customer-lifetime-value-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Customer Lifetime Value Analysis\n",
    "\n",
    "The marketing team wants to determine how much they can spend on acquiring new customers to the platform. To achieve this, they need a CLV analysis for all customers, covering their entire relationship duration with the company."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data handling and pipeline\n",
    "from resq_pipeline.data_pipeline import DataPipeline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Visualization\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reset color and other runtime configs\n",
    "plt.rcParams.update(plt.rcParamsDefault)\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# apply a ploting style\n",
    "plt.style.use(\"seaborn-v0_8-talk\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Data pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12:23:03 Initializing pipeline\n",
      "12:23:03 Creating customer cohorts view in database\n",
      "12:23:03 Creating top partners by sales view in database\n",
      "12:23:03 Creating partner segments and order quantity view in database\n",
      "12:23:03 Creating Lifespan, Frequency, sales value view in database\n",
      "12:23:03 Done\n"
     ]
    }
   ],
   "source": [
    "pipeline = DataPipeline()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Retention Rate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "query = \"\"\"\n",
    "SELECT \n",
    "    MONTHS_SINCE_FIRST_PURCHASE AS M,\n",
    "    (CAST(COUNT(MONTHS_SINCE_FIRST_PURCHASE) AS REAL) / \n",
    "     CAST((SELECT COUNT(DISTINCT(USERID)) FROM CUSTOMER_COHORT) AS REAL)) * 100 AS RETENTION_RATE,\n",
    "    COUNT(MONTHS_SINCE_FIRST_PURCHASE) AS CUSTOMER_COUNT\n",
    "FROM \n",
    "    CUSTOMER_COHORT\n",
    "GROUP BY \n",
    "    MONTHS_SINCE_FIRST_PURCHASE\n",
    "\"\"\"\n",
    "retention_rate = pipeline.execute_query(query=query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "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>M</th>\n",
       "      <th>RETENTION_RATE</th>\n",
       "      <th>CUSTOMER_COUNT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>123208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>14.587527</td>\n",
       "      <td>17973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>12.001656</td>\n",
       "      <td>14787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>10.594280</td>\n",
       "      <td>13053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>9.544835</td>\n",
       "      <td>11760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>8.895526</td>\n",
       "      <td>10960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>7.850140</td>\n",
       "      <td>9672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>7.306344</td>\n",
       "      <td>9002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>6.209012</td>\n",
       "      <td>7650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>5.468801</td>\n",
       "      <td>6738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>4.843841</td>\n",
       "      <td>5968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>4.183982</td>\n",
       "      <td>5155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>3.195409</td>\n",
       "      <td>3937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>1.722291</td>\n",
       "      <td>2122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>0.372541</td>\n",
       "      <td>459</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     M  RETENTION_RATE  CUSTOMER_COUNT\n",
       "0    0      100.000000          123208\n",
       "1    1       14.587527           17973\n",
       "2    2       12.001656           14787\n",
       "3    3       10.594280           13053\n",
       "4    4        9.544835           11760\n",
       "5    5        8.895526           10960\n",
       "6    6        7.850140            9672\n",
       "7    7        7.306344            9002\n",
       "8    8        6.209012            7650\n",
       "9    9        5.468801            6738\n",
       "10  10        4.843841            5968\n",
       "11  11        4.183982            5155\n",
       "12  12        3.195409            3937\n",
       "13  13        1.722291            2122\n",
       "14  14        0.372541             459"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retention_rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting retention curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(retention_rate.M, retention_rate.RETENTION_RATE)\n",
    "plt.title(\"Customer Retention Curve\")\n",
    "plt.ylabel(\"Retention Rate\")\n",
    "plt.xlabel(\"Month\")\n",
    "plt.xticks(ticks=retention_rate.M)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "- The customer base is **123,208**. These customers are users who have purchased at least once.\n",
    "- Out of this customer base, the M1 retention rate is **14.59%**. This means that **14.59% of customers (17,973)** return to purchase again one month after their first purchase. Conversely, **more than 80% of customers** do not return to purchase in the first month after their first purchase. Customers **could be encouraged to continue purchasing** after their first purchase, perhaps through discounts for subsequent months, and impproved customer experience.\n",
    "- The maximum customer lifetime is **14 months**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cohort Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "query = \"\"\"\n",
    "SELECT \n",
    "    USERID,\n",
    "    MONTHS_SINCE_FIRST_PURCHASE AS M,\n",
    "    COHORT_DATE AS cohort\n",
    "FROM CUSTOMER_COHORT\n",
    "\"\"\"\n",
    "\n",
    "cohorts_df = pipeline.execute_query(query=query)\n",
    "\n",
    "cohorts_df = (\n",
    "    cohorts_df.groupby([\"cohort\", \"M\"])[[\"USERID\"]]\n",
    "    .nunique()\n",
    "    .assign(\n",
    "        total=lambda x: x.groupby(\"cohort\")[[\"USERID\"]].transform(lambda x: x.iloc[0]),\n",
    "        retention=lambda x: 100 * x.USERID / x.total,\n",
    "    )\n",
    "    .reset_index()\n",
    ")\n",
    "cohorts_df.rename(columns={\"USERID\": \"customer_count\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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>cohort</th>\n",
       "      <th>M</th>\n",
       "      <th>customer_count</th>\n",
       "      <th>total</th>\n",
       "      <th>retention</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>0</td>\n",
       "      <td>4134</td>\n",
       "      <td>4134</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1220</td>\n",
       "      <td>4134</td>\n",
       "      <td>29.511369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>1090</td>\n",
       "      <td>4134</td>\n",
       "      <td>26.366715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>3</td>\n",
       "      <td>849</td>\n",
       "      <td>4134</td>\n",
       "      <td>20.537010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>4</td>\n",
       "      <td>898</td>\n",
       "      <td>4134</td>\n",
       "      <td>21.722303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>1</td>\n",
       "      <td>903</td>\n",
       "      <td>7502</td>\n",
       "      <td>12.036790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>474</td>\n",
       "      <td>7502</td>\n",
       "      <td>6.318315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>0</td>\n",
       "      <td>7123</td>\n",
       "      <td>7123</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>1</td>\n",
       "      <td>531</td>\n",
       "      <td>7123</td>\n",
       "      <td>7.454724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>0</td>\n",
       "      <td>3525</td>\n",
       "      <td>3525</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>120 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         cohort  M  customer_count  total   retention\n",
       "0    2022-09-01  0            4134   4134  100.000000\n",
       "1    2022-09-01  1            1220   4134   29.511369\n",
       "2    2022-09-01  2            1090   4134   26.366715\n",
       "3    2022-09-01  3             849   4134   20.537010\n",
       "4    2022-09-01  4             898   4134   21.722303\n",
       "..          ... ..             ...    ...         ...\n",
       "115  2023-09-01  1             903   7502   12.036790\n",
       "116  2023-09-01  2             474   7502    6.318315\n",
       "117  2023-10-01  0            7123   7123  100.000000\n",
       "118  2023-10-01  1             531   7123    7.454724\n",
       "119  2023-11-01  0            3525   3525  100.000000\n",
       "\n",
       "[120 rows x 5 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohorts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "cohorts_pivot = cohorts_df[[\"cohort\", \"M\", \"retention\"]].pivot(\n",
    "    columns=\"M\", index=\"cohort\"\n",
    ")[\"retention\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.heatmap(cohorts_pivot, cmap=\"crest\", annot=True, fmt=\".1f\")\n",
    "g.axes.xaxis.set_ticks_position(\"top\")\n",
    "plt.title(\"Cohort Retention Chart\")\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Cohort\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "- Retention is sustained after M1. It is crucial to reduce the drop after M0 to increase the likelihood of retaining customers for greater revenue.\n",
    "- The cohort from **September 2022** (2022-09) is the most retained cohort, with retention sustained around **20%** up to M9 (the tenth month).\n",
    "- There was a drop in retention in **December** for the 2022-09 and 2022-10 cohorts. In December, the 2022-09 cohort dropped by about **6%**, and the 2022-10 cohort dropped by about **3%**.\n",
    "- There is a noticeable **4-7% drop** in retention during **November** across all cohorts (see diagonal from cohort 2023-10, M1 to cohort 2022-09, M14). What happens in November? The company could consider strategies such as discounted sales or special offers in October, November, and December to sustain or boost retention.\n",
    "- An increase in retention is observable during the **fall months** (August, September, October). The company could capitalize on this opportunity to boost sales during these months."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customer Lifetime Value "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read customer lifespan, frequency, sales values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "lfs_query = \"SELECT * FROM LIFESPAN_FREQUENCY_SALES\"\n",
    "lfs = pipeline.execute_query(query=lfs_query)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the data types of columns and converting them appropriately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 123210 entries, 0 to 123209\n",
      "Data columns (total 7 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   userId          123210 non-null  int64  \n",
      " 1   COHORT_DATE     123210 non-null  object \n",
      " 2   purchase_month  123210 non-null  object \n",
      " 3   lifespan        123210 non-null  int64  \n",
      " 4   frequency       123210 non-null  int64  \n",
      " 5   currency        123210 non-null  object \n",
      " 6   average_sales   123210 non-null  float64\n",
      "dtypes: float64(1), int64(3), object(3)\n",
      "memory usage: 6.6+ MB\n"
     ]
    }
   ],
   "source": [
    "lfs.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_dtypes(data):\n",
    "    data.rename(columns={\"COHORT_DATE\": \"first_purchase_month\"}, inplace=True)\n",
    "    data[\"userId\"] = data[\"userId\"].astype(\"object\")\n",
    "    data[\"purchase_month\"] = pd.to_datetime(data[\"purchase_month\"])\n",
    "    data[\"first_purchase_month\"] = pd.to_datetime(data[\"first_purchase_month\"])\n",
    "    return data\n",
    "\n",
    "\n",
    "lfs = convert_dtypes(lfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 123210 entries, 0 to 123209\n",
      "Data columns (total 7 columns):\n",
      " #   Column                Non-Null Count   Dtype         \n",
      "---  ------                --------------   -----         \n",
      " 0   userId                123210 non-null  object        \n",
      " 1   first_purchase_month  123210 non-null  datetime64[ns]\n",
      " 2   purchase_month        123210 non-null  datetime64[ns]\n",
      " 3   lifespan              123210 non-null  int64         \n",
      " 4   frequency             123210 non-null  int64         \n",
      " 5   currency              123210 non-null  object        \n",
      " 6   average_sales         123210 non-null  float64       \n",
      "dtypes: datetime64[ns](2), float64(1), int64(2), object(2)\n",
      "memory usage: 6.6+ MB\n"
     ]
    }
   ],
   "source": [
    "lfs.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explore the transaction data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert all **SEK** sales to **Euro** assuming a convertion rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "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>userId</th>\n",
       "      <th>purchase_month</th>\n",
       "      <th>first_purchase_month</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>65326324392533</td>\n",
       "      <td>2023-05-01</td>\n",
       "      <td>2023-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>250.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>168982159910603</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>650.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>219034330643057</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>12.0</td>\n",
       "      <td>3</td>\n",
       "      <td>673.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>271311745575070</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1180.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>327509841715406</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1800.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>332400596016082</td>\n",
       "      <td>2023-04-01</td>\n",
       "      <td>2023-04-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>391633657998574</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>490.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>406087302631582</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1045.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>472654236140424</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1025.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>494869758008189</td>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>2023-04-01</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>688.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            userId purchase_month first_purchase_month  lifespan  frequency  \\\n",
       "0   65326324392533     2023-05-01           2023-05-01       0.0          1   \n",
       "1  168982159910603     2023-08-01           2023-08-01       0.0          1   \n",
       "2  219034330643057     2023-11-01           2022-11-01      12.0          3   \n",
       "3  271311745575070     2022-12-01           2022-12-01       0.0          1   \n",
       "4  327509841715406     2022-10-01           2022-10-01       0.0          1   \n",
       "5  332400596016082     2023-04-01           2023-04-01       0.0          1   \n",
       "6  391633657998574     2022-11-01           2022-11-01       0.0          1   \n",
       "7  406087302631582     2023-08-01           2023-08-01       0.0          2   \n",
       "8  472654236140424     2023-11-01           2023-08-01       3.0          2   \n",
       "9  494869758008189     2023-09-01           2023-04-01       5.0          2   \n",
       "\n",
       "   average_sales_euro  \n",
       "0          250.000000  \n",
       "1          650.000000  \n",
       "2          673.333333  \n",
       "3         1180.000000  \n",
       "4         1800.000000  \n",
       "5          400.000000  \n",
       "6          490.000000  \n",
       "7         1045.000000  \n",
       "8         1025.000000  \n",
       "9          688.000000  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def sek_euro_converter(values):\n",
    "    sek_euro_convertion_rate = 0.088\n",
    "    return (\n",
    "        values[\"average_sales\"] * sek_euro_convertion_rate\n",
    "        if values[\"currency\"] == \"sek\"\n",
    "        else values[\"average_sales\"]\n",
    "    )\n",
    "\n",
    "\n",
    "def convert_currency_and_aggregate(data):\n",
    "    data[\"average_sales_euro\"] = data.apply(\n",
    "        sek_euro_converter,\n",
    "        axis=1,\n",
    "    )\n",
    "    data.drop(columns=[\"currency\", \"average_sales\"], inplace=True)\n",
    "    data = data.groupby(\n",
    "        [\"userId\", \"purchase_month\", \"first_purchase_month\"], as_index=False\n",
    "    ).agg({\"lifespan\": \"mean\", \"frequency\": \"sum\", \"average_sales_euro\": \"mean\"})\n",
    "    return data\n",
    "\n",
    "\n",
    "lfs = convert_currency_and_aggregate(lfs)\n",
    "lfs.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the distributions of lifespan, freqency and average_sales_euros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_dist_plot(var_data, title, ylabel, xlabel):\n",
    "    sns.kdeplot(x=var_data)\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(ylabel)\n",
    "    plt.title(title)\n",
    "    # Show the mean, median, mode and max\n",
    "    plt.axvline(\n",
    "        x=var_data.mean(),\n",
    "        color=\"cyan\",\n",
    "        linestyle=\"dashed\",\n",
    "        linewidth=2,\n",
    "        label=f\"Mean ({var_data.mean():.2f})\",\n",
    "    )\n",
    "    plt.axvline(\n",
    "        x=var_data.median(),\n",
    "        color=\"red\",\n",
    "        linestyle=\"dashed\",\n",
    "        linewidth=2,\n",
    "        label=f\"Median ({var_data.median():.2f})\",\n",
    "    )\n",
    "    plt.axvline(\n",
    "        x=var_data.mode()[0],\n",
    "        color=\"yellow\",\n",
    "        linestyle=\"dashed\",\n",
    "        linewidth=2,\n",
    "        label=f\"Mode ({var_data.mode()[0]:.2f})\",\n",
    "    )\n",
    "    plt.axvline(\n",
    "        x=var_data.max(),\n",
    "        color=\"gray\",\n",
    "        linestyle=\"dashed\",\n",
    "        linewidth=2,\n",
    "        label=f\"Max ({var_data.max()})\",\n",
    "    )\n",
    "    plt.axvline(\n",
    "        x=var_data.min(),\n",
    "        color=\"gray\",\n",
    "        linestyle=\"dashed\",\n",
    "        linewidth=2,\n",
    "        label=f\"Min ({var_data.min()})\",\n",
    "    )\n",
    "    plt.xlim((var_data.min(), var_data.max()))\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_dist_plot(\n",
    "    var_data=lfs[\"average_sales_euro\"],\n",
    "    title=\"Distribution of Average customer sales (Euro)\",\n",
    "    ylabel=\"Proportion of Customers\",\n",
    "    xlabel=\"Average Sales (Euro)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "The distribution of average customer sales is left-skewed. Although the maximum customer sales reach 9,980 euros, the average is 666 euros, with the majority of customers having sales around 500 euros. \n",
    "\n",
    "`Question`\n",
    "\n",
    "The minimum lifetime sales for some customers (4778) is zero. Does this indicate that these orders were free? Customers might have received items through promotions or loyalty programs without direct purchases, leading to zero sales in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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>userId</th>\n",
       "      <th>purchase_month</th>\n",
       "      <th>first_purchase_month</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>5120141954573712</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>2022-12-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>6207944155636470</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>2023-03-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>8039853486500445</td>\n",
       "      <td>2023-06-01</td>\n",
       "      <td>2023-05-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>8423360510494468</td>\n",
       "      <td>2023-02-01</td>\n",
       "      <td>2023-02-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>9292090121837218</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123071</th>\n",
       "      <td>9213804441424331690</td>\n",
       "      <td>2023-07-01</td>\n",
       "      <td>2023-07-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123099</th>\n",
       "      <td>9215015255602677840</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123130</th>\n",
       "      <td>9217410302401760993</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123184</th>\n",
       "      <td>9222211130855761329</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>2022-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123209</th>\n",
       "      <td>9223343504002548352</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4778 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     userId purchase_month first_purchase_month  lifespan  \\\n",
       "58         5120141954573712     2022-12-01           2022-12-01       0.0   \n",
       "74         6207944155636470     2023-03-01           2023-03-01       0.0   \n",
       "100        8039853486500445     2023-06-01           2023-05-01       1.0   \n",
       "106        8423360510494468     2023-02-01           2023-02-01       0.0   \n",
       "119        9292090121837218     2022-11-01           2022-11-01       0.0   \n",
       "...                     ...            ...                  ...       ...   \n",
       "123071  9213804441424331690     2023-07-01           2023-07-01       0.0   \n",
       "123099  9215015255602677840     2022-11-01           2022-11-01       0.0   \n",
       "123130  9217410302401760993     2022-11-01           2022-11-01       0.0   \n",
       "123184  9222211130855761329     2022-11-01           2022-11-01       0.0   \n",
       "123209  9223343504002548352     2023-10-01           2023-10-01       0.0   \n",
       "\n",
       "        frequency  average_sales_euro  \n",
       "58              1                 0.0  \n",
       "74              1                 0.0  \n",
       "100             2                 0.0  \n",
       "106             1                 0.0  \n",
       "119             1                 0.0  \n",
       "...           ...                 ...  \n",
       "123071          2                 0.0  \n",
       "123099          1                 0.0  \n",
       "123130          1                 0.0  \n",
       "123184          1                 0.0  \n",
       "123209          1                 0.0  \n",
       "\n",
       "[4778 rows x 6 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lfs[lfs[\"average_sales_euro\"] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "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>Zero_Sales_Customers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Zero_Sales_Customers\n",
       "0                  4778"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline.execute_query(\n",
    "    \"\"\"SELECT COUNT(*) AS Zero_Sales_Customers\n",
    "FROM (\n",
    "    SELECT userId\n",
    "    FROM orders\n",
    "    GROUP BY userId\n",
    "    HAVING SUM(sales) = 0\n",
    ") \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_dist_plot(\n",
    "    var_data=lfs[\"lifespan\"],\n",
    "    xlabel=\"Lifespan (Months)\",\n",
    "    ylabel=\"Proportion of Customers\",\n",
    "    title=\"Distribution of customer lifespan (Months)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "Similar to the retention curve, the distribution of customer lifespan is right-skewed. The maximum lifespan is 14 months after the first purchase, with an average of 2.54 months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_dist_plot(\n",
    "    var_data=lfs[\"frequency\"],\n",
    "    xlabel=\"Frequency (Counts)\",\n",
    "    ylabel=\"Proportion of Customers\",\n",
    "    title=\"Distribution of customer purchase frequency (Counts)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "While most customers make only one purchase, the average purchase frequency is 2.43, with at least one customer having made 250 purchases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "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>userId</th>\n",
       "      <th>purchase_month</th>\n",
       "      <th>first_purchase_month</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5389</th>\n",
       "      <td>402089433377497830</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>14.0</td>\n",
       "      <td>262</td>\n",
       "      <td>567.198473</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  userId purchase_month first_purchase_month  lifespan  \\\n",
       "5389  402089433377497830     2023-11-01           2022-09-01      14.0   \n",
       "\n",
       "      frequency  average_sales_euro  \n",
       "5389        262          567.198473  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lfs[lfs[\"frequency\"] == 262]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute Customer Lifetime Value\n",
    "Compute **CV** as:\n",
    "$ \\text{Average Frequency} \\times \\text{Average Sales (Euros)}$\n",
    "\n",
    "Compute **CLV** as:\n",
    "$ \\text{CLV} = \\text{Average Lifespan} \\times \\text{Average Frequency} \\times \\text{Average Sales (Euros)}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>userId</th>\n",
       "      <th>purchase_month</th>\n",
       "      <th>first_purchase_month</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "      <th>CV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5389</th>\n",
       "      <td>402089433377497830</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>14.0</td>\n",
       "      <td>262</td>\n",
       "      <td>567.198473</td>\n",
       "      <td>148606.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91485</th>\n",
       "      <td>6836716632121424733</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>14.0</td>\n",
       "      <td>63</td>\n",
       "      <td>856.031746</td>\n",
       "      <td>53930.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69095</th>\n",
       "      <td>5156756655607387559</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>13.0</td>\n",
       "      <td>34</td>\n",
       "      <td>1555.588235</td>\n",
       "      <td>52890.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77438</th>\n",
       "      <td>5786196591665482994</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>2022-09-01</td>\n",
       "      <td>13.0</td>\n",
       "      <td>76</td>\n",
       "      <td>668.421053</td>\n",
       "      <td>50800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26437</th>\n",
       "      <td>1963435673590959229</td>\n",
       "      <td>2023-11-01</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>13.0</td>\n",
       "      <td>39</td>\n",
       "      <td>1171.794872</td>\n",
       "      <td>45700.0</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
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       "      <td>6002307372811900218</td>\n",
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       "      <td>2022-11-01</td>\n",
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       "    <tr>\n",
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       "      <td>2022-10-01</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80370</th>\n",
       "      <td>6002096817342340296</td>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123209</th>\n",
       "      <td>9223343504002548352</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>123210 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     userId purchase_month first_purchase_month  lifespan  \\\n",
       "5389     402089433377497830     2023-11-01           2022-09-01      14.0   \n",
       "91485   6836716632121424733     2023-11-01           2022-09-01      14.0   \n",
       "69095   5156756655607387559     2023-10-01           2022-09-01      13.0   \n",
       "77438   5786196591665482994     2023-10-01           2022-09-01      13.0   \n",
       "26437   1963435673590959229     2023-11-01           2022-10-01      13.0   \n",
       "...                     ...            ...                  ...       ...   \n",
       "41087   3052559157775286154     2022-11-01           2022-11-01       0.0   \n",
       "80374   6002307372811900218     2022-11-01           2022-11-01       0.0   \n",
       "41114   3055220048359771058     2022-10-01           2022-10-01       0.0   \n",
       "80370   6002096817342340296     2023-09-01           2023-09-01       0.0   \n",
       "123209  9223343504002548352     2023-10-01           2023-10-01       0.0   \n",
       "\n",
       "        frequency  average_sales_euro        CV  \n",
       "5389          262          567.198473  148606.0  \n",
       "91485          63          856.031746   53930.0  \n",
       "69095          34         1555.588235   52890.0  \n",
       "77438          76          668.421053   50800.0  \n",
       "26437          39         1171.794872   45700.0  \n",
       "...           ...                 ...       ...  \n",
       "41087           1            0.000000       0.0  \n",
       "80374           1            0.000000       0.0  \n",
       "41114           1            0.000000       0.0  \n",
       "80370           1            0.000000       0.0  \n",
       "123209          1            0.000000       0.0  \n",
       "\n",
       "[123210 rows x 7 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lfs[\"CV\"] = lfs[\"frequency\"] * lfs[\"average_sales_euro\"]\n",
    "customer_clv = lfs.copy()\n",
    "\n",
    "customer_clv.sort_values(by=\"CV\", ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4130.549767444847"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CLV = (\n",
    "    customer_clv[\"lifespan\"].mean()\n",
    "    * customer_clv[\"frequency\"].mean()\n",
    "    * customer_clv[\"average_sales_euro\"].mean()\n",
    ")\n",
    "\n",
    "CLV"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assuming a profit margin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "206.52748837224237"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profit_margin = 0.05\n",
    "CLV * profit_margin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `Now answering the Marketing question`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference\n",
    "\n",
    "- The average customer generates **4,130 euros** in sales.\n",
    "- Assuming a profit margin of **5%**, the profit from an average customer is **206.53 euros**. Therefore, the marketing team should not spend more than **206.53 euros** to acquire a new customer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using probabilistic models to estimate future CLV\n",
    "\n",
    "Given the skewness in customer lifespan, purchase frequency, and average sales, and the fact that the CLV formula uses averages, on historical data, this CLV estimate may not be entirely reliable when looking into the future. Unlike subscription-based models, where retention is more predictable, customers in this case can leave and return at any time. There is the need to explore more advanced methods that leverage customer behavior trends and enable more confident estimation of Customer Lifetime Values (CLVs). This [video](https://www.youtube.com/watch?v=guj2gVEEx4s&ab_channel=FirstMarkCapital) emphasizes the importance of probabilistic modeling for customer behavior in non-subscription-based businesses. \n",
    "\n",
    "\n",
    "The [lifetimes](https://lifetimes.readthedocs.io/en/latest/index.html) marketing science python libraries will be used in these probalistic estimations. We use the **BetaGeoFitter** and **GammaGammaFitter** models in lifetimes package."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computing T (Age of Customer)\n",
    "`T` is the age of customers at the end of the period under study. So in our data, this is the age of the customer in months from first purchase date and the last transation dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "trans_data = lfs.copy()\n",
    "period_end_date = trans_data[\"purchase_month\"].max()\n",
    "\n",
    "trans_data[\"T\"] = trans_data[\"first_purchase_month\"].apply(\n",
    "    lambda x: (period_end_date.to_period(\"M\") - x.to_period(\"M\")).n\n",
    ")\n",
    "trans_data = trans_data[\n",
    "    [\"userId\", \"frequency\", \"lifespan\", \"T\", \"average_sales_euro\", \"CV\"]\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predicting future purchases and probability that the customer is alive\n",
    "\n",
    "The model requires repeat customers only, i.e, customer who purchased again after their first transaction\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>frequency</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>T</th>\n",
       "      <th>average_sales_euro</th>\n",
       "      <th>CV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>219034330643057</th>\n",
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       "      <td>12.0</td>\n",
       "      <td>12</td>\n",
       "      <td>673.333333</td>\n",
       "      <td>2020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472654236140424</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1025.000000</td>\n",
       "      <td>2050.0</td>\n",
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       "    <tr>\n",
       "      <th>494869758008189</th>\n",
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       "      <td>5.0</td>\n",
       "      <td>7</td>\n",
       "      <td>688.000000</td>\n",
       "      <td>1376.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857319303011182</th>\n",
       "      <td>5</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13</td>\n",
       "      <td>556.000000</td>\n",
       "      <td>2780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010263118317948</th>\n",
       "      <td>2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4</td>\n",
       "      <td>850.000000</td>\n",
       "      <td>1700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>9223090445069821952</th>\n",
       "      <td>6</td>\n",
       "      <td>8.0</td>\n",
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       "      <td>983.333333</td>\n",
       "      <td>5900.0</td>\n",
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       "      <td>2</td>\n",
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       "      <td>470.000000</td>\n",
       "      <td>940.0</td>\n",
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       "    <tr>\n",
       "      <th>9223113765943846674</th>\n",
       "      <td>4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9223115497170789549</th>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>626.666667</td>\n",
       "      <td>1880.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9223201399781576886</th>\n",
       "      <td>3</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11</td>\n",
       "      <td>530.000000</td>\n",
       "      <td>1590.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>51558 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     frequency  lifespan   T  average_sales_euro      CV\n",
       "userId                                                                  \n",
       "219034330643057              3      12.0  12          673.333333  2020.0\n",
       "472654236140424              2       3.0   3         1025.000000  2050.0\n",
       "494869758008189              2       5.0   7          688.000000  1376.0\n",
       "857319303011182              5      13.0  13          556.000000  2780.0\n",
       "1010263118317948             2       4.0   4          850.000000  1700.0\n",
       "...                        ...       ...  ..                 ...     ...\n",
       "9223090445069821952          6       8.0  13          983.333333  5900.0\n",
       "9223097207332177627          2       2.0   8          470.000000   940.0\n",
       "9223113765943846674          4       4.0  11          500.000000  2000.0\n",
       "9223115497170789549          3       2.0  10          626.666667  1880.0\n",
       "9223201399781576886          3       8.0  11          530.000000  1590.0\n",
       "\n",
       "[51558 rows x 5 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans_data = trans_data[trans_data.lifespan > 0]\n",
    "trans_data.set_index(\"userId\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lifetimes import BetaGeoFitter\n",
    "from lifetimes.plotting import (\n",
    "    plot_frequency_recency_matrix,\n",
    "    plot_probability_alive_matrix,\n",
    "    plot_period_transactions,\n",
    ")\n",
    "\n",
    "# penalizer_coef hyperparameter tunning\n",
    "def best_penalizer_coef(min_r=0.9):\n",
    "    param_space = np.linspace(0.001, 1)\n",
    "    r2_values = pd.DataFrame()\n",
    "    for p in param_space:\n",
    "        beta_geo = BetaGeoFitter(penalizer_coef=p)\n",
    "        beta_geo.fit(\n",
    "            frequency=trans_data[\"frequency\"],\n",
    "            recency=trans_data[\"lifespan\"],\n",
    "            T=trans_data[\"T\"],\n",
    "        )\n",
    "        r = beta_geo.summary.loc[\"r\", \"coef\"]\n",
    "        print(f\"penalizer_coef {p}, r {r}\")\n",
    "        r2_values = pd.concat(\n",
    "            [r2_values, pd.DataFrame({\"penalizer_coef\": [p], \"r\": [r]})], ignore_index=True\n",
    "        )\n",
    "\n",
    "        if r<=min_r:\n",
    "            break\n",
    "\n",
    "    r2_values.set_index(\"penalizer_coef\", inplace=True)\n",
    "    return [r2_values.idxmin().values[0] , r2_values]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "penalizer_coef 0.001, r 3.32099113597663\n",
      "penalizer_coef 0.021387755102040818, r 1.799377213497318\n",
      "penalizer_coef 0.041775510204081635, r 1.475567229727938\n",
      "penalizer_coef 0.062163265306122456, r 1.301089174744519\n",
      "penalizer_coef 0.08255102040816327, r 1.1853888497715033\n",
      "penalizer_coef 0.10293877551020408, r 1.1005488272308692\n",
      "penalizer_coef 0.12332653061224491, r 1.0344773987823646\n",
      "penalizer_coef 0.1437142857142857, r 0.9809073147223525\n",
      "penalizer_coef 0.16410204081632654, r 0.9361984785410343\n",
      "penalizer_coef 0.18448979591836737, r 0.8980620649053187\n",
      "penalizer_coef 0.20487755102040817, r 0.8649727473788379\n",
      "penalizer_coef 0.225265306122449, r 0.8358660325521727\n",
      "penalizer_coef 0.24565306122448982, r 0.8099730116146143\n",
      "penalizer_coef 0.26604081632653065, r 0.7867205746351674\n",
      "penalizer_coef 0.2864285714285714, r 0.7656718113062092\n",
      "penalizer_coef 0.30681632653061225, r 0.7464863593435774\n",
      "penalizer_coef 0.3272040816326531, r 0.7288944038121647\n",
      "penalizer_coef 0.3475918367346939, r 0.7126787448343971\n",
      "penalizer_coef 0.36797959183673473, r 0.6976621786990943\n"
     ]
    }
   ],
   "source": [
    "penalizer_coef, result = best_penalizer_coef(min_r=0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(result.index, result[\"r\"])\n",
    "plt.title(\"L2 Normalization (penalizer_coef) hyperparameter tunning\")\n",
    "plt.xlabel(\"L2 Normalization (penalizer_coef)\")\n",
    "plt.ylabel(\"Coefficient of Determination (R)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.36797959183673473"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "penalizer_coef"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "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>coef</th>\n",
       "      <th>se(coef)</th>\n",
       "      <th>lower 95% bound</th>\n",
       "      <th>upper 95% bound</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>r</th>\n",
       "      <td>0.697662</td>\n",
       "      <td>0.003119</td>\n",
       "      <td>0.691549</td>\n",
       "      <td>0.703775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>1.040423</td>\n",
       "      <td>0.008289</td>\n",
       "      <td>1.024177</td>\n",
       "      <td>1.056668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0.064063</td>\n",
       "      <td>0.001160</td>\n",
       "      <td>0.061790</td>\n",
       "      <td>0.066337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>0.390233</td>\n",
       "      <td>0.003604</td>\n",
       "      <td>0.383170</td>\n",
       "      <td>0.397296</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           coef  se(coef)  lower 95% bound  upper 95% bound\n",
       "r      0.697662  0.003119         0.691549         0.703775\n",
       "alpha  1.040423  0.008289         1.024177         1.056668\n",
       "a      0.064063  0.001160         0.061790         0.066337\n",
       "b      0.390233  0.003604         0.383170         0.397296"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "bgf = BetaGeoFitter(penalizer_coef=penalizer_coef)\n",
    "bgf.fit(\n",
    "    frequency=trans_data[\"frequency\"], recency=trans_data[\"lifespan\"], T=trans_data[\"T\"]\n",
    ")\n",
    "bgf.summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_unit = 1\n",
    "plot_frequency_recency_matrix(bgf, T=time_unit)\n",
    "plt.title(\n",
    "    f\"Expected Number of Future Purchases for {time_unit} month  \\n by Frequency and Lifespan of a Customer\"\n",
    ")\n",
    "plt.ylabel(\"Customer's Lifespan\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "- Customers who made 100 or more purchases by their 14th month with the company are likely to make 8 to 16 purchases in the following month. \n",
    "\n",
    "- Customers who made 25 to 100 purchases recently (between months 10 and 13) are likely to make 2 to 5 purchases next month. However, we do not know the probability that these customers will be alive (with next month). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_probability_alive_matrix(bgf)\n",
    "plt.title(\n",
    "    f\"Probability that Customer is Alive, \\n by Frequency and Lifespan of a Customer\"\n",
    ")\n",
    "plt.ylabel(\"Customer's Lifespan\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "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>userId</th>\n",
       "      <th>frequency</th>\n",
       "      <th>lifespan</th>\n",
       "      <th>T</th>\n",
       "      <th>average_sales_euro</th>\n",
       "      <th>CV</th>\n",
       "      <th>predict_purchases_next_1_m</th>\n",
       "      <th>predict_probability_alive</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5389</th>\n",
       "      <td>402089433377497830</td>\n",
       "      <td>262</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14</td>\n",
       "      <td>567.198473</td>\n",
       "      <td>148606.0</td>\n",
       "      <td>16.743371</td>\n",
       "      <td>0.999504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6718</th>\n",
       "      <td>497424748271724727</td>\n",
       "      <td>95</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13</td>\n",
       "      <td>333.789474</td>\n",
       "      <td>31710.0</td>\n",
       "      <td>6.526133</td>\n",
       "      <td>0.998632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53342</th>\n",
       "      <td>3959435739687960670</td>\n",
       "      <td>72</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11</td>\n",
       "      <td>623.333333</td>\n",
       "      <td>44880.0</td>\n",
       "      <td>5.743214</td>\n",
       "      <td>0.998194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5963</th>\n",
       "      <td>444730773991424385</td>\n",
       "      <td>54</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9</td>\n",
       "      <td>352.962963</td>\n",
       "      <td>19060.0</td>\n",
       "      <td>5.134769</td>\n",
       "      <td>0.997590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45773</th>\n",
       "      <td>3405990330003900548</td>\n",
       "      <td>17</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>191.176471</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>4.848680</td>\n",
       "      <td>0.992298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31378</th>\n",
       "      <td>2333573918598501663</td>\n",
       "      <td>70</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13</td>\n",
       "      <td>467.785714</td>\n",
       "      <td>32745.0</td>\n",
       "      <td>4.826127</td>\n",
       "      <td>0.998142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74554</th>\n",
       "      <td>5569149071209566419</td>\n",
       "      <td>65</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13</td>\n",
       "      <td>331.153846</td>\n",
       "      <td>21525.0</td>\n",
       "      <td>4.486122</td>\n",
       "      <td>0.997999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122945</th>\n",
       "      <td>9204248135457745700</td>\n",
       "      <td>65</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13</td>\n",
       "      <td>389.384615</td>\n",
       "      <td>25310.0</td>\n",
       "      <td>4.486122</td>\n",
       "      <td>0.997999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103802</th>\n",
       "      <td>7763147301647778346</td>\n",
       "      <td>47</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9</td>\n",
       "      <td>473.829787</td>\n",
       "      <td>22270.0</td>\n",
       "      <td>4.480870</td>\n",
       "      <td>0.997230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55732</th>\n",
       "      <td>4144786482233488865</td>\n",
       "      <td>68</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14</td>\n",
       "      <td>227.500000</td>\n",
       "      <td>15470.0</td>\n",
       "      <td>4.391507</td>\n",
       "      <td>0.998087</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     userId  frequency  lifespan   T  average_sales_euro  \\\n",
       "5389     402089433377497830        262      14.0  14          567.198473   \n",
       "6718     497424748271724727         95      13.0  13          333.789474   \n",
       "53342   3959435739687960670         72      11.0  11          623.333333   \n",
       "5963     444730773991424385         54       9.0   9          352.962963   \n",
       "45773   3405990330003900548         17       2.0   2          191.176471   \n",
       "31378   2333573918598501663         70      13.0  13          467.785714   \n",
       "74554   5569149071209566419         65      13.0  13          331.153846   \n",
       "122945  9204248135457745700         65      13.0  13          389.384615   \n",
       "103802  7763147301647778346         47       9.0   9          473.829787   \n",
       "55732   4144786482233488865         68      14.0  14          227.500000   \n",
       "\n",
       "              CV  predict_purchases_next_1_m  predict_probability_alive  \n",
       "5389    148606.0                   16.743371                   0.999504  \n",
       "6718     31710.0                    6.526133                   0.998632  \n",
       "53342    44880.0                    5.743214                   0.998194  \n",
       "5963     19060.0                    5.134769                   0.997590  \n",
       "45773     3250.0                    4.848680                   0.992298  \n",
       "31378    32745.0                    4.826127                   0.998142  \n",
       "74554    21525.0                    4.486122                   0.997999  \n",
       "122945   25310.0                    4.486122                   0.997999  \n",
       "103802   22270.0                    4.480870                   0.997230  \n",
       "55732    15470.0                    4.391507                   0.998087  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans_data[\"predict_purchases_next_1_m\"] = (\n",
    "    bgf.conditional_expected_number_of_purchases_up_to_time(\n",
    "        t=time_unit,\n",
    "        frequency=trans_data[\"frequency\"],\n",
    "        recency=trans_data[\"lifespan\"],\n",
    "        T=trans_data[\"T\"],\n",
    "    )\n",
    ")\n",
    "trans_data[\"predict_probability_alive\"] = bgf.conditional_probability_alive(\n",
    "    frequency=trans_data[\"frequency\"], recency=trans_data[\"lifespan\"], T=trans_data[\"T\"]\n",
    ")\n",
    "trans_data.sort_values(by=\"predict_purchases_next_1_m\", ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Frequency of Repeat Transactions'}, xlabel='Number of Calibration Period Transactions', ylabel='Customers'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_period_transactions(bgf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predicting future sales of customer for CLV\n",
    "The model assumes that\n",
    "*  Customer are repeat customers only, i.e, customer who purchased again after their first transaction\n",
    "* The frequency and average_sales_euro are not (strongly) correlated,  \n",
    "* All monetary values are greater than zero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "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>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>frequency</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.081475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>average_sales_euro</th>\n",
       "      <td>-0.081475</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    frequency  average_sales_euro\n",
       "frequency            1.000000           -0.081475\n",
       "average_sales_euro  -0.081475            1.000000"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans_data = trans_data[trans_data[\"average_sales_euro\"] > 0]\n",
    "trans_data.set_index(\"userId\")\n",
    "trans_data[[\"frequency\", \"average_sales_euro\"]].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<lifetimes.BetaGeoFitter: fitted with 51409 subjects, a: 0.13, alpha: 1.64, b: 0.72, r: 1.11>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from lifetimes import GammaGammaFitter\n",
    "\n",
    "ggf = GammaGammaFitter(penalizer_coef=0)\n",
    "ggf.fit(trans_data[\"frequency\"], trans_data[\"average_sales_euro\"])\n",
    "\n",
    "bgf.fit(\n",
    "    frequency=trans_data[\"frequency\"], recency=trans_data[\"lifespan\"], T=trans_data[\"T\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "look_forward_months = 6\n",
    "trans_data[\"predicted_CLV\"] = ggf.customer_lifetime_value(\n",
    "    bgf,  # the model to use to predict the number of future transactions\n",
    "    trans_data[\"frequency\"],\n",
    "    trans_data[\"lifespan\"],\n",
    "    trans_data[\"T\"],\n",
    "    trans_data[\"average_sales_euro\"],\n",
    "    time=look_forward_months,\n",
    "    discount_rate=0.0,\n",
    "    freq=\"M\",\n",
    ")\n",
    "predicted_CLV = trans_data[\"predicted_CLV\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting from 2023-11-01, the predicted CLV for 6 months is 1417.62 euros\n",
      "Assuming a profit margin of 5.0 percent, the profit from an average customer is 70.88 euros. \n",
      "Therefore, the marketing team should not spend more than 70.88 to acquire a new customer within the next 6 months.\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    f\"Starting from {period_end_date.strftime('%Y-%m-%d')}, the predicted CLV for {look_forward_months} months is {predicted_CLV:.2f} euros\"\n",
    ")\n",
    "print(\n",
    "    f\"Assuming a profit margin of {profit_margin*100} percent, the profit from an average customer is {predicted_CLV*profit_margin:.2f} euros. \\nTherefore, the marketing team should not spend more than {predicted_CLV*profit_margin:.2f} to acquire a new customer within the next {look_forward_months} months.\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `More answers for the Marketing question`\n",
    "\n",
    "The marketing team can predict the CLV for the entire customer base over a given time frame. Starting from 2023-11-01, the predicted CLV for the next 6 months is 1,417.62 euros. Assuming a profit margin of 5%, the expected profit from an average customer is 70.88 euros. Therefore, the marketing team should not spend more than 70.88 euros to acquire a new customer over the next 6 months."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While probabilistic models may provide more accurate CLV calculations, they can still be fine-tuned using cross-validation, as explained in the [Lifetimes model guide](https://lifetimes.readthedocs.io/en/latest/Quickstart.html#more-model-fitting)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Machine Learning\n",
    "\n",
    "The marketing team now has a good understanding of both historical and future CLV. The next step is to analyze customer behaviors that may influence CLV. How much will customers purchase in the future, and what is the probability that they will continue to buy? With machine learning predictive analysis, the marketing team can predict the CLV of new customer who starts purchasing from the company. Additionally, identifying the top customers for the next prediction window allows the marketting team to target them strategically to boost sales.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load and transform data \n",
    "\n",
    "To predict future customer behavior, transactions from any time before the past 90 days will be used to engineer features, while transactions within the last 90 days will be used to engineer targets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "last_trans_date = pd.to_datetime(\n",
    "    pipeline.execute_query(\n",
    "        \"SELECT MAX(DATE(CREATEDAT)) LAST_TRANS_DATE FROM ORDERS\"\n",
    "    ).loc[0, \"LAST_TRANS_DATE\"]\n",
    ")\n",
    "cut_off_90_date = last_trans_date - pd.to_timedelta(90, unit=\"d\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The queries below are similar to `LIFESPAN_FREQUENCY_SALES` View in the database. However, SQLite does not support parameters in views or provide native support for stored procedures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "past_transations_query = \"\"\"\n",
    "    WITH FIRSTORDERDATES AS (\n",
    "            SELECT \n",
    "                USERID, \n",
    "                strftime('%Y-%m-01', MIN(DATE(CREATEDAT)))  AS COHORT_DATE\n",
    "            FROM ORDERS\n",
    "            GROUP BY USERID\n",
    "        )\n",
    "\n",
    "    SELECT \n",
    "        O.USERID,\n",
    "        FOD.COHORT_DATE,\n",
    "        strftime('%Y-%m-01', MAX(DATE(CREATEDAT)))  AS purchase_month,\n",
    "        ((strftime('%Y', MAX(DATE(CREATEDAT))) - strftime('%Y', FOD.COHORT_DATE)) * 12) + (strftime('%m', MAX(DATE(CREATEDAT))) - strftime('%m', FOD.COHORT_DATE)) as lifespan,\n",
    "        COUNT(O.SALES) AS frequency,\n",
    "        O.currency,\n",
    "        AVG(O.SALES) AS average_sales\n",
    "    FROM ORDERS O\n",
    "    LEFT JOIN FIRSTORDERDATES FOD ON O.USERID = FOD.USERID\n",
    "    WHERE O.CREATEDAT<?\n",
    "    GROUP BY O.USERID, O.currency\n",
    "\"\"\"\n",
    "past_ml_data = pipeline.execute_query(\n",
    "    query=past_transations_query, param=(cut_off_90_date.strftime(\"%Y-%m-%d\"),)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "future_transations_query = \"\"\"\n",
    "    WITH FIRSTORDERDATES AS (\n",
    "            SELECT \n",
    "                USERID, \n",
    "                strftime('%Y-%m-01', MIN(DATE(CREATEDAT)))  AS COHORT_DATE\n",
    "            FROM ORDERS\n",
    "            GROUP BY USERID\n",
    "        )\n",
    "\n",
    "    SELECT \n",
    "        O.USERID,\n",
    "        FOD.COHORT_DATE,\n",
    "        strftime('%Y-%m-01', MAX(DATE(CREATEDAT)))  AS purchase_month,\n",
    "        ((strftime('%Y', MAX(DATE(CREATEDAT))) - strftime('%Y', FOD.COHORT_DATE)) * 12) + (strftime('%m', MAX(DATE(CREATEDAT))) - strftime('%m', FOD.COHORT_DATE)) as lifespan,\n",
    "        COUNT(O.SALES) AS frequency,\n",
    "        O.currency,\n",
    "        AVG(O.SALES) AS average_sales\n",
    "    FROM ORDERS O\n",
    "    LEFT JOIN FIRSTORDERDATES FOD ON O.USERID = FOD.USERID\n",
    "    WHERE O.CREATEDAT>=?\n",
    "    GROUP BY O.USERID, O.currency\n",
    "\"\"\"\n",
    "future_ml_data = pipeline.execute_query(\n",
    "    query=future_transations_query, param=(cut_off_90_date.strftime(\"%Y-%m-%d\"),)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert purchases in SEK to EURO assuming a conversion rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "past_ml_data = convert_dtypes(past_ml_data)\n",
    "past_ml_data = convert_currency_and_aggregate(past_ml_data)\n",
    "past_ml_data.set_index(\"userId\", inplace=True)\n",
    "\n",
    "future_ml_data = convert_dtypes(future_ml_data)\n",
    "future_ml_data = convert_currency_and_aggregate(future_ml_data)\n",
    "future_ml_data.set_index(\"userId\", inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**`Age`** is the number of months that have elapsed since the customer's first purchase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "past_ml_data[\"customer_age\"] = past_ml_data[\"first_purchase_month\"].apply(\n",
    "    lambda x: (last_trans_date.to_period(\"M\") - x.to_period(\"M\")).n\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**`Total sales`** is the sum of the sales of the customer, computed as $ \\text{Frequency} \\times \\text{Average Sales (Euros)}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "past_ml_data[\"total_sales\"] = (\n",
    "    past_ml_data[\"frequency\"] * past_ml_data[\"average_sales_euro\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**`Recency`** indicates how recent (in months) the customer's last purchase is. The most recent purchases have a recency of zero, while older transactions have negative recency values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "past_ml_data[\"recency\"] = past_ml_data[\"purchase_month\"].apply(\n",
    "    lambda x: (x.to_period(\"M\") - last_trans_date.to_period(\"M\")).n\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**`sales_2weeks_avg`** is the average sales from a customer's transactions within the last two weeks.  \n",
    "\n",
    "**`transaction_2weeks_count`** indicates the number of customer's transactions that occurred within the last two weeks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "cut_off_2weeks_date = past_ml_data[\"purchase_month\"].max() - pd.to_timedelta(\n",
    "    14, unit=\"d\"\n",
    ")\n",
    "\n",
    "sales_2weeks_features = (\n",
    "    past_ml_data[past_ml_data[\"purchase_month\"] >= cut_off_2weeks_date]\n",
    "    .groupby([\"userId\"])\n",
    "    .agg(\n",
    "        sales_2weeks_avg=(\"average_sales_euro\", \"mean\"),\n",
    "        transaction_2weeks_count=(\"average_sales_euro\", \"count\"),\n",
    "    )\n",
    ")\n",
    "\n",
    "past_ml_data = past_ml_data.merge(\n",
    "    sales_2weeks_features, left_index=True, right_index=True, how=\"left\"\n",
    ").fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Targets**\n",
    "\n",
    "**`sales_next_90_avg`** is the average sales of a customer in the next 90 days. \n",
    " \n",
    "**`sales_next_90_flag`** indicates whether the customer is will make purchases in the next 90 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales_next_90_features = (\n",
    "    future_ml_data.groupby([\"userId\"])\n",
    "    .agg(sales_next_90_avg=(\"average_sales_euro\", \"mean\"))\n",
    "    .assign(sales_next_90_flag=1)\n",
    ")\n",
    "\n",
    "\n",
    "ml_df = past_ml_data.merge(\n",
    "    sales_next_90_features, left_index=True, right_index=True, how=\"left\"\n",
    ").fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Correlation between all features and targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(ml_df.corr(), cmap=\"crest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ml_df[\n",
    "    [\n",
    "        \"frequency\",\n",
    "        \"average_sales_euro\",\n",
    "        \"customer_age\",\n",
    "        \"recency\",\n",
    "        \"sales_2weeks_avg\",\n",
    "        \"transaction_2weeks_count\",\n",
    "    ]\n",
    "]\n",
    "reg_target = ml_df[\"sales_next_90_avg\"]\n",
    "class_target = ml_df[\"sales_next_90_flag\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Regression and Classification modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "from xgboost import XGBRegressor, XGBClassifier\n",
    "from sklearn.model_selection import KFold, GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best set of hyperparameters:  {'learning_rate': 0.01, 'max_depth': 5, 'n_estimators': 1000, 'subsample': 0.7}\n",
      "Best Mean MAE:216.799\n"
     ]
    }
   ],
   "source": [
    "regressor = XGBRegressor()\n",
    "param_grid = {\n",
    "    \"max_depth\": [3, 5, 7],\n",
    "    \"learning_rate\": [0.1, 0.01, 0.001],\n",
    "    \"subsample\": [0.5, 0.7, 1],\n",
    "    \"n_estimators\": [50, 100, 1000],\n",
    "}\n",
    "\n",
    "grid_search_reg = GridSearchCV(\n",
    "    estimator=regressor,\n",
    "    param_grid=param_grid,\n",
    "    cv=KFold(n_splits=10),\n",
    "    scoring=\"neg_mean_absolute_error\",\n",
    ")\n",
    "\n",
    "grid_search_reg.fit(X=features, y=reg_target)\n",
    "# Print the best set of hyperparameters and the corresponding score\n",
    "print(\"Best set of hyperparameters: \", grid_search_reg.best_params_)\n",
    "print(f\"Best Mean MAE:{np.absolute(grid_search_reg.best_score_):.3f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_sale_next_90_avg = grid_search_reg.best_estimator_.predict(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x390 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import shap\n",
    "\n",
    "explainer_reg = shap.TreeExplainer(grid_search_reg.best_estimator_)\n",
    "explanation_reg = explainer_reg(features)\n",
    "shap_values_reg = explanation_reg.values\n",
    "shap.plots.beeswarm(explanation_reg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "* The regression model can predict the average sales for the next 90 days with a margin of plus or minus 200 euros.\n",
    "* The predicted average sales next 90 days is impacted by Frequency of puchase, average sales in the past, and recency of the purchase. More frequent buyers are with higher averages sales in the past and more recent transactions are expected to contribute to higher average sales in the next 90 days.\n",
    "* Customer age and transactions in the last two weeks do not show a clear relationship with their average sales in the next 90 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best set of hyperparameters:  {'learning_rate': 0.01, 'max_depth': 3, 'n_estimators': 1000, 'subsample': 0.5}\n",
      "Best AUC:71.97\n"
     ]
    }
   ],
   "source": [
    "classifier = XGBClassifier()\n",
    "\n",
    "grid_search_cls = GridSearchCV(\n",
    "    estimator=classifier,\n",
    "    param_grid=param_grid,\n",
    "    cv=KFold(n_splits=10),\n",
    "    scoring=\"roc_auc\",\n",
    ")\n",
    "\n",
    "grid_search_cls.fit(X=features, y=class_target)\n",
    "# Print the best set of hyperparameters and the corresponding score\n",
    "print(\"Best set of hyperparameters: \", grid_search_cls.best_params_)\n",
    "print(f\"Best AUC:{np.absolute(grid_search_cls.best_score_)*100:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_proba_sale_next_90 = grid_search_cls.best_estimator_.predict_proba(features)[:, 1]\n",
    "pred_sale_next_90_flag = grid_search_cls.best_estimator_.predict(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x390 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "explainer_cls = shap.TreeExplainer(grid_search_cls.best_estimator_)\n",
    "explanation_cls = explainer_cls(features)\n",
    "shap_values_cls = explanation_cls.values\n",
    "shap.plots.beeswarm(explanation_cls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "* The model can predict the probability of a customer purchasing in the next 90 days with high accuracy ( AUC of 71.97 %)\n",
    "* Frequency, recency of transactions, and customer age influence the probability of a customer making a purchase in the next 90 days.\n",
    "* Older customers who have not purchased recently or have made fewer purchases in the past are less likely to make a purchase in the next 90 days. Conversely, newer customers with a high frequency of purchases and more recent transactions are more likely to make a purchase in the next 90 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge predictions into features\n",
    "final_table = features.copy()\n",
    "final_table[\"pred_sale_next_90_avg\"] = pred_sale_next_90_avg\n",
    "final_table[\"pred_proba_sale_next_90\"] = pred_proba_sale_next_90\n",
    "final_table.sort_values(by=[\"pred_sale_next_90_avg\"], ascending=False, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `More answers for the Marketing team`\n",
    "\n",
    "#### Top customers with the high probability of purchase in the next 90 days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Top customers with the high probability of purchase in the next 90 days\n",
    "top_n = 50\n",
    "prob_threshold = 0.5\n",
    "sale_threshold = 0.0\n",
    "final_table = final_table[\n",
    "    (final_table[\"pred_proba_sale_next_90\"] >= prob_threshold)\n",
    "    & (final_table[\"pred_sale_next_90_avg\"] > sale_threshold)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>average_sales_euro</th>\n",
       "      <th>customer_age</th>\n",
       "      <th>recency</th>\n",
       "      <th>sales_2weeks_avg</th>\n",
       "      <th>transaction_2weeks_count</th>\n",
       "      <th>pred_sale_next_90_avg</th>\n",
       "      <th>pred_proba_sale_next_90</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>userId</th>\n",
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       "      <td>1246.215385</td>\n",
       "      <td>13</td>\n",
       "      <td>-5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1550.748901</td>\n",
       "      <td>0.821302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7803134376982934048</th>\n",
       "      <td>7</td>\n",
       "      <td>2128.571429</td>\n",
       "      <td>10</td>\n",
       "      <td>-6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1481.502686</td>\n",
       "      <td>0.601594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7308564510325687140</th>\n",
       "      <td>8</td>\n",
       "      <td>1621.250000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1621.250000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1463.014648</td>\n",
       "      <td>0.771856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5200083858774336444</th>\n",
       "      <td>7</td>\n",
       "      <td>1828.571429</td>\n",
       "      <td>10</td>\n",
       "      <td>-3</td>\n",
       "      <td>1828.571429</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1411.716309</td>\n",
       "      <td>0.754674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8597323003979209507</th>\n",
       "      <td>5</td>\n",
       "      <td>1521.400000</td>\n",
       "      <td>14</td>\n",
       "      <td>-3</td>\n",
       "      <td>1521.400000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1403.780640</td>\n",
       "      <td>0.647607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6146852045155325256</th>\n",
       "      <td>19</td>\n",
       "      <td>1262.631579</td>\n",
       "      <td>12</td>\n",
       "      <td>-3</td>\n",
       "      <td>1262.631579</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1373.659546</td>\n",
       "      <td>0.945909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1831167567366470988</th>\n",
       "      <td>8</td>\n",
       "      <td>1563.750000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1563.750000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1368.064941</td>\n",
       "      <td>0.779405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8979193897949196807</th>\n",
       "      <td>14</td>\n",
       "      <td>1276.428571</td>\n",
       "      <td>11</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1347.848145</td>\n",
       "      <td>0.879501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3521480400409139935</th>\n",
       "      <td>5</td>\n",
       "      <td>1490.000000</td>\n",
       "      <td>14</td>\n",
       "      <td>-3</td>\n",
       "      <td>1490.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1315.843750</td>\n",
       "      <td>0.651798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5156756655607387559</th>\n",
       "      <td>29</td>\n",
       "      <td>1587.931034</td>\n",
       "      <td>14</td>\n",
       "      <td>-3</td>\n",
       "      <td>1587.931034</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1313.896484</td>\n",
       "      <td>0.969881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963435673590959229</th>\n",
       "      <td>36</td>\n",
       "      <td>1126.388889</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1126.388889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1305.043213</td>\n",
       "      <td>0.966832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1331175590391651538</th>\n",
       "      <td>13</td>\n",
       "      <td>1175.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1175.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1276.578979</td>\n",
       "      <td>0.894410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6687871536716425521</th>\n",
       "      <td>7</td>\n",
       "      <td>1521.428571</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1521.428571</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1245.581787</td>\n",
       "      <td>0.775205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6373299565216195981</th>\n",
       "      <td>17</td>\n",
       "      <td>1307.647059</td>\n",
       "      <td>14</td>\n",
       "      <td>-6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1221.598755</td>\n",
       "      <td>0.814031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1836974674558095944</th>\n",
       "      <td>7</td>\n",
       "      <td>1833.571429</td>\n",
       "      <td>13</td>\n",
       "      <td>-6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1183.433594</td>\n",
       "      <td>0.621441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2106762733770992846</th>\n",
       "      <td>13</td>\n",
       "      <td>1288.461538</td>\n",
       "      <td>12</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1166.275513</td>\n",
       "      <td>0.871106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411994089603024641</th>\n",
       "      <td>7</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>-3</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1154.708374</td>\n",
       "      <td>0.748352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1678093046687605731</th>\n",
       "      <td>13</td>\n",
       "      <td>1611.538462</td>\n",
       "      <td>14</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1142.273926</td>\n",
       "      <td>0.863502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8727933238807787543</th>\n",
       "      <td>8</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1125.335938</td>\n",
       "      <td>0.663820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7632974522149307827</th>\n",
       "      <td>7</td>\n",
       "      <td>1342.857143</td>\n",
       "      <td>9</td>\n",
       "      <td>-3</td>\n",
       "      <td>1342.857143</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1119.358521</td>\n",
       "      <td>0.785456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4348801244420142027</th>\n",
       "      <td>11</td>\n",
       "      <td>2090.909091</td>\n",
       "      <td>10</td>\n",
       "      <td>-5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1113.779053</td>\n",
       "      <td>0.764217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>768100758869037150</th>\n",
       "      <td>7</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1094.936157</td>\n",
       "      <td>0.698191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8909814062220489386</th>\n",
       "      <td>5</td>\n",
       "      <td>1700.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1700.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1088.679810</td>\n",
       "      <td>0.635806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4061843065023891403</th>\n",
       "      <td>12</td>\n",
       "      <td>1152.500000</td>\n",
       "      <td>14</td>\n",
       "      <td>-3</td>\n",
       "      <td>1152.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1076.770142</td>\n",
       "      <td>0.881060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>723513955432389419</th>\n",
       "      <td>7</td>\n",
       "      <td>1492.857143</td>\n",
       "      <td>11</td>\n",
       "      <td>-3</td>\n",
       "      <td>1492.857143</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1055.413086</td>\n",
       "      <td>0.780544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3860687727043786122</th>\n",
       "      <td>18</td>\n",
       "      <td>1405.555556</td>\n",
       "      <td>13</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1039.830322</td>\n",
       "      <td>0.934487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3274241785415673531</th>\n",
       "      <td>8</td>\n",
       "      <td>1426.250000</td>\n",
       "      <td>11</td>\n",
       "      <td>-3</td>\n",
       "      <td>1426.250000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1039.507080</td>\n",
       "      <td>0.755479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294301877040040480</th>\n",
       "      <td>13</td>\n",
       "      <td>1341.923077</td>\n",
       "      <td>12</td>\n",
       "      <td>-3</td>\n",
       "      <td>1341.923077</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1034.674927</td>\n",
       "      <td>0.916613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8622151806657300217</th>\n",
       "      <td>20</td>\n",
       "      <td>1177.750000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1177.750000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1034.375122</td>\n",
       "      <td>0.964121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2374751365343554912</th>\n",
       "      <td>20</td>\n",
       "      <td>1176.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-5</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1033.990234</td>\n",
       "      <td>0.913789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5052340629890545130</th>\n",
       "      <td>15</td>\n",
       "      <td>1493.666667</td>\n",
       "      <td>13</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1031.351074</td>\n",
       "      <td>0.928793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459476809824996220</th>\n",
       "      <td>16</td>\n",
       "      <td>1231.450000</td>\n",
       "      <td>13</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1029.883545</td>\n",
       "      <td>0.935819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6547979762166587770</th>\n",
       "      <td>7</td>\n",
       "      <td>1317.142857</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1317.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1023.889709</td>\n",
       "      <td>0.740971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6960670268974794018</th>\n",
       "      <td>8</td>\n",
       "      <td>1245.000000</td>\n",
       "      <td>10</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.955505</td>\n",
       "      <td>0.691235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2994401254952486734</th>\n",
       "      <td>6</td>\n",
       "      <td>2063.333333</td>\n",
       "      <td>12</td>\n",
       "      <td>-6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1011.935425</td>\n",
       "      <td>0.521455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3210374918718909087</th>\n",
       "      <td>8</td>\n",
       "      <td>1135.000000</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1135.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1004.344482</td>\n",
       "      <td>0.747968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5829395833302970485</th>\n",
       "      <td>16</td>\n",
       "      <td>1155.937500</td>\n",
       "      <td>13</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000.034546</td>\n",
       "      <td>0.936553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6680854331401630563</th>\n",
       "      <td>12</td>\n",
       "      <td>1564.166667</td>\n",
       "      <td>13</td>\n",
       "      <td>-4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>992.844238</td>\n",
       "      <td>0.863674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125587389245608054</th>\n",
       "      <td>9</td>\n",
       "      <td>1122.222222</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1122.222222</td>\n",
       "      <td>1.0</td>\n",
       "      <td>990.943848</td>\n",
       "      <td>0.787598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2759751677286287812</th>\n",
       "      <td>8</td>\n",
       "      <td>1183.750000</td>\n",
       "      <td>12</td>\n",
       "      <td>-3</td>\n",
       "      <td>1183.750000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>973.400085</td>\n",
       "      <td>0.729857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8015847651155022352</th>\n",
       "      <td>9</td>\n",
       "      <td>1146.666667</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1146.666667</td>\n",
       "      <td>1.0</td>\n",
       "      <td>963.943481</td>\n",
       "      <td>0.787429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374525967619359164</th>\n",
       "      <td>7</td>\n",
       "      <td>1814.285714</td>\n",
       "      <td>14</td>\n",
       "      <td>-6</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>957.167603</td>\n",
       "      <td>0.592425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5449281706118422564</th>\n",
       "      <td>14</td>\n",
       "      <td>1192.142857</td>\n",
       "      <td>14</td>\n",
       "      <td>-3</td>\n",
       "      <td>1192.142857</td>\n",
       "      <td>1.0</td>\n",
       "      <td>956.468933</td>\n",
       "      <td>0.908405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4060407405763178170</th>\n",
       "      <td>7</td>\n",
       "      <td>1434.285714</td>\n",
       "      <td>13</td>\n",
       "      <td>-3</td>\n",
       "      <td>1434.285714</td>\n",
       "      <td>1.0</td>\n",
       "      <td>942.970581</td>\n",
       "      <td>0.762554</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     frequency  average_sales_euro  customer_age  recency  \\\n",
       "userId                                                                      \n",
       "6466311134798860530          8         1255.625000            11       -3   \n",
       "5751267705453534770          7         2265.714286            13       -3   \n",
       "7301457211102063352          8         1632.500000            13       -3   \n",
       "3413727104991269184         18         1501.666667            10       -3   \n",
       "8947766884244807627          5         1853.400000            12       -3   \n",
       "6637608848075134823          6         2199.833333            12       -6   \n",
       "5794839213058583147         13         1246.215385            13       -5   \n",
       "7803134376982934048          7         2128.571429            10       -6   \n",
       "7308564510325687140          8         1621.250000            13       -3   \n",
       "5200083858774336444          7         1828.571429            10       -3   \n",
       "8597323003979209507          5         1521.400000            14       -3   \n",
       "6146852045155325256         19         1262.631579            12       -3   \n",
       "1831167567366470988          8         1563.750000            13       -3   \n",
       "8979193897949196807         14         1276.428571            11       -4   \n",
       "3521480400409139935          5         1490.000000            14       -3   \n",
       "5156756655607387559         29         1587.931034            14       -3   \n",
       "1963435673590959229         36         1126.388889            13       -3   \n",
       "1331175590391651538         13         1175.000000            13       -3   \n",
       "6687871536716425521          7         1521.428571            13       -3   \n",
       "6373299565216195981         17         1307.647059            14       -6   \n",
       "1836974674558095944          7         1833.571429            13       -6   \n",
       "2106762733770992846         13         1288.461538            12       -4   \n",
       "411994089603024641           7         1300.000000            10       -3   \n",
       "1678093046687605731         13         1611.538462            14       -4   \n",
       "8727933238807787543          8         2000.000000            13       -5   \n",
       "7632974522149307827          7         1342.857143             9       -3   \n",
       "4348801244420142027         11         2090.909091            10       -5   \n",
       "768100758869037150           7         1250.000000            13       -3   \n",
       "8909814062220489386          5         1700.000000            13       -3   \n",
       "4061843065023891403         12         1152.500000            14       -3   \n",
       "723513955432389419           7         1492.857143            11       -3   \n",
       "3860687727043786122         18         1405.555556            13       -4   \n",
       "3274241785415673531          8         1426.250000            11       -3   \n",
       "294301877040040480          13         1341.923077            12       -3   \n",
       "8622151806657300217         20         1177.750000            13       -3   \n",
       "2374751365343554912         20         1176.000000            13       -5   \n",
       "5052340629890545130         15         1493.666667            13       -4   \n",
       "459476809824996220          16         1231.450000            13       -4   \n",
       "6547979762166587770          7         1317.142857            13       -3   \n",
       "6960670268974794018          8         1245.000000            10       -4   \n",
       "2994401254952486734          6         2063.333333            12       -6   \n",
       "3210374918718909087          8         1135.000000            13       -3   \n",
       "5829395833302970485         16         1155.937500            13       -4   \n",
       "6680854331401630563         12         1564.166667            13       -4   \n",
       "125587389245608054           9         1122.222222            13       -3   \n",
       "2759751677286287812          8         1183.750000            12       -3   \n",
       "8015847651155022352          9         1146.666667            13       -3   \n",
       "8374525967619359164          7         1814.285714            14       -6   \n",
       "5449281706118422564         14         1192.142857            14       -3   \n",
       "4060407405763178170          7         1434.285714            13       -3   \n",
       "\n",
       "                     sales_2weeks_avg  transaction_2weeks_count  \\\n",
       "userId                                                            \n",
       "6466311134798860530       1255.625000                       1.0   \n",
       "5751267705453534770       2265.714286                       1.0   \n",
       "7301457211102063352       1632.500000                       1.0   \n",
       "3413727104991269184       1501.666667                       1.0   \n",
       "8947766884244807627       1853.400000                       1.0   \n",
       "6637608848075134823          0.000000                       0.0   \n",
       "5794839213058583147          0.000000                       0.0   \n",
       "7803134376982934048          0.000000                       0.0   \n",
       "7308564510325687140       1621.250000                       1.0   \n",
       "5200083858774336444       1828.571429                       1.0   \n",
       "8597323003979209507       1521.400000                       1.0   \n",
       "6146852045155325256       1262.631579                       1.0   \n",
       "1831167567366470988       1563.750000                       1.0   \n",
       "8979193897949196807          0.000000                       0.0   \n",
       "3521480400409139935       1490.000000                       1.0   \n",
       "5156756655607387559       1587.931034                       1.0   \n",
       "1963435673590959229       1126.388889                       1.0   \n",
       "1331175590391651538       1175.000000                       1.0   \n",
       "6687871536716425521       1521.428571                       1.0   \n",
       "6373299565216195981          0.000000                       0.0   \n",
       "1836974674558095944          0.000000                       0.0   \n",
       "2106762733770992846          0.000000                       0.0   \n",
       "411994089603024641        1300.000000                       1.0   \n",
       "1678093046687605731          0.000000                       0.0   \n",
       "8727933238807787543          0.000000                       0.0   \n",
       "7632974522149307827       1342.857143                       1.0   \n",
       "4348801244420142027          0.000000                       0.0   \n",
       "768100758869037150        1250.000000                       1.0   \n",
       "8909814062220489386       1700.000000                       1.0   \n",
       "4061843065023891403       1152.500000                       1.0   \n",
       "723513955432389419        1492.857143                       1.0   \n",
       "3860687727043786122          0.000000                       0.0   \n",
       "3274241785415673531       1426.250000                       1.0   \n",
       "294301877040040480        1341.923077                       1.0   \n",
       "8622151806657300217       1177.750000                       1.0   \n",
       "2374751365343554912          0.000000                       0.0   \n",
       "5052340629890545130          0.000000                       0.0   \n",
       "459476809824996220           0.000000                       0.0   \n",
       "6547979762166587770       1317.142857                       1.0   \n",
       "6960670268974794018          0.000000                       0.0   \n",
       "2994401254952486734          0.000000                       0.0   \n",
       "3210374918718909087       1135.000000                       1.0   \n",
       "5829395833302970485          0.000000                       0.0   \n",
       "6680854331401630563          0.000000                       0.0   \n",
       "125587389245608054        1122.222222                       1.0   \n",
       "2759751677286287812       1183.750000                       1.0   \n",
       "8015847651155022352       1146.666667                       1.0   \n",
       "8374525967619359164          0.000000                       0.0   \n",
       "5449281706118422564       1192.142857                       1.0   \n",
       "4060407405763178170       1434.285714                       1.0   \n",
       "\n",
       "                     pred_sale_next_90_avg  pred_proba_sale_next_90  \n",
       "userId                                                               \n",
       "6466311134798860530            2609.890869                 0.707868  \n",
       "5751267705453534770            2186.032959                 0.766092  \n",
       "7301457211102063352            1779.968140                 0.761263  \n",
       "3413727104991269184            1729.994873                 0.958234  \n",
       "8947766884244807627            1652.913696                 0.620687  \n",
       "6637608848075134823            1609.187256                 0.512924  \n",
       "5794839213058583147            1550.748901                 0.821302  \n",
       "7803134376982934048            1481.502686                 0.601594  \n",
       "7308564510325687140            1463.014648                 0.771856  \n",
       "5200083858774336444            1411.716309                 0.754674  \n",
       "8597323003979209507            1403.780640                 0.647607  \n",
       "6146852045155325256            1373.659546                 0.945909  \n",
       "1831167567366470988            1368.064941                 0.779405  \n",
       "8979193897949196807            1347.848145                 0.879501  \n",
       "3521480400409139935            1315.843750                 0.651798  \n",
       "5156756655607387559            1313.896484                 0.969881  \n",
       "1963435673590959229            1305.043213                 0.966832  \n",
       "1331175590391651538            1276.578979                 0.894410  \n",
       "6687871536716425521            1245.581787                 0.775205  \n",
       "6373299565216195981            1221.598755                 0.814031  \n",
       "1836974674558095944            1183.433594                 0.621441  \n",
       "2106762733770992846            1166.275513                 0.871106  \n",
       "411994089603024641             1154.708374                 0.748352  \n",
       "1678093046687605731            1142.273926                 0.863502  \n",
       "8727933238807787543            1125.335938                 0.663820  \n",
       "7632974522149307827            1119.358521                 0.785456  \n",
       "4348801244420142027            1113.779053                 0.764217  \n",
       "768100758869037150             1094.936157                 0.698191  \n",
       "8909814062220489386            1088.679810                 0.635806  \n",
       "4061843065023891403            1076.770142                 0.881060  \n",
       "723513955432389419             1055.413086                 0.780544  \n",
       "3860687727043786122            1039.830322                 0.934487  \n",
       "3274241785415673531            1039.507080                 0.755479  \n",
       "294301877040040480             1034.674927                 0.916613  \n",
       "8622151806657300217            1034.375122                 0.964121  \n",
       "2374751365343554912            1033.990234                 0.913789  \n",
       "5052340629890545130            1031.351074                 0.928793  \n",
       "459476809824996220             1029.883545                 0.935819  \n",
       "6547979762166587770            1023.889709                 0.740971  \n",
       "6960670268974794018            1019.955505                 0.691235  \n",
       "2994401254952486734            1011.935425                 0.521455  \n",
       "3210374918718909087            1004.344482                 0.747968  \n",
       "5829395833302970485            1000.034546                 0.936553  \n",
       "6680854331401630563             992.844238                 0.863674  \n",
       "125587389245608054              990.943848                 0.787598  \n",
       "2759751677286287812             973.400085                 0.729857  \n",
       "8015847651155022352             963.943481                 0.787429  \n",
       "8374525967619359164             957.167603                 0.592425  \n",
       "5449281706118422564             956.468933                 0.908405  \n",
       "4060407405763178170             942.970581                 0.762554  "
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_n_customers = final_table.head(top_n)\n",
    "top_n_customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The top 50 customers can generate 62049.34 in average sales with between 51.29 and 96.99 percent probability for the company\n"
     ]
    }
   ],
   "source": [
    "print(f\"The top {top_n} customers can generate {top_n_customers[\"pred_sale_next_90_avg\"].mean()*top_n:.2f} in average sales with between {top_n_customers[\"pred_proba_sale_next_90\"].min()*100:.2f} and {top_n_customers[\"pred_proba_sale_next_90\"].max()*100:.2f} percent probability for the company\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inference\n",
    "\n",
    "The top 50 customers can generate an average of 62,049.34 euros in sales, with a probability ranging from 51.29% to 96.99% for the company. Targetting these to customers for more frequent and recent purchases will achieve even higher sales. "
   ]
  }
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