },
    "papermill": {
     "duration": 0.086684,
     "end_time": "2024-09-20T15:36:17.473293",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.386609",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quantity</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PAPER CRAFT , LITTLE BIRDIE</th>\n",
       "      <td>80995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEDIUM CERAMIC TOP STORAGE JAR</th>\n",
       "      <td>77916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORLD WAR 2 GLIDERS ASSTD DESIGNS</th>\n",
       "      <td>54415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JUMBO BAG RED RETROSPOT</th>\n",
       "      <td>46181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHITE HANGING HEART T-LIGHT HOLDER</th>\n",
       "      <td>36725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Quantity\n",
       "Description                                 \n",
       "PAPER CRAFT , LITTLE BIRDIE            80995\n",
       "MEDIUM CERAMIC TOP STORAGE JAR         77916\n",
       "WORLD WAR 2 GLIDERS ASSTD DESIGNS      54415\n",
       "JUMBO BAG RED RETROSPOT                46181\n",
       "WHITE HANGING HEART T-LIGHT HOLDER     36725"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Max Quantity\n",
    "df_retail.groupby(\"Description\").agg({\"Quantity\":\"sum\"}).sort_values(by=\"Quantity\", ascending=0).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a8439c0f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.520404Z",
     "iopub.status.busy": "2024-09-20T15:36:17.519574Z",
     "iopub.status.idle": "2024-09-20T15:36:17.586595Z",
     "shell.execute_reply": "2024-09-20T15:36:17.585612Z"
    },
    "papermill": {
     "duration": 0.092321,
     "end_time": "2024-09-20T15:36:17.588778",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.496457",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PAPER CRAFT , LITTLE BIRDIE</th>\n",
       "      <td>168469.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REGENCY CAKESTAND 3 TIER</th>\n",
       "      <td>142592.950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WHITE HANGING HEART T-LIGHT HOLDER</th>\n",
       "      <td>100448.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JUMBO BAG RED RETROSPOT</th>\n",
       "      <td>85220.780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEDIUM CERAMIC TOP STORAGE JAR</th>\n",
       "      <td>81416.730</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    TotalPrice\n",
       "Description                                   \n",
       "PAPER CRAFT , LITTLE BIRDIE         168469.600\n",
       "REGENCY CAKESTAND 3 TIER            142592.950\n",
       "WHITE HANGING HEART T-LIGHT HOLDER  100448.150\n",
       "JUMBO BAG RED RETROSPOT              85220.780\n",
       "MEDIUM CERAMIC TOP STORAGE JAR       81416.730"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Max Total Price\n",
    "df_retail.groupby(\"Description\").agg({\"TotalPrice\":\"sum\"}).sort_values(by=\"TotalPrice\", ascending=0).head()"
   ]
  },
  {
   "attachments": {
    "b3b30fb6-cb12-4518-a802-4aa53f7567b6.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "f4c1b40e",
   "metadata": {
    "papermill": {
     "duration": 0.02163,
     "end_time": "2024-09-20T15:36:17.632603",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.610973",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='7'></a>\n",
    "## RFM (Recency, Frequency, Monetary)\n",
    "* R (Recency) => Time elapsed between today and the last purchase (the larger the score, the smaller the score)\n",
    "* F (Frequency) => Number of unique invoices (The larger the number, the larger the score)\n",
    "* M (Monetary) => Total payment on invoice\n",
    "\n",
    "![rfm.png](attachment:b3b30fb6-cb12-4518-a802-4aa53f7567b6.png)\n",
    "\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#6)\n",
    "<br>\n",
    "> Next [Content](#8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "61cb2321",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.678386Z",
     "iopub.status.busy": "2024-09-20T15:36:17.678014Z",
     "iopub.status.idle": "2024-09-20T15:36:17.692314Z",
     "shell.execute_reply": "2024-09-20T15:36:17.691251Z"
    },
    "papermill": {
     "duration": 0.039889,
     "end_time": "2024-09-20T15:36:17.694565",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.654676",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Invoice</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>Price</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.550</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.750</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>22.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Invoice StockCode                          Description  Quantity  \\\n",
       "0  536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1  536365     71053                  WHITE METAL LANTERN         6   \n",
       "2  536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3  536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4  536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "          InvoiceDate  Price  Customer ID         Country  TotalPrice  \n",
       "0 2010-12-01 08:26:00  2.550    17850.000  United Kingdom      15.300  \n",
       "1 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  \n",
       "2 2010-12-01 08:26:00  2.750    17850.000  United Kingdom      22.000  \n",
       "3 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  \n",
       "4 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_retail.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a1383347",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.741909Z",
     "iopub.status.busy": "2024-09-20T15:36:17.741477Z",
     "iopub.status.idle": "2024-09-20T15:36:17.746341Z",
     "shell.execute_reply": "2024-09-20T15:36:17.745352Z"
    },
    "papermill": {
     "duration": 0.031339,
     "end_time": "2024-09-20T15:36:17.748614",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.717275",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# For Recency Because \"Time elapsed between today and the last purchase\"\n",
    "# today_date: example datetime\n",
    "today_date = dt.datetime(2011, 12, 11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "65e1e97e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.795721Z",
     "iopub.status.busy": "2024-09-20T15:36:17.795287Z",
     "iopub.status.idle": "2024-09-20T15:36:17.803153Z",
     "shell.execute_reply": "2024-09-20T15:36:17.802138Z"
    },
    "papermill": {
     "duration": 0.034064,
     "end_time": "2024-09-20T15:36:17.805327",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.771263",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2011-12-09 12:50:00')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Last Invoice\n",
    "df_retail[\"InvoiceDate\"].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "96ecfd32",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:17.853333Z",
     "iopub.status.busy": "2024-09-20T15:36:17.852932Z",
     "iopub.status.idle": "2024-09-20T15:36:18.823981Z",
     "shell.execute_reply": "2024-09-20T15:36:18.822653Z"
    },
    "papermill": {
     "duration": 0.998308,
     "end_time": "2024-09-20T15:36:18.826440",
     "exception": false,
     "start_time": "2024-09-20T15:36:17.828132",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# RFM DataFrame\n",
    "rfm = df_retail.groupby(\"Customer ID\").agg({\"InvoiceDate\": lambda date: (today_date - date.max()).days,\n",
    "                                            \"Invoice\": lambda num: num.nunique(),\n",
    "                                            \"TotalPrice\": lambda TotalPrice: TotalPrice.sum()})\n",
    "rfm.columns = [\"Recency\", \"Frequency\", \"Monetary\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4f45910c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:18.874080Z",
     "iopub.status.busy": "2024-09-20T15:36:18.873673Z",
     "iopub.status.idle": "2024-09-20T15:36:18.883382Z",
     "shell.execute_reply": "2024-09-20T15:36:18.882469Z"
    },
    "papermill": {
     "duration": 0.035915,
     "end_time": "2024-09-20T15:36:18.885247",
     "exception": false,
     "start_time": "2024-09-20T15:36:18.849332",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Recency</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Monetary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.000</th>\n",
       "      <td>326</td>\n",
       "      <td>1</td>\n",
       "      <td>77183.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.000</th>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4310.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.000</th>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "      <td>1797.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349.000</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>1757.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.000</th>\n",
       "      <td>311</td>\n",
       "      <td>1</td>\n",
       "      <td>334.400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Recency  Frequency  Monetary\n",
       "Customer ID                              \n",
       "12346.000        326          1 77183.600\n",
       "12347.000          3          7  4310.000\n",
       "12348.000         76          4  1797.240\n",
       "12349.000         19          1  1757.550\n",
       "12350.000        311          1   334.400"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# RFM Head\n",
    "rfm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "636bfff6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:18.932185Z",
     "iopub.status.busy": "2024-09-20T15:36:18.931270Z",
     "iopub.status.idle": "2024-09-20T15:36:18.949181Z",
     "shell.execute_reply": "2024-09-20T15:36:18.948242Z"
    },
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     "duration": 0.043582,
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     "exception": false,
     "start_time": "2024-09-20T15:36:18.907754",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Recency</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>93.059</td>\n",
       "      <td>100.012</td>\n",
       "      <td>1.000</td>\n",
       "      <td>18.000</td>\n",
       "      <td>51.000</td>\n",
       "      <td>142.750</td>\n",
       "      <td>374.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frequency</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>4.272</td>\n",
       "      <td>7.698</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>209.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Monetary</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>2054.271</td>\n",
       "      <td>8989.230</td>\n",
       "      <td>3.750</td>\n",
       "      <td>307.415</td>\n",
       "      <td>674.485</td>\n",
       "      <td>1661.740</td>\n",
       "      <td>280206.020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             count     mean      std   min     25%     50%      75%        max\n",
       "Recency   4338.000   93.059  100.012 1.000  18.000  51.000  142.750    374.000\n",
       "Frequency 4338.000    4.272    7.698 1.000   1.000   2.000    5.000    209.000\n",
       "Monetary  4338.000 2054.271 8989.230 3.750 307.415 674.485 1661.740 280206.020"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# RFM Analysis\n",
    "rfm.describe().T"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "aa56d312",
   "metadata": {
    "papermill": {
     "duration": 0.022495,
     "end_time": "2024-09-20T15:36:19.047357",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.024862",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='8'></a>\n",
    "## RFM Scores\n",
    "\n",
    "![rfmscore.png](attachment:d8501f4b-b36b-4958-bb81-39d9d360dbf3.png)\n",
    "\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#7)\n",
    "<br>\n",
    "> Next [Content](#9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "05d51152",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.095644Z",
     "iopub.status.busy": "2024-09-20T15:36:19.094713Z",
     "iopub.status.idle": "2024-09-20T15:36:19.113838Z",
     "shell.execute_reply": "2024-09-20T15:36:19.112876Z"
    },
    "papermill": {
     "duration": 0.045626,
     "end_time": "2024-09-20T15:36:19.115997",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.070371",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Calculate RFM Score\n",
    "rfm[\"Recency_Score\"] = pd.qcut(rfm[\"Recency\"], 5, labels=[5,4,3,2,1])\n",
    "rfm[\"Frequency_Score\"] = pd.qcut(rfm[\"Frequency\"].rank(method=\"first\"), 5, labels=[1,2,3,4,5])\n",
    "rfm[\"Monetary_Score\"] = pd.qcut(rfm[\"Monetary\"], 5, labels=[1,2,3,4,5])\n",
    "\n",
    "rfm[\"RFM_Score\"] = (rfm[\"Recency_Score\"].astype(str) + rfm[\"Frequency_Score\"].astype(str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ad868163",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.163857Z",
     "iopub.status.busy": "2024-09-20T15:36:19.163102Z",
     "iopub.status.idle": "2024-09-20T15:36:19.176270Z",
     "shell.execute_reply": "2024-09-20T15:36:19.175294Z"
    },
    "papermill": {
     "duration": 0.039273,
     "end_time": "2024-09-20T15:36:19.178232",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.138959",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Recency</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Monetary</th>\n",
       "      <th>Recency_Score</th>\n",
       "      <th>Frequency_Score</th>\n",
       "      <th>Monetary_Score</th>\n",
       "      <th>RFM_Score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.000</th>\n",
       "      <td>326</td>\n",
       "      <td>1</td>\n",
       "      <td>77183.600</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.000</th>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4310.000</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.000</th>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "      <td>1797.240</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349.000</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>1757.550</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.000</th>\n",
       "      <td>311</td>\n",
       "      <td>1</td>\n",
       "      <td>334.400</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Recency  Frequency  Monetary Recency_Score Frequency_Score  \\\n",
       "Customer ID                                                               \n",
       "12346.000        326          1 77183.600             1               1   \n",
       "12347.000          3          7  4310.000             5               5   \n",
       "12348.000         76          4  1797.240             2               4   \n",
       "12349.000         19          1  1757.550             4               1   \n",
       "12350.000        311          1   334.400             1               1   \n",
       "\n",
       "            Monetary_Score RFM_Score  \n",
       "Customer ID                           \n",
       "12346.000                5        11  \n",
       "12347.000                5        55  \n",
       "12348.000                4        24  \n",
       "12349.000                4        41  \n",
       "12350.000                2        11  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# New RFM Head\n",
    "rfm.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae3270c6",
   "metadata": {
    "papermill": {
     "duration": 0.022626,
     "end_time": "2024-09-20T15:36:19.223790",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.201164",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='9'></a>\n",
    "## RFM Segmentation\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#8)\n",
    "<br>\n",
    "> Next [Content](#10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "35473580",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.272058Z",
     "iopub.status.busy": "2024-09-20T15:36:19.271142Z",
     "iopub.status.idle": "2024-09-20T15:36:19.276717Z",
     "shell.execute_reply": "2024-09-20T15:36:19.275724Z"
    },
    "papermill": {
     "duration": 0.031998,
     "end_time": "2024-09-20T15:36:19.278778",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.246780",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Segmentation\n",
    "seg_map = {\n",
    "    r\"[1-2][1-2]\": \"hibernating\",\n",
    "    r\"[1-2][3-4]\": \"at_Risk\",\n",
    "    r\"[1-2]5\": \"cant_loose\",\n",
    "    r\"3[1-2]\": \"about_to_sleep\",\n",
    "    r\"33\": \"need_attention\",\n",
    "    r\"[3-4][4-5]\": \"loyal_customers\",\n",
    "    r\"41\": \"promising\",\n",
    "    r\"51\": \"new_customers\",\n",
    "    r\"[4-5][2-3]\": \"potential_loyalists\",\n",
    "    r\"5[4-5]\": \"champions\",\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "89b9b1d3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.326782Z",
     "iopub.status.busy": "2024-09-20T15:36:19.326142Z",
     "iopub.status.idle": "2024-09-20T15:36:19.388677Z",
     "shell.execute_reply": "2024-09-20T15:36:19.387544Z"
    },
    "papermill": {
     "duration": 0.088981,
     "end_time": "2024-09-20T15:36:19.390808",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.301827",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "rfm[\"Segment\"] = rfm[\"RFM_Score\"].replace(seg_map, regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0f5e18ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.438339Z",
     "iopub.status.busy": "2024-09-20T15:36:19.437936Z",
     "iopub.status.idle": "2024-09-20T15:36:19.452468Z",
     "shell.execute_reply": "2024-09-20T15:36:19.451536Z"
    },
    "papermill": {
     "duration": 0.040684,
     "end_time": "2024-09-20T15:36:19.454485",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.413801",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Recency</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Monetary</th>\n",
       "      <th>Recency_Score</th>\n",
       "      <th>Frequency_Score</th>\n",
       "      <th>Monetary_Score</th>\n",
       "      <th>RFM_Score</th>\n",
       "      <th>Segment</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346</th>\n",
       "      <td>326</td>\n",
       "      <td>1</td>\n",
       "      <td>77183.600</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>hibernating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347</th>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4310.000</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>55</td>\n",
       "      <td>champions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348</th>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "      <td>1797.240</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "      <td>at_Risk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>1757.550</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>41</td>\n",
       "      <td>promising</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350</th>\n",
       "      <td>311</td>\n",
       "      <td>1</td>\n",
       "      <td>334.400</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>hibernating</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Recency  Frequency  Monetary Recency_Score Frequency_Score  \\\n",
       "Customer ID                                                               \n",
       "12346            326          1 77183.600             1               1   \n",
       "12347              3          7  4310.000             5               5   \n",
       "12348             76          4  1797.240             2               4   \n",
       "12349             19          1  1757.550             4               1   \n",
       "12350            311          1   334.400             1               1   \n",
       "\n",
       "            Monetary_Score RFM_Score      Segment  \n",
       "Customer ID                                        \n",
       "12346                    5        11  hibernating  \n",
       "12347                    5        55    champions  \n",
       "12348                    4        24      at_Risk  \n",
       "12349                    4        41    promising  \n",
       "12350                    2        11  hibernating  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfm.index = rfm.index.astype(int)\n",
    "rfm.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a1d81d6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.505782Z",
     "iopub.status.busy": "2024-09-20T15:36:19.504876Z",
     "iopub.status.idle": "2024-09-20T15:36:19.588103Z",
     "shell.execute_reply": "2024-09-20T15:36:19.587102Z"
    },
    "papermill": {
     "duration": 0.111781,
     "end_time": "2024-09-20T15:36:19.590186",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.478405",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">Recency</th>\n",
       "      <th colspan=\"8\" halign=\"left\">Frequency</th>\n",
       "      <th colspan=\"8\" halign=\"left\">Monetary</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
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       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
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       "      <th>std</th>\n",
       "      <th>min</th>\n",
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       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>about_to_sleep</th>\n",
       "      <td>352.000</td>\n",
       "      <td>53.312</td>\n",
       "      <td>10.943</td>\n",
       "      <td>34.000</td>\n",
       "      <td>44.000</td>\n",
       "      <td>53.000</td>\n",
       "      <td>64.000</td>\n",
       "      <td>72.000</td>\n",
       "      <td>352.000</td>\n",
       "      <td>1.162</td>\n",
       "      <td>0.369</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>352.000</td>\n",
       "      <td>471.994</td>\n",
       "      <td>533.591</td>\n",
       "      <td>6.200</td>\n",
       "      <td>194.520</td>\n",
       "      <td>330.050</td>\n",
       "      <td>543.750</td>\n",
       "      <td>6207.670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>at_Risk</th>\n",
       "      <td>593.000</td>\n",
       "      <td>153.786</td>\n",
       "      <td>68.619</td>\n",
       "      <td>73.000</td>\n",
       "      <td>96.000</td>\n",
       "      <td>139.000</td>\n",
       "      <td>195.000</td>\n",
       "      <td>374.000</td>\n",
       "      <td>593.000</td>\n",
       "      <td>2.877</td>\n",
       "      <td>0.952</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>593.000</td>\n",
       "      <td>1084.535</td>\n",
       "      <td>2562.073</td>\n",
       "      <td>52.000</td>\n",
       "      <td>412.780</td>\n",
       "      <td>678.250</td>\n",
       "      <td>1200.620</td>\n",
       "      <td>44534.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cant_loose</th>\n",
       "      <td>63.000</td>\n",
       "      <td>132.968</td>\n",
       "      <td>65.250</td>\n",
       "      <td>73.000</td>\n",
       "      <td>89.000</td>\n",
       "      <td>108.000</td>\n",
       "      <td>161.000</td>\n",
       "      <td>373.000</td>\n",
       "      <td>63.000</td>\n",
       "      <td>8.381</td>\n",
       "      <td>4.290</td>\n",
       "      <td>6.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>34.000</td>\n",
       "      <td>63.000</td>\n",
       "      <td>2796.156</td>\n",
       "      <td>2090.490</td>\n",
       "      <td>70.020</td>\n",
       "      <td>1137.505</td>\n",
       "      <td>2225.970</td>\n",
       "      <td>3532.235</td>\n",
       "      <td>10254.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>champions</th>\n",
       "      <td>633.000</td>\n",
       "      <td>6.362</td>\n",
       "      <td>3.683</td>\n",
       "      <td>1.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>13.000</td>\n",
       "      <td>633.000</td>\n",
       "      <td>12.414</td>\n",
       "      <td>16.452</td>\n",
       "      <td>3.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>14.000</td>\n",
       "      <td>209.000</td>\n",
       "      <td>633.000</td>\n",
       "      <td>6857.964</td>\n",
       "      <td>20339.764</td>\n",
       "      <td>201.120</td>\n",
       "      <td>1451.280</td>\n",
       "      <td>2612.960</td>\n",
       "      <td>4954.840</td>\n",
       "      <td>280206.020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hibernating</th>\n",
       "      <td>1071.000</td>\n",
       "      <td>217.605</td>\n",
       "      <td>92.014</td>\n",
       "      <td>73.000</td>\n",
       "      <td>135.000</td>\n",
       "      <td>219.000</td>\n",
       "      <td>289.500</td>\n",
       "      <td>374.000</td>\n",
       "      <td>1071.000</td>\n",
       "      <td>1.102</td>\n",
       "      <td>0.302</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>1071.000</td>\n",
       "      <td>488.643</td>\n",
       "      <td>2419.683</td>\n",
       "      <td>3.750</td>\n",
       "      <td>155.110</td>\n",
       "      <td>296.250</td>\n",
       "      <td>457.930</td>\n",
       "      <td>77183.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loyal_customers</th>\n",
       "      <td>819.000</td>\n",
       "      <td>33.608</td>\n",
       "      <td>15.577</td>\n",
       "      <td>15.000</td>\n",
       "      <td>20.000</td>\n",
       "      <td>30.000</td>\n",
       "      <td>44.000</td>\n",
       "      <td>72.000</td>\n",
       "      <td>819.000</td>\n",
       "      <td>6.480</td>\n",
       "      <td>4.546</td>\n",
       "      <td>3.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>63.000</td>\n",
       "      <td>819.000</td>\n",
       "      <td>2864.248</td>\n",
       "      <td>6007.062</td>\n",
       "      <td>36.560</td>\n",
       "      <td>991.795</td>\n",
       "      <td>1740.480</td>\n",
       "      <td>3052.905</td>\n",
       "      <td>124914.530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>need_attention</th>\n",
       "      <td>187.000</td>\n",
       "      <td>52.428</td>\n",
       "      <td>11.552</td>\n",
       "      <td>34.000</td>\n",
       "      <td>42.000</td>\n",
       "      <td>52.000</td>\n",
       "      <td>61.500</td>\n",
       "      <td>72.000</td>\n",
       "      <td>187.000</td>\n",
       "      <td>2.326</td>\n",
       "      <td>0.470</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>187.000</td>\n",
       "      <td>897.628</td>\n",
       "      <td>1102.503</td>\n",
       "      <td>6.900</td>\n",
       "      <td>385.965</td>\n",
       "      <td>638.060</td>\n",
       "      <td>1052.525</td>\n",
       "      <td>12601.830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_customers</th>\n",
       "      <td>42.000</td>\n",
       "      <td>7.429</td>\n",
       "      <td>3.902</td>\n",
       "      <td>1.000</td>\n",
       "      <td>4.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>11.000</td>\n",
       "      <td>13.000</td>\n",
       "      <td>42.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>42.000</td>\n",
       "      <td>388.213</td>\n",
       "      <td>570.776</td>\n",
       "      <td>89.940</td>\n",
       "      <td>195.037</td>\n",
       "      <td>274.505</td>\n",
       "      <td>358.317</td>\n",
       "      <td>3861.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>potential_loyalists</th>\n",
       "      <td>484.000</td>\n",
       "      <td>17.399</td>\n",
       "      <td>9.339</td>\n",
       "      <td>1.000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>18.000</td>\n",
       "      <td>25.000</td>\n",
       "      <td>33.000</td>\n",
       "      <td>484.000</td>\n",
       "      <td>2.010</td>\n",
       "      <td>0.651</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>484.000</td>\n",
       "      <td>1041.222</td>\n",
       "      <td>7656.324</td>\n",
       "      <td>20.800</td>\n",
       "      <td>290.117</td>\n",
       "      <td>521.275</td>\n",
       "      <td>883.730</td>\n",
       "      <td>168472.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>promising</th>\n",
       "      <td>94.000</td>\n",
       "      <td>23.511</td>\n",
       "      <td>5.193</td>\n",
       "      <td>15.000</td>\n",
       "      <td>19.000</td>\n",
       "      <td>23.000</td>\n",
       "      <td>27.000</td>\n",
       "      <td>33.000</td>\n",
       "      <td>94.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>94.000</td>\n",
       "      <td>294.008</td>\n",
       "      <td>240.407</td>\n",
       "      <td>30.000</td>\n",
       "      <td>141.567</td>\n",
       "      <td>221.425</td>\n",
       "      <td>361.845</td>\n",
       "      <td>1757.550</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Recency                                                \\\n",
       "                       count    mean    std    min     25%     50%     75%   \n",
       "Segment                                                                      \n",
       "about_to_sleep       352.000  53.312 10.943 34.000  44.000  53.000  64.000   \n",
       "at_Risk              593.000 153.786 68.619 73.000  96.000 139.000 195.000   \n",
       "cant_loose            63.000 132.968 65.250 73.000  89.000 108.000 161.000   \n",
       "champions            633.000   6.362  3.683  1.000   3.000   5.000  10.000   \n",
       "hibernating         1071.000 217.605 92.014 73.000 135.000 219.000 289.500   \n",
       "loyal_customers      819.000  33.608 15.577 15.000  20.000  30.000  44.000   \n",
       "need_attention       187.000  52.428 11.552 34.000  42.000  52.000  61.500   \n",
       "new_customers         42.000   7.429  3.902  1.000   4.000   8.000  11.000   \n",
       "potential_loyalists  484.000  17.399  9.339  1.000  10.000  18.000  25.000   \n",
       "promising             94.000  23.511  5.193 15.000  19.000  23.000  27.000   \n",
       "\n",
       "                            Frequency                                         \\\n",
       "                        max     count   mean    std   min   25%   50%    75%   \n",
       "Segment                                                                        \n",
       "about_to_sleep       72.000   352.000  1.162  0.369 1.000 1.000 1.000  1.000   \n",
       "at_Risk             374.000   593.000  2.877  0.952 2.000 2.000 3.000  3.000   \n",
       "cant_loose          373.000    63.000  8.381  4.290 6.000 6.000 7.000  9.000   \n",
       "champions            13.000   633.000 12.414 16.452 3.000 5.000 8.000 14.000   \n",
       "hibernating         374.000  1071.000  1.102  0.302 1.000 1.000 1.000  1.000   \n",
       "loyal_customers      72.000   819.000  6.480  4.546 3.000 4.000 5.000  8.000   \n",
       "need_attention       72.000   187.000  2.326  0.470 2.000 2.000 2.000  3.000   \n",
       "new_customers        13.000    42.000  1.000  0.000 1.000 1.000 1.000  1.000   \n",
       "potential_loyalists  33.000   484.000  2.010  0.651 1.000 2.000 2.000  2.000   \n",
       "promising            33.000    94.000  1.000  0.000 1.000 1.000 1.000  1.000   \n",
       "\n",
       "                            Monetary                                      \\\n",
       "                        max    count     mean       std     min      25%   \n",
       "Segment                                                                    \n",
       "about_to_sleep        2.000  352.000  471.994   533.591   6.200  194.520   \n",
       "at_Risk               6.000  593.000 1084.535  2562.073  52.000  412.780   \n",
       "cant_loose           34.000   63.000 2796.156  2090.490  70.020 1137.505   \n",
       "champions           209.000  633.000 6857.964 20339.764 201.120 1451.280   \n",
       "hibernating           2.000 1071.000  488.643  2419.683   3.750  155.110   \n",
       "loyal_customers      63.000  819.000 2864.248  6007.062  36.560  991.795   \n",
       "need_attention        3.000  187.000  897.628  1102.503   6.900  385.965   \n",
       "new_customers         1.000   42.000  388.213   570.776  89.940  195.037   \n",
       "potential_loyalists   3.000  484.000 1041.222  7656.324  20.800  290.117   \n",
       "promising             1.000   94.000  294.008   240.407  30.000  141.567   \n",
       "\n",
       "                                                  \n",
       "                         50%      75%        max  \n",
       "Segment                                           \n",
       "about_to_sleep       330.050  543.750   6207.670  \n",
       "at_Risk              678.250 1200.620  44534.300  \n",
       "cant_loose          2225.970 3532.235  10254.180  \n",
       "champions           2612.960 4954.840 280206.020  \n",
       "hibernating          296.250  457.930  77183.600  \n",
       "loyal_customers     1740.480 3052.905 124914.530  \n",
       "need_attention       638.060 1052.525  12601.830  \n",
       "new_customers        274.505  358.317   3861.000  \n",
       "potential_loyalists  521.275  883.730 168472.500  \n",
       "promising            221.425  361.845   1757.550  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe for segments\n",
    "rfm[[\"Segment\", \"Recency\", \"Frequency\", \"Monetary\"]].groupby(\"Segment\").describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93760c54",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='10'></a>\n",
    "## RFM Analysis (Heatmap)\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#9)\n",
    "<br>\n",
    "> Next [Content](#11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "018f28e3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:19.687769Z",
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     "shell.execute_reply": "2024-09-20T15:36:19.695133Z"
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     "exception": false,
     "start_time": "2024-09-20T15:36:19.662002",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "customer_seg = rfm[[\"Segment\", \"RFM_Score\"]].groupby(\"Segment\").count()\n",
    "customer_seg.columns = [\"Customer Count\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "295ab0b4",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Customer Count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Segment</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>about_to_sleep</th>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>at_Risk</th>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cant_loose</th>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>champions</th>\n",
       "      <td>633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hibernating</th>\n",
       "      <td>1071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loyal_customers</th>\n",
       "      <td>819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>need_attention</th>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_customers</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>potential_loyalists</th>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>promising</th>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Customer Count\n",
       "Segment                            \n",
       "about_to_sleep                  352\n",
       "at_Risk                         593\n",
       "cant_loose                       63\n",
       "champions                       633\n",
       "hibernating                    1071\n",
       "loyal_customers                 819\n",
       "need_attention                  187\n",
       "new_customers                    42\n",
       "potential_loyalists             484\n",
       "promising                        94"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer_seg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b89440b4",
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Segment</th>\n",
       "      <th>Recency</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Customer Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hibernating</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>hibernating</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>at_Risk</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>at_Risk</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>cant_loose</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>hibernating</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>hibernating</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>at_Risk</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>at_Risk</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>cant_loose</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>about_to_sleep</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>about_to_sleep</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>need_attention</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>loyal_customers</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>loyal_customers</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>promising</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>potential_loyalists</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>potential_loyalists</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>loyal_customers</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>loyal_customers</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>new_customers</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>potential_loyalists</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>potential_loyalists</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>champions</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>champions</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>633</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Segment  Recency  Frequency  Customer Count\n",
       "0           hibernating        1          1            1071\n",
       "1           hibernating        1          2            1071\n",
       "2               at_Risk        1          3             593\n",
       "3               at_Risk        1          4             593\n",
       "4            cant_loose        1          5              63\n",
       "5           hibernating        2          1            1071\n",
       "6           hibernating        2          2            1071\n",
       "7               at_Risk        2          3             593\n",
       "8               at_Risk        2          4             593\n",
       "9            cant_loose        2          5              63\n",
       "10       about_to_sleep        3          1             352\n",
       "11       about_to_sleep        3          2             352\n",
       "12       need_attention        3          3             187\n",
       "13      loyal_customers        3          4             819\n",
       "14      loyal_customers        3          5             819\n",
       "15            promising        4          1              94\n",
       "16  potential_loyalists        4          2             484\n",
       "17  potential_loyalists        4          3             484\n",
       "18      loyal_customers        4          4             819\n",
       "19      loyal_customers        4          5             819\n",
       "20        new_customers        5          1              42\n",
       "21  potential_loyalists        5          2             484\n",
       "22  potential_loyalists        5          3             484\n",
       "23            champions        5          4             633\n",
       "24            champions        5          5             633"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# RFM Data\n",
    "recency_values = [1, 2, 3, 4, 5]\n",
    "frequency_values = [1, 2, 3, 4, 5]\n",
    "\n",
    "combinations = list(itertools.product(recency_values, frequency_values))\n",
    "\n",
    "# RFM Matrix\n",
    "rfm_matrix = pd.DataFrame(combinations, columns=['Recency', 'Frequency'])\n",
    "\n",
    "def assign_segment(recency, frequency):\n",
    "    rfm_score = f\"{recency}{frequency}\"\n",
    "    for pattern, segment in seg_map.items():\n",
    "        if re.match(pattern, rfm_score):\n",
    "            return [segment, recency, frequency]\n",
    "    return [\"undefined\", recency, frequency]\n",
    "\n",
    "# RFM Score\n",
    "rfm_df = rfm_matrix.apply(lambda row: assign_segment(row['Recency'], row['Frequency']), axis=1)\n",
    "\n",
    "# RFM Dataframe\n",
    "rfm_df = pd.DataFrame(list(rfm_df), columns=['Segment', 'Recency', 'Frequency'])\n",
    "\n",
    "# Segment'e göre müşteri sayısı ekleme\n",
    "rfm_df = rfm_df.merge(customer_seg, on='Segment', how='left')\n",
    "\n",
    "rfm_df"
   ]
  },
  {
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    "papermill": {
     "duration": 0.373095,
     "end_time": "2024-09-20T15:36:20.230955",
     "exception": false,
     "start_time": "2024-09-20T15:36:19.857860",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create Pivot Table\n",
    "heatmap_data = rfm_df.pivot(index='Frequency', columns='Recency', values='Customer Count')\n",
    "\n",
    "# Fill NaN:0\n",
    "heatmap_data = heatmap_data.fillna(0)\n",
    "\n",
    "# Frequency ve Recency'ye göre gruplama ve toplama\n",
    "heatmap_data = heatmap_data.groupby(level=0).sum()\n",
    "heatmap_data = heatmap_data.sort_index(ascending=False)\n",
    "\n",
    "# Heatmap\n",
    "plt.figure(figsize=(8, 6))\n",
    "ax = sns.heatmap(heatmap_data, annot=True, fmt=\"n\", linewidths=0.5, cbar_kws={'label': 'Customer Count'})\n",
    "\n",
    "plt.title('RFM Segments Grid')\n",
    "plt.xlabel('Recency Score')\n",
    "plt.ylabel('Frequency Score')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {
    "8655750d-1d92-4463-9214-01659c43e610.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "id": "0f999084",
   "metadata": {
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     "start_time": "2024-09-20T15:36:20.255885",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='11'></a>\n",
    "## CLTV (Customer Lifetime Value)\n",
    "\n",
    "![cltv.png](attachment:8655750d-1d92-4463-9214-01659c43e610.png)\n",
    "\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#10)\n",
    "<br>\n",
    "> Next [Content](#12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "88715f6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:20.331997Z",
     "iopub.status.busy": "2024-09-20T15:36:20.331178Z",
     "iopub.status.idle": "2024-09-20T15:36:20.344500Z",
     "shell.execute_reply": "2024-09-20T15:36:20.343567Z"
    },
    "papermill": {
     "duration": 0.041547,
     "end_time": "2024-09-20T15:36:20.346808",
     "exception": false,
     "start_time": "2024-09-20T15:36:20.305261",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Invoice</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>Price</th>\n",
       "      <th>Customer ID</th>\n",
       "      <th>Country</th>\n",
       "      <th>TotalPrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.550</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>2.750</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>22.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>3.390</td>\n",
       "      <td>17850.000</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>20.340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Invoice StockCode                          Description  Quantity  \\\n",
       "0  536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1  536365     71053                  WHITE METAL LANTERN         6   \n",
       "2  536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3  536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4  536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "          InvoiceDate  Price  Customer ID         Country  TotalPrice  \n",
       "0 2010-12-01 08:26:00  2.550    17850.000  United Kingdom      15.300  \n",
       "1 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  \n",
       "2 2010-12-01 08:26:00  2.750    17850.000  United Kingdom      22.000  \n",
       "3 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  \n",
       "4 2010-12-01 08:26:00  3.390    17850.000  United Kingdom      20.340  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_retail.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b7f8f3bc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:20.400164Z",
     "iopub.status.busy": "2024-09-20T15:36:20.399757Z",
     "iopub.status.idle": "2024-09-20T15:36:21.096480Z",
     "shell.execute_reply": "2024-09-20T15:36:21.095497Z"
    },
    "papermill": {
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     "end_time": "2024-09-20T15:36:21.098762",
     "exception": false,
     "start_time": "2024-09-20T15:36:20.373076",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total_Transaction</th>\n",
       "      <th>Total_Unit</th>\n",
       "      <th>Total_Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346</th>\n",
       "      <td>1</td>\n",
       "      <td>74215</td>\n",
       "      <td>77183.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347</th>\n",
       "      <td>7</td>\n",
       "      <td>2458</td>\n",
       "      <td>4310.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348</th>\n",
       "      <td>4</td>\n",
       "      <td>2341</td>\n",
       "      <td>1797.240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349</th>\n",
       "      <td>1</td>\n",
       "      <td>631</td>\n",
       "      <td>1757.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350</th>\n",
       "      <td>1</td>\n",
       "      <td>197</td>\n",
       "      <td>334.400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Total_Transaction  Total_Unit  Total_Price\n",
       "Customer ID                                            \n",
       "12346                        1       74215    77183.600\n",
       "12347                        7        2458     4310.000\n",
       "12348                        4        2341     1797.240\n",
       "12349                        1         631     1757.550\n",
       "12350                        1         197      334.400"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cltv = df_retail.groupby(\"Customer ID\").agg({\"Invoice\": lambda x: x.nunique(),\n",
    "                                             \"Quantity\": lambda x: x.sum(),\n",
    "                                             \"TotalPrice\": lambda x: x.sum()})\n",
    "cltv.index = rfm.index.astype(int)\n",
    "cltv.columns = [\"Total_Transaction\", \"Total_Unit\", \"Total_Price\"]\n",
    "cltv.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4112c76f",
   "metadata": {
    "papermill": {
     "duration": 0.024968,
     "end_time": "2024-09-20T15:36:21.149279",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.124311",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='12'></a>\n",
    "## CLTV Scores\n",
    "* Average Order Value\n",
    "* Purchase Frequency\n",
    "* Repeat Rate & Churn Rate\n",
    "* Profit Margin\n",
    "* Customer Value\n",
    "* Customer Lifetime Value\n",
    "---\n",
    "> CLTV = (Customer Value / Churn Rate) * Profit Margin\n",
    "<br>\n",
    "> Customer Value = (Avg Order Value * Purchase Frequency)\n",
    "<br>\n",
    "> Average Order Value = (Total Price * Total Transaction)\n",
    "<br>\n",
    "> Purchase Frequency = (Total Transaction / Total Number of Customers)\n",
    "<br>\n",
    "> Churn Rate = (1 - Repeat Rate)\n",
    "<br>\n",
    "> Repeat Rate = (Customers of multi Purchases  / Total Number of Customers)\n",
    "<br>\n",
    "> Profit Margin = (Total Price * 0.1)\n",
    "\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#11)\n",
    "<br>\n",
    "> Next [Content](#13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f6eb36a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.201138Z",
     "iopub.status.busy": "2024-09-20T15:36:21.200741Z",
     "iopub.status.idle": "2024-09-20T15:36:21.206533Z",
     "shell.execute_reply": "2024-09-20T15:36:21.205514Z"
    },
    "papermill": {
     "duration": 0.034206,
     "end_time": "2024-09-20T15:36:21.208640",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.174434",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Average Order Value = Total Price * Total Transaction\n",
    "cltv[\"Average_Order_Value\"] = cltv[\"Total_Price\"] * cltv[\"Total_Transaction\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4ebefd63",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.261438Z",
     "iopub.status.busy": "2024-09-20T15:36:21.261037Z",
     "iopub.status.idle": "2024-09-20T15:36:21.265611Z",
     "shell.execute_reply": "2024-09-20T15:36:21.264750Z"
    },
    "papermill": {
     "duration": 0.033403,
     "end_time": "2024-09-20T15:36:21.267600",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.234197",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Total Customer (CLTV DataFrame: Groupby with Customer ID)\n",
    "Total_Customer = cltv.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c7a887f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.320116Z",
     "iopub.status.busy": "2024-09-20T15:36:21.319720Z",
     "iopub.status.idle": "2024-09-20T15:36:21.325453Z",
     "shell.execute_reply": "2024-09-20T15:36:21.324592Z"
    },
    "papermill": {
     "duration": 0.034674,
     "end_time": "2024-09-20T15:36:21.327578",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.292904",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Purchase Frequency = Total Transaction / Total Customer\n",
    "cltv[\"Purchase_Frequency\"] = cltv[\"Total_Transaction\"] / Total_Customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e08d110f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.380508Z",
     "iopub.status.busy": "2024-09-20T15:36:21.380110Z",
     "iopub.status.idle": "2024-09-20T15:36:21.386560Z",
     "shell.execute_reply": "2024-09-20T15:36:21.385655Z"
    },
    "papermill": {
     "duration": 0.035467,
     "end_time": "2024-09-20T15:36:21.388480",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.353013",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Customers of multi Purchases\n",
    "Multi_Customer = cltv[cltv[\"Total_Transaction\"] > 1].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "626c3dba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.440889Z",
     "iopub.status.busy": "2024-09-20T15:36:21.440473Z",
     "iopub.status.idle": "2024-09-20T15:36:21.445635Z",
     "shell.execute_reply": "2024-09-20T15:36:21.444669Z"
    },
    "papermill": {
     "duration": 0.033935,
     "end_time": "2024-09-20T15:36:21.447737",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.413802",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Repeat Rate = (Customers of multi Purchases / Total Number of Customers)\n",
    "cltv[\"Repeat_Rate\"] = Multi_Customer / Total_Customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "dd94aa14",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.501346Z",
     "iopub.status.busy": "2024-09-20T15:36:21.500957Z",
     "iopub.status.idle": "2024-09-20T15:36:21.506731Z",
     "shell.execute_reply": "2024-09-20T15:36:21.505752Z"
    },
    "papermill": {
     "duration": 0.035625,
     "end_time": "2024-09-20T15:36:21.508745",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.473120",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Churn Rate = (1 - Repeat Rate)\n",
    "cltv[\"Churn_Rate\"] = 1 - cltv[\"Repeat_Rate\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d22ac9eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.561604Z",
     "iopub.status.busy": "2024-09-20T15:36:21.561191Z",
     "iopub.status.idle": "2024-09-20T15:36:21.566955Z",
     "shell.execute_reply": "2024-09-20T15:36:21.565824Z"
    },
    "papermill": {
     "duration": 0.034799,
     "end_time": "2024-09-20T15:36:21.569112",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.534313",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Profit Margin = (Total Price * 0.1)\n",
    "cltv[\"Profit_Margin\"] = cltv[\"Total_Price\"] * 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "860dec3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.622112Z",
     "iopub.status.busy": "2024-09-20T15:36:21.621663Z",
     "iopub.status.idle": "2024-09-20T15:36:21.627409Z",
     "shell.execute_reply": "2024-09-20T15:36:21.626421Z"
    },
    "papermill": {
     "duration": 0.034907,
     "end_time": "2024-09-20T15:36:21.629515",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.594608",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Customer Value = (Avg Order Value * Purchase Frequency)\n",
    "cltv[\"Customer_Value\"] = cltv[\"Average_Order_Value\"] * cltv[\"Purchase_Frequency\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e190160d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.682895Z",
     "iopub.status.busy": "2024-09-20T15:36:21.682448Z",
     "iopub.status.idle": "2024-09-20T15:36:21.688571Z",
     "shell.execute_reply": "2024-09-20T15:36:21.687704Z"
    },
    "papermill": {
     "duration": 0.03544,
     "end_time": "2024-09-20T15:36:21.690775",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.655335",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# CLTV (Customer Lifetime Value) = (Customer Value / Churn Rate) * Profit Margin\n",
    "cltv[\"CLTV\"] = (cltv[\"Customer_Value\"] / cltv[\"Churn_Rate\"]) * cltv[\"Profit_Margin\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "252eb975",
   "metadata": {
    "papermill": {
     "duration": 0.025089,
     "end_time": "2024-09-20T15:36:21.741280",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.716191",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='13'></a>\n",
    "## CLTV Segmentation\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#12)\n",
    "<br>\n",
    "> Next [Content](#14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0d405793",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.795300Z",
     "iopub.status.busy": "2024-09-20T15:36:21.794906Z",
     "iopub.status.idle": "2024-09-20T15:36:21.803555Z",
     "shell.execute_reply": "2024-09-20T15:36:21.802505Z"
    },
    "papermill": {
     "duration": 0.037763,
     "end_time": "2024-09-20T15:36:21.805733",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.767970",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "cltv[\"Segment\"] = pd.qcut(cltv[\"CLTV\"], 4, labels=[\"D\", \"C\", \"B\", \"A\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3cdd1c7",
   "metadata": {
    "papermill": {
     "duration": 0.026283,
     "end_time": "2024-09-20T15:36:21.858498",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.832215",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "<a id='14'></a>\n",
    "## CLTV Analysis\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#13)\n",
    "<br>\n",
    "> Next [Content](#15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e9d482a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.914487Z",
     "iopub.status.busy": "2024-09-20T15:36:21.914099Z",
     "iopub.status.idle": "2024-09-20T15:36:21.928112Z",
     "shell.execute_reply": "2024-09-20T15:36:21.927174Z"
    },
    "papermill": {
     "duration": 0.044455,
     "end_time": "2024-09-20T15:36:21.930602",
     "exception": false,
     "start_time": "2024-09-20T15:36:21.886147",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Total_Transaction</th>\n",
       "      <th>Total_Unit</th>\n",
       "      <th>Total_Price</th>\n",
       "      <th>Average_Order_Value</th>\n",
       "      <th>Purchase_Frequency</th>\n",
       "      <th>Repeat_Rate</th>\n",
       "      <th>Churn_Rate</th>\n",
       "      <th>Profit_Margin</th>\n",
       "      <th>Customer_Value</th>\n",
       "      <th>CLTV</th>\n",
       "      <th>Segment</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346</th>\n",
       "      <td>1</td>\n",
       "      <td>74215</td>\n",
       "      <td>77183.600</td>\n",
       "      <td>77183.600</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.344</td>\n",
       "      <td>7718.360</td>\n",
       "      <td>17.792</td>\n",
       "      <td>399015.948</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347</th>\n",
       "      <td>7</td>\n",
       "      <td>2458</td>\n",
       "      <td>4310.000</td>\n",
       "      <td>30170.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.344</td>\n",
       "      <td>431.000</td>\n",
       "      <td>48.684</td>\n",
       "      <td>60966.437</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348</th>\n",
       "      <td>4</td>\n",
       "      <td>2341</td>\n",
       "      <td>1797.240</td>\n",
       "      <td>7188.960</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.344</td>\n",
       "      <td>179.724</td>\n",
       "      <td>6.629</td>\n",
       "      <td>3461.564</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349</th>\n",
       "      <td>1</td>\n",
       "      <td>631</td>\n",
       "      <td>1757.550</td>\n",
       "      <td>1757.550</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.344</td>\n",
       "      <td>175.755</td>\n",
       "      <td>0.405</td>\n",
       "      <td>206.898</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350</th>\n",
       "      <td>1</td>\n",
       "      <td>197</td>\n",
       "      <td>334.400</td>\n",
       "      <td>334.400</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.344</td>\n",
       "      <td>33.440</td>\n",
       "      <td>0.077</td>\n",
       "      <td>7.490</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Total_Transaction  Total_Unit  Total_Price  Average_Order_Value  \\\n",
       "Customer ID                                                                    \n",
       "12346                        1       74215    77183.600            77183.600   \n",
       "12347                        7        2458     4310.000            30170.000   \n",
       "12348                        4        2341     1797.240             7188.960   \n",
       "12349                        1         631     1757.550             1757.550   \n",
       "12350                        1         197      334.400              334.400   \n",
       "\n",
       "             Purchase_Frequency  Repeat_Rate  Churn_Rate  Profit_Margin  \\\n",
       "Customer ID                                                               \n",
       "12346                     0.000        0.656       0.344       7718.360   \n",
       "12347                     0.002        0.656       0.344        431.000   \n",
       "12348                     0.001        0.656       0.344        179.724   \n",
       "12349                     0.000        0.656       0.344        175.755   \n",
       "12350                     0.000        0.656       0.344         33.440   \n",
       "\n",
       "             Customer_Value       CLTV Segment  \n",
       "Customer ID                                     \n",
       "12346                17.792 399015.948       A  \n",
       "12347                48.684  60966.437       A  \n",
       "12348                 6.629   3461.564       B  \n",
       "12349                 0.405    206.898       B  \n",
       "12350                 0.077      7.490       D  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cltv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "cceb601a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-09-20T15:36:21.985393Z",
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       "      <td>0.014</td>\n",
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       "      <td>3371.973</td>\n",
       "      <td>339537.005</td>\n",
       "      <td>3326602744.474</td>\n",
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      "text/plain": [
       "             Total_Transaction  Total_Unit  Total_Price  Average_Order_Value  \\\n",
       "Customer ID                                                                    \n",
       "14911                      201       80265   143825.060         28908837.060   \n",
       "14646                       73      196915   280206.020         20455039.460   \n",
       "18102                       60       64124   259657.300         15579438.000   \n",
       "17450                       46       69993   194550.790          8949336.340   \n",
       "12748                      209       25747    33719.730          7047423.570   \n",
       "\n",
       "             Purchase_Frequency  Repeat_Rate  Churn_Rate  Profit_Margin  \\\n",
       "Customer ID                                                               \n",
       "14911                     0.046        0.656       0.344      14382.506   \n",
       "14646                     0.017        0.656       0.344      28020.602   \n",
       "18102                     0.014        0.656       0.344      25965.730   \n",
       "17450                     0.011        0.656       0.344      19455.079   \n",
       "12748                     0.048        0.656       0.344       3371.973   \n",
       "\n",
       "             Customer_Value            CLTV Segment  \n",
       "Customer ID                                          \n",
       "14911           1339482.768 55975945087.852       A  \n",
       "14646            344218.045 28024691179.515       A  \n",
       "18102            215483.237 16257125813.519       A  \n",
       "17450             94898.449  5364408635.395       A  \n",
       "12748            339537.005  3326602744.474       A  "
      ]
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>count</th>\n",
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       "      <th>Total_Transaction</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>4.272</td>\n",
       "      <td>7.698</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>209.000</td>\n",
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       "      <th>Total_Unit</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>1191.289</td>\n",
       "      <td>5046.082</td>\n",
       "      <td>1.000</td>\n",
       "      <td>160.000</td>\n",
       "      <td>379.000</td>\n",
       "      <td>992.750</td>\n",
       "      <td>196915.000</td>\n",
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       "    <tr>\n",
       "      <th>Total_Price</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>2054.271</td>\n",
       "      <td>8989.230</td>\n",
       "      <td>3.750</td>\n",
       "      <td>307.415</td>\n",
       "      <td>674.485</td>\n",
       "      <td>1661.740</td>\n",
       "      <td>280206.020</td>\n",
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       "    <tr>\n",
       "      <th>Average_Order_Value</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>47079.107</td>\n",
       "      <td>654271.723</td>\n",
       "      <td>3.750</td>\n",
       "      <td>358.715</td>\n",
       "      <td>1491.210</td>\n",
       "      <td>7289.898</td>\n",
       "      <td>28908837.060</td>\n",
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       "      <th>Purchase_Frequency</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.048</td>\n",
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       "    <tr>\n",
       "      <th>Repeat_Rate</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.656</td>\n",
       "      <td>0.656</td>\n",
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       "    <tr>\n",
       "      <th>Churn_Rate</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Profit_Margin</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>205.427</td>\n",
       "      <td>898.923</td>\n",
       "      <td>0.375</td>\n",
       "      <td>30.742</td>\n",
       "      <td>67.448</td>\n",
       "      <td>166.174</td>\n",
       "      <td>28020.602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Customer_Value</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>796.609</td>\n",
       "      <td>22274.806</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.753</td>\n",
       "      <td>7.766</td>\n",
       "      <td>1339482.768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLTV</th>\n",
       "      <td>4338.000</td>\n",
       "      <td>28813747.506</td>\n",
       "      <td>989207339.382</td>\n",
       "      <td>0.001</td>\n",
       "      <td>8.619</td>\n",
       "      <td>148.942</td>\n",
       "      <td>3559.452</td>\n",
       "      <td>55975945087.852</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                       count         mean           std   min     25%  \\\n",
       "Total_Transaction   4338.000        4.272         7.698 1.000   1.000   \n",
       "Total_Unit          4338.000     1191.289      5046.082 1.000 160.000   \n",
       "Total_Price         4338.000     2054.271      8989.230 3.750 307.415   \n",
       "Average_Order_Value 4338.000    47079.107    654271.723 3.750 358.715   \n",
       "Purchase_Frequency  4338.000        0.001         0.002 0.000   0.000   \n",
       "Repeat_Rate         4338.000        0.656         0.000 0.656   0.656   \n",
       "Churn_Rate          4338.000        0.344         0.000 0.344   0.344   \n",
       "Profit_Margin       4338.000      205.427       898.923 0.375  30.742   \n",
       "Customer_Value      4338.000      796.609     22274.806 0.001   0.088   \n",
       "CLTV                4338.000 28813747.506 989207339.382 0.001   8.619   \n",
       "\n",
       "                         50%      75%             max  \n",
       "Total_Transaction      2.000    5.000         209.000  \n",
       "Total_Unit           379.000  992.750      196915.000  \n",
       "Total_Price          674.485 1661.740      280206.020  \n",
       "Average_Order_Value 1491.210 7289.898    28908837.060  \n",
       "Purchase_Frequency     0.000    0.001           0.048  \n",
       "Repeat_Rate            0.656    0.656           0.656  \n",
       "Churn_Rate             0.344    0.344           0.344  \n",
       "Profit_Margin         67.448  166.174       28020.602  \n",
       "Customer_Value         0.753    7.766     1339482.768  \n",
       "CLTV                 148.942 3559.452 55975945087.852  "
      ]
     },
     "execution_count": 49,
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    "cltv.sort_values(by=\"CLTV\", ascending=False).describe().T"
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   "source": [
    "<a id='15'></a>\n",
    "## Conclusion\n",
    "---\n",
    "> Back to [Main Content](#content)\n",
    "<br>\n",
    "> Previous [Content](#14)"
   ]
  }
 ],
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