customer_lifetime_modeling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Customer Lifetime Value Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dataset: https://www.kaggle.com/vijayuv/onlineretail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
      "  import pandas.util.testing as tm\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import lifetimes\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Probablistic Model: BG/NBD, Gamma-Gamma Model\n",
    "LTV = expected number of transactions * revenue per transactions * margin    \n",
    "- BG/NBD model: predict 1) expected number of transactions; 2) probability of being alive    \n",
    "- Gamma-Gamma model: predict expected monetary value per transaction    \n",
    "- Margin is defined by business, e.g., discount, campaign, something relates to the price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>2010-12-01 08:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>2010-12-01 08:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity       InvoiceDate  UnitPrice  CustomerID         Country\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6  2010-12-01 08:26       2.55     17850.0  United Kingdom\n",
       "1    536365     71053                  WHITE METAL LANTERN         6  2010-12-01 08:26       3.39     17850.0  United Kingdom\n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8  2010-12-01 08:26       2.75     17850.0  United Kingdom\n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6  2010-12-01 08:26       3.39     17850.0  United Kingdom\n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6  2010-12-01 08:26       3.39     17850.0  United Kingdom"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"Online+Retail.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Data preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo       object\n",
       "StockCode       object\n",
       "Description     object\n",
       "Quantity         int64\n",
       "InvoiceDate     object\n",
       "UnitPrice      float64\n",
       "CustomerID     float64\n",
       "Country         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InvoiceNo           0\n",
       "StockCode           0\n",
       "Description      1454\n",
       "Quantity            0\n",
       "InvoiceDate         0\n",
       "UnitPrice           0\n",
       "CustomerID     135080\n",
       "Country             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data cleansing\n",
    "customerID: remove missing values, because the model is built on specific customers.    \n",
    "Quantity: remove negative records (the data is based on accounting records, positive records have related negative records)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfnew = df[(df.Quantity>0) & (df.CustomerID.isnull() == False)]\n",
    "\n",
    "dfnew['amt'] = dfnew['Quantity'] * dfnew['UnitPrice']\n",
    "dfnew['InvoiceDate'] = pd.to_datetime(dfnew['InvoiceDate']).dt.date"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### EDA\n",
    "- 4339 customers\n",
    "- 397,924 transactions\n",
    "- Date: 2010-12-01 to 2011-12-09\n",
    "- Average CLV: 2053.79, median CLV: 674.45"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2010-12-01\n",
      "2011-12-09\n"
     ]
    }
   ],
   "source": [
    "print(dfnew['InvoiceDate'].min())\n",
    "print(dfnew['InvoiceDate'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4339"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of customers\n",
    "dfnew['CustomerID'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(397924, 9)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of transactions\n",
    "dfnew.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "cust = dfnew.groupby(['CustomerID']).agg({\n",
    "    'InvoiceNo': 'count',\n",
    "    'amt': 'sum'\n",
    "}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>amt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4339.000000</td>\n",
       "      <td>4339.000000</td>\n",
       "      <td>4339.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>15299.936852</td>\n",
       "      <td>91.708689</td>\n",
       "      <td>2053.793018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1721.889758</td>\n",
       "      <td>228.792852</td>\n",
       "      <td>8988.248381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>12346.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>13812.500000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>307.245000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>15299.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>674.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>16778.500000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>1661.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>18287.000000</td>\n",
       "      <td>7847.000000</td>\n",
       "      <td>280206.020000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         CustomerID    InvoiceNo            amt\n",
       "count   4339.000000  4339.000000    4339.000000\n",
       "mean   15299.936852    91.708689    2053.793018\n",
       "std     1721.889758   228.792852    8988.248381\n",
       "min    12346.000000     1.000000       0.000000\n",
       "25%    13812.500000    17.000000     307.245000\n",
       "50%    15299.000000    41.000000     674.450000\n",
       "75%    16778.500000   100.000000    1661.640000\n",
       "max    18287.000000  7847.000000  280206.020000"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cust.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Feature aggregation\n",
    "The lifetime package is based on transaction data only. For each customer, aggregate:\n",
    "- recency: days between first and last purchase in the given period.\n",
    "- frequency: number of repeated purchase in the given period. More precisely, it's the count of days the customer had a repeated purchase on.\n",
    "- T: customer age, days since first purchase.\n",
    "- monetary_value: transaction value in the given period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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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>recency</th>\n",
       "      <th>T</th>\n",
       "      <th>monetary_value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>325.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.0</th>\n",
       "      <td>6.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>599.701667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>301.480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12349.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "            frequency  recency      T  monetary_value\n",
       "CustomerID                                           \n",
       "12346.0           0.0      0.0  325.0        0.000000\n",
       "12347.0           6.0    365.0  367.0      599.701667\n",
       "12348.0           3.0    283.0  358.0      301.480000\n",
       "12349.0           0.0      0.0   18.0        0.000000\n",
       "12350.0           0.0      0.0  310.0        0.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from lifetimes.plotting import *\n",
    "from lifetimes.utils import *\n",
    "\n",
    "modeldata = summary_data_from_transaction_data(dfnew, 'CustomerID', 'InvoiceDate', \n",
    "                                               monetary_value_col='amt', \n",
    "                                               observation_period_end='2011-12-9')\n",
    "modeldata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "count    4339.000000\n",
      "mean        2.864024\n",
      "std         5.952745\n",
      "min         0.000000\n",
      "25%         0.000000\n",
      "50%         1.000000\n",
      "75%         3.000000\n",
      "max       131.000000\n",
      "Name: frequency, dtype: float64\n",
      "0.3569946992394561\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "modeldata['frequency'].plot(kind='hist', bins=50)\n",
    "print(modeldata['frequency'].describe())\n",
    "# frequency=0 means no repeated purchase. 35.7% customers left after one purchase.\n",
    "print(sum(modeldata['frequency'] == 0)/float(len(modeldata)))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 BG/NBD model\n",
    "Beta-Geometric/Negative Binomial Distribution Model\n",
    "#### 1.3.1 Assumptions"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. When a user is active, the number of his transactions in a time period of length t is described by Poisson distribution with transaction rate λ.\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Transaction rate λ has Gamma distribution with parameters r (shape) and α (scale).\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Users may become inactive after any transaction with probability p and their dropout point is distributed between purchases with Geometric distribution.\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Dropout probability p has Beta distribution with the two shape parameters α and β.\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Transaction rate and dropout probability independently vary across users."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<lifetimes.BetaGeoFitter: fitted with 4339 subjects, a: 0.00, alpha: 68.89, b: 6.75, r: 0.83>\n"
     ]
    }
   ],
   "source": [
    "from lifetimes import BetaGeoFitter\n",
    "\n",
    "# penalizer_coef: regularization, to prevent overfitting especially when the dataset is small, can set 0 when dataset is large enough\n",
    "bgf = BetaGeoFitter(penalizer_coef=0.0)\n",
    "\n",
    "# fit BG model on the whole data\n",
    "bgf.fit(modeldata['frequency'], modeldata['recency'], modeldata['T'])\n",
    "print(bgf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:  0.0005098191370874716\n",
      "median:  3.267989632629193e-89\n",
      "std:  0.008107144035249531\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import gamma, beta\n",
    "\n",
    "x = np.arange (0.01, 1, 0.1)\n",
    "a, b = bgf.params_['a'], bgf.params_['b']\n",
    "gbd = beta.pdf(x, a, b)\n",
    "plt.figure(figsize=(6,4))\n",
    "plt.title('Heterogenity of $p$')\n",
    "temp = plt.plot(x, gbd)\n",
    "plt.show()\n",
    "print('mean: ', beta.mean(a, b))\n",
    "print('median: ', beta.median(a, b))\n",
    "print('std: ', beta.std(a, b))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean:  0.011996297994156649\n",
      "median:  0.007641762756333042\n",
      "std:  0.01319603301914138\n"
     ]
    }
   ],
   "source": [
    "x = np.arange (0.0001, 0.15, 0.001)\n",
    "r, alpha = bgf.params_['r'], bgf.params_['alpha']\n",
    "ggd = gamma.pdf(x, r, scale=1.0/alpha)\n",
    "plt.figure(figsize=(6,4))\n",
    "plt.title('Heterogenity of $\\lambda$')\n",
    "temp = plt.plot(x, ggd)\n",
    "plt.show()\n",
    "print('mean: ', gamma.mean(r, scale=1.0/alpha))\n",
    "print('median: ', gamma.median(r, scale=1.0/alpha))\n",
    "print('std: ', gamma.std(r, scale=1.0/alpha))"
   ]
  },
  {
   "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>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>0.826433</td>\n",
       "      <td>0.026780</td>\n",
       "      <td>0.773944</td>\n",
       "      <td>0.878922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>68.890678</td>\n",
       "      <td>2.611055</td>\n",
       "      <td>63.773011</td>\n",
       "      <td>74.008345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0.003443</td>\n",
       "      <td>0.010347</td>\n",
       "      <td>-0.016837</td>\n",
       "      <td>0.023722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>6.749363</td>\n",
       "      <td>22.412933</td>\n",
       "      <td>-37.179985</td>\n",
       "      <td>50.678711</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            coef   se(coef)  lower 95% bound  upper 95% bound\n",
       "r       0.826433   0.026780         0.773944         0.878922\n",
       "alpha  68.890678   2.611055        63.773011        74.008345\n",
       "a       0.003443   0.010347        -0.016837         0.023722\n",
       "b       6.749363  22.412933       -37.179985        50.678711"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bgf.summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.2 Frequency-recency matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1225c2eb8>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifetimes.plotting import plot_frequency_recency_matrix\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "plot_frequency_recency_matrix(bgf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Target: expected number of purchase in next 1 day    \n",
    "X-axis: frequency    \n",
    "Y-axis: recency    \n",
    "- Up-right: dark, rare chance of purchase, people have high frequency, but rarely buy things recently, they might quit the product/your business\n",
    "- Diagonal: blue curve, relatively good customer    \n",
    "\n",
    "**Recency is more important than frequency**. People with good recency (bottom) is more likely to buy than people with high frequency but bad recency (up right)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.3 Churn/Active Probability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x122304b38>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifetimes.plotting import plot_probability_alive_matrix\n",
    "\n",
    "fig = plt.figure(figsize=(12,8))\n",
    "plot_probability_alive_matrix(bgf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Up-right: dead/silent\n",
    "- Bottom-left: high activity. Active probability decrease exponentially with recency (time between first and last purchase) decrease."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.4 Predict future transaction number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = 1  # in the next 1 day\n",
    "modeldata['predicted_purchases'] = bgf.conditional_expected_number_of_purchases_up_to_time(t, modeldata['frequency'], modeldata['recency'], modeldata['T'])\n"
   ]
  },
  {
   "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",
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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>frequency</th>\n",
       "      <th>recency</th>\n",
       "      <th>T</th>\n",
       "      <th>monetary_value</th>\n",
       "      <th>predicted_purchases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14606.0</th>\n",
       "      <td>88.0</td>\n",
       "      <td>372.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>135.890114</td>\n",
       "      <td>0.201005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15311.0</th>\n",
       "      <td>89.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>677.729438</td>\n",
       "      <td>0.203269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17841.0</th>\n",
       "      <td>111.0</td>\n",
       "      <td>372.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>364.452162</td>\n",
       "      <td>0.253053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12748.0</th>\n",
       "      <td>113.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>298.360885</td>\n",
       "      <td>0.257581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14911.0</th>\n",
       "      <td>131.0</td>\n",
       "      <td>372.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>1093.661679</td>\n",
       "      <td>0.298312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            frequency  recency      T  monetary_value  predicted_purchases\n",
       "CustomerID                                                                \n",
       "14606.0          88.0    372.0  373.0      135.890114             0.201005\n",
       "15311.0          89.0    373.0  373.0      677.729438             0.203269\n",
       "17841.0         111.0    372.0  373.0      364.452162             0.253053\n",
       "12748.0         113.0    373.0  373.0      298.360885             0.257581\n",
       "14911.0         131.0    372.0  373.0     1093.661679             0.298312"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Highest 5 customers\n",
    "modeldata.sort_values(by='predicted_purchases').tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>frequency</th>\n",
       "      <th>recency</th>\n",
       "      <th>T</th>\n",
       "      <th>monetary_value</th>\n",
       "      <th>predicted_purchases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18074.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16048.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16274.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14237.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14142.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            frequency  recency      T  monetary_value  predicted_purchases\n",
       "CustomerID                                                                \n",
       "18074.0           0.0      0.0  373.0             0.0              0.00187\n",
       "16048.0           0.0      0.0  373.0             0.0              0.00187\n",
       "16274.0           0.0      0.0  373.0             0.0              0.00187\n",
       "14237.0           0.0      0.0  373.0             0.0              0.00187\n",
       "14142.0           0.0      0.0  373.0             0.0              0.00187"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lowest 5 customers\n",
    "modeldata.sort_values(by='predicted_purchases').head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.5 Model validation: period transaction plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12244d5f8>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifetimes.plotting import plot_period_transactions\n",
    "plot_period_transactions(bgf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "X-axis: number of transactions in calibration period (whole training data)    \n",
    "Error: gap between two bars    \n",
    "\n",
    "The model is good because:\n",
    "-\t**accurate**: Gaps between two bars are small\n",
    "-\t**stable**: Two bars decline consistently.    \n",
    "If the pattern (two bars) is not declining consistently, the model is not stable.\n",
    "-\tThere are both positive and negative errors, the error is random.     \n",
    "If the model prediction is always larger/smaller than actual, the model is not good because the error is not random, there’s still room for the model to be improved."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.6 Model validation: split calibration and holdout sets\n",
    "Partition data into two parts. Fit the model on calibration (train) set, test on future/holdout."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary_cal_holdout = calibration_and_holdout_data(dfnew, 'CustomerID', 'InvoiceDate',\n",
    "                                        calibration_period_end='2011-08-31',\n",
    "                                        observation_period_end='2011-12-09' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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_cal</th>\n",
       "      <th>recency_cal</th>\n",
       "      <th>T_cal</th>\n",
       "      <th>frequency_holdout</th>\n",
       "      <th>duration_holdout</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.0</th>\n",
       "      <td>2.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12352.0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            frequency_cal  recency_cal  T_cal  frequency_holdout  duration_holdout\n",
       "CustomerID                                                                        \n",
       "12346.0               0.0          0.0  225.0                0.0               100\n",
       "12347.0               4.0        238.0  267.0                2.0               100\n",
       "12348.0               2.0        110.0  258.0                1.0               100\n",
       "12350.0               0.0          0.0  210.0                0.0               100\n",
       "12352.0               3.0         34.0  196.0                3.0               100"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_cal_holdout.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x117745828>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lifetimes.plotting import plot_calibration_purchases_vs_holdout_purchases\n",
    "\n",
    "bgf2 = BetaGeoFitter(penalizer_coef=0.0)\n",
    "bgf2.fit(summary_cal_holdout['frequency_cal'], summary_cal_holdout['recency_cal'], summary_cal_holdout['T_cal'])\n",
    "plot_calibration_purchases_vs_holdout_purchases(bgf2, summary_cal_holdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model is good because model prediction (orange line) and true data (blue line) overlap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary_cal_holdout['predicted_purchases'] = bgf2.conditional_expected_number_of_purchases_up_to_time(100, summary_cal_holdout['frequency_cal'], summary_cal_holdout['recency_cal'], summary_cal_holdout['T_cal'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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_cal</th>\n",
       "      <th>recency_cal</th>\n",
       "      <th>T_cal</th>\n",
       "      <th>frequency_holdout</th>\n",
       "      <th>duration_holdout</th>\n",
       "      <th>predicted_purchases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12346.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.248374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12347.0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100</td>\n",
       "      <td>1.418368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12348.0</th>\n",
       "      <td>2.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.840423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12350.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.261874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12352.0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>100</td>\n",
       "      <td>1.421056</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>18280.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.297442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18281.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.495104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18282.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.785817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18283.0</th>\n",
       "      <td>7.0</td>\n",
       "      <td>189.0</td>\n",
       "      <td>237.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>100</td>\n",
       "      <td>2.549027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18287.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100</td>\n",
       "      <td>0.432833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3317 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            frequency_cal  recency_cal  T_cal  frequency_holdout  duration_holdout  predicted_purchases\n",
       "CustomerID                                                                                             \n",
       "12346.0               0.0          0.0  225.0                0.0               100             0.248374\n",
       "12347.0               4.0        238.0  267.0                2.0               100             1.418368\n",
       "12348.0               2.0        110.0  258.0                1.0               100             0.840423\n",
       "12350.0               0.0          0.0  210.0                0.0               100             0.261874\n",
       "12352.0               3.0         34.0  196.0                3.0               100             1.421056\n",
       "...                   ...          ...    ...                ...               ...                  ...\n",
       "18280.0               0.0          0.0  177.0                0.0               100             0.297442\n",
       "18281.0               0.0          0.0   80.0                0.0               100             0.495104\n",
       "18282.0               0.0          0.0   26.0                1.0               100             0.785817\n",
       "18283.0               7.0        189.0  237.0                6.0               100             2.549027\n",
       "18287.0               0.0          0.0  101.0                2.0               100             0.432833\n",
       "\n",
       "[3317 rows x 6 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_cal_holdout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "def smape(y_true, y_pred):\n",
    "    difference = abs(y_true - y_pred)\n",
    "    denominator = (abs(y_true) + abs(y_pred))/2\n",
    "    return np.mean(np.where(denominator==0, 0, difference/denominator))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE:  1.6297864600060779\n",
      "SMAPE 1.2143022906730694\n",
      "R2:  0.5610201649501331\n"
     ]
    }
   ],
   "source": [
    "print('RMSE: ', mean_squared_error(summary_cal_holdout['frequency_holdout'], summary_cal_holdout['predicted_purchases'])**(1/2))\n",
    "print('SMAPE', smape(summary_cal_holdout['frequency_holdout'], summary_cal_holdout['predicted_purchases']))\n",
    "print('R2: ', r2_score(summary_cal_holdout['frequency_holdout'], summary_cal_holdout['predicted_purchases']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15170360805212538"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# predict for a specific customer, number of purchase in next 10 days\n",
    "t = 10\n",
    "individual = modeldata.loc[12380]\n",
    "bgf.predict(t, individual['frequency'], individual['recency'], individual['T'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.7 Historical probability of being alive    \n",
    "With the CLV model we have created, we can specifically estimate a customer's historical probability of being alive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1240dd320>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customer 14606\n",
    "# frequent customer, alive throughout the year.\n",
    "id = 14606\n",
    "days_since_birth = 365\n",
    "sp_trans = dfnew.loc[df['CustomerID'] == id]\n",
    "plot_history_alive(bgf, days_since_birth, sp_trans, 'InvoiceDate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x117836940>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Customer 12352    \n",
    "# 6 repeated orders\n",
    "id = 12352\n",
    "days_since_birth = 365\n",
    "sp_trans = dfnew.loc[df['CustomerID'] == id]\n",
    "plot_history_alive(bgf, days_since_birth, sp_trans, 'InvoiceDate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Gamma-Gamma model\n",
    "Predict average monetary value per transaction. If we know the price and historical transactions of a specific customer, then we can apply Gamma-Gamma model to predict most likely monetary value **per transaction** in the future.    \n",
    "#### Focus on customers with repurchase behavior\n",
    "Focus on estimating the customers who had at least one repeat purchase. Because customer with only one purchase is very less likely to make additional purchase. It’s difficult to save/wake up these silent customers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "returning_customers_summary = modeldata[modeldata['frequency']>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6430053007605439"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 64% customer left\n",
    "len(returning_customers_summary)/len(modeldata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<lifetimes.GammaGammaFitter: fitted with 2790 subjects, p: 2.10, q: 3.45, v: 485.57>\n"
     ]
    }
   ],
   "source": [
    "from lifetimes import GammaGammaFitter\n",
    "\n",
    "ggf = GammaGammaFitter(penalizer_coef = 0)\n",
    "ggf.fit(returning_customers_summary['frequency'],\n",
    "        returning_customers_summary['monetary_value'])\n",
    "\n",
    "print(ggf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CustomerID\n",
       "12346.0    416.917667\n",
       "12347.0    569.988807\n",
       "12348.0    333.762672\n",
       "12349.0    416.917667\n",
       "12350.0    416.917667\n",
       "12352.0    376.166864\n",
       "12353.0    416.917667\n",
       "12354.0    416.917667\n",
       "12355.0    416.917667\n",
       "12356.0    324.008941\n",
       "dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggf.conditional_expected_average_profit(modeldata['frequency'], \\\n",
    "    modeldata['monetary_value']).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Machine Learning: Xgboost and Lightgbm Algorithm\n",
    "Features:    \n",
    "- customerID\n",
    "- latetime: days between last transaction to now\n",
    "- earlytime: days between first transaction to now\n",
    "- freq: transaction frequency (whole history)\n",
    "- freq_3m: transaction frequency (recent 3 months history)\n",
    "    \n",
    "Target: number of transactions in test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         2010-12-01\n",
       "1         2010-12-01\n",
       "2         2010-12-01\n",
       "3         2010-12-01\n",
       "4         2010-12-01\n",
       "             ...    \n",
       "541904    2011-12-09\n",
       "541905    2011-12-09\n",
       "541906    2011-12-09\n",
       "541907    2011-12-09\n",
       "541908    2011-12-09\n",
       "Name: InvoiceDate, Length: 397924, dtype: object"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfnew.InvoiceDate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "\n",
    "dfnew_train = dfnew[dfnew.InvoiceDate <= datetime.date(2011, 8, 31)]\n",
    "dfnew_test = dfnew[dfnew.InvoiceDate > datetime.date(2011, 8, 31)]\n",
    "\n",
    "maxdate = dfnew_train.InvoiceDate.max()\n",
    "mindate = dfnew_train.InvoiceDate.min()\n",
    "\n",
    "dfnew_train['duration'] =  (maxdate - dfnew_train.InvoiceDate)/np.timedelta64(1, 'D')\n",
    "# get time duration between the last transaction to now\n",
    "dfsum1 = dfnew_train.groupby(['CustomerID'])['duration'].min().reset_index()\n",
    "dfsum1.rename(columns = {'duration':'latetime'}, inplace = True)\n",
    "\n",
    "# get time duration between the first transaction to now\n",
    "dfsum2 = dfnew_train.groupby(['CustomerID'])['duration'].max().reset_index()\n",
    "dfsum2.rename(columns = {'duration':'earlytime'}, inplace = True)\n",
    "\n",
    "# get transaction frequency (whole history)\n",
    "dfsum3 = dfnew_train.groupby(['CustomerID'])['InvoiceDate'].nunique().reset_index()\n",
    "dfsum3.rename(columns={'InvoiceDate': 'freq'}, inplace=True)\n",
    "# get transaction frequency (recent 3 months history)\n",
    "dfsum4 = dfnew_train[dfnew_train.duration<91].groupby(['CustomerID'])['InvoiceDate'].nunique().reset_index()\n",
    "dfsum4.rename(columns={'InvoiceDate': 'freq_3m'}, inplace=True)\n",
    "\n",
    "dfsum = pd.merge(dfsum1, dfsum2, on=['CustomerID'], how='outer')\n",
    "dfsum = pd.merge(dfsum, dfsum3, on=['CustomerID'], how='outer')\n",
    "dfsum = pd.merge(dfsum, dfsum4, on=['CustomerID'], how='outer')\n",
    "\n",
    "# get target: number of transactions in test set\n",
    "dfsum_target = dfnew_test.groupby(['CustomerID'])['InvoiceDate'].nunique().reset_index()\n",
    "dfsum_target.rename(columns={'InvoiceDate': 'target'}, inplace=True)\n",
    "dfsum = pd.merge(dfsum, dfsum_target, on=['CustomerID'], how='left')\n",
    "dfsum  = dfsum.fillna(0).sort_values(['target'], ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3317.000000\n",
       "mean        1.449201\n",
       "std         2.460220\n",
       "min         0.000000\n",
       "25%         0.000000\n",
       "50%         1.000000\n",
       "75%         2.000000\n",
       "max        52.000000\n",
       "Name: target, dtype: float64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfsum['target'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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>CustomerID</th>\n",
       "      <th>latetime</th>\n",
       "      <th>earlytime</th>\n",
       "      <th>freq</th>\n",
       "      <th>freq_3m</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1463</th>\n",
       "      <td>14911.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>80</td>\n",
       "      <td>33.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>12748.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>70</td>\n",
       "      <td>29.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3065</th>\n",
       "      <td>17841.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>73</td>\n",
       "      <td>29.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694</th>\n",
       "      <td>15311.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>62</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1292</th>\n",
       "      <td>14606.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>65</td>\n",
       "      <td>19.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>12971.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>13089.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>47</td>\n",
       "      <td>13.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>12569.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>10</td>\n",
       "      <td>6.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>14646.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>29</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248</th>\n",
       "      <td>14527.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>38</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CustomerID  latetime  earlytime  freq  freq_3m  target\n",
       "1463     14911.0       5.0      273.0    80     33.0    52.0\n",
       "249      12748.0       1.0      273.0    70     29.0    44.0\n",
       "3065     17841.0       3.0      273.0    73     29.0    39.0\n",
       "1694     15311.0      12.0      273.0    62     20.0    28.0\n",
       "1292     14606.0       3.0      273.0    65     19.0    24.0\n",
       "366      12971.0       7.0      272.0    50     17.0    21.0\n",
       "434      13089.0       0.0      269.0    47     13.0    19.0\n",
       "134      12569.0       7.0      152.0    10      6.0    16.0\n",
       "1315     14646.0       5.0      254.0    29      9.0    16.0\n",
       "1248     14527.0       7.0      269.0    38     13.0    16.0"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfsum.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### xgb model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "             colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,\n",
       "             max_depth=3, min_child_weight=1, missing=None, n_estimators=2200,\n",
       "             n_jobs=1, nthread=None, objective='reg:linear', random_state=0,\n",
       "             reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n",
       "             silent=True, subsample=1)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import xgboost as xgb\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "xgb_model = xgb.XGBRegressor(n_estimators=2200, objective='reg:linear', max_depth = 3)\n",
    " \n",
    "predictors = ['latetime','earlytime', 'freq','freq_3m']\n",
    "X = dfsum[predictors]\n",
    "y = dfsum.target\n",
    "\n",
    "x_trains, x_valids, y_train, y_valid = train_test_split(X, y, test_size=0.3, random_state=12)\n",
    "\n",
    "xgb_model.fit(x_trains, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE on test set:  1.789839681695472\n"
     ]
    }
   ],
   "source": [
    "y_pred = xgb_model.predict(x_valids)\n",
    "rmse = mean_squared_error(y_valid, y_pred)**(1/2)\n",
    "print('RMSE on test set: ', rmse)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE:  0.9432251152502583\n",
      "SMAPE 1.0779295245501\n",
      "R2:  0.8529673202695269\n"
     ]
    }
   ],
   "source": [
    "xgb_model2 = xgb.XGBRegressor(n_estimators=2200, objective='reg:linear', max_depth = 3)\n",
    "xgb_model2.fit(X, y)\n",
    "y_pred2 = xgb_model2.predict(X)\n",
    "print('RMSE: ', mean_squared_error(y, y_pred2)**(1/2))\n",
    "print('SMAPE', smape(y, y_pred2))\n",
    "print('R2: ', r2_score(y, y_pred2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Feature importance\n",
    "importance_type:\n",
    "- ‘weight’ - the number of times a feature is used to split the data across all trees.\n",
    "- ‘gain’ - the average gain across all splits the feature is used in. most popular way.\n",
    "- ‘cover’ - the average coverage across all splits the feature is used in. (yes/no proportion)\n",
    "- ‘total_gain’ - the total gain across all splits the feature is used in.\n",
    "- ‘total_cover’ - the total coverage across all splits the feature is used in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11b676dd8>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xgb.plot_importance(xgb_model, importance_type='gain')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x117625518>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xgb.plot_importance(xgb_model, importance_type='weight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### lgb model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\n",
       "              importance_type='split', learning_rate=0.02, max_depth=3,\n",
       "              metric='mse', min_child_samples=20, min_child_weight=0.001,\n",
       "              min_split_gain=0.0, n_estimators=2200, n_jobs=-1, num_leaves=31,\n",
       "              objective='regression', random_state=None, reg_alpha=0.0,\n",
       "              reg_lambda=0.0, silent=True, subsample=1.0,\n",
       "              subsample_for_bin=200000, subsample_freq=0)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import lightgbm as lgb\n",
    "\n",
    "lgbparams = {\n",
    "    'n_estimators': 2200, \n",
    "    'boosting_type': 'gbdt',\n",
    "    'objective': 'regression',\n",
    "    'metric': 'mse',    \n",
    "    'max_depth': 3, \n",
    "    'learning_rate': 0.02\n",
    "}\n",
    "\n",
    "lgb_model = lgb.LGBMRegressor(**lgbparams)\n",
    " \n",
    "predictors = ['latetime','earlytime', 'freq','freq_3m']\n",
    "X = dfsum[predictors]\n",
    "y = dfsum.target\n",
    "\n",
    "x_trains, x_valids, y_train, y_valid = train_test_split(X, y, test_size=0.3, random_state=12)\n",
    "\n",
    "lgb_model.fit(x_trains, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE on test set:  1.557216855982251\n"
     ]
    }
   ],
   "source": [
    "y_pred = lgb_model.predict(x_valids)\n",
    "rmse = mean_squared_error(y_valid, y_pred)**(1/2)\n",
    "print('RMSE on test set: ', rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ba26898>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lgb.plot_importance(lgb_model, importance_type='gain')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11ba26ac8>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lgb.plot_importance(lgb_model) # defualt: weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE:  1.373259592334425\n",
      "SMAPE 1.1109920509253797\n",
      "R2:  0.6883347065146813\n"
     ]
    }
   ],
   "source": [
    "lgb_model2 = lgb.LGBMRegressor(**lgbparams)\n",
    "lgb_model2.fit(X, y)\n",
    "y_pred3 = lgb_model2.predict(X)\n",
    "print('RMSE: ', mean_squared_error(y, y_pred3)**(1/2))\n",
    "print('SMAPE', smape(y, y_pred3))\n",
    "print('R2: ', r2_score(y, y_pred3))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Probabilistic Modeling vs Machine Learning\n",
    "**BG/NBD Model**\n",
    "- RMSE:  1.6298\n",
    "- R2:  0.5610\n",
    "    \n",
    "**Xgboost**\n",
    "- RMSE:  0.9432\n",
    "- R2:  0.8530\n",
    "\n",
    "### Disadvantages of Probabilistic Model\n",
    "- Only use transaction features. No capability to add other important features like age, gender, education, price, trading behaviors.\n",
    "- Not accurate. The model is built on strong assumptions, which might not be accurate in practical application. True data often doesn’t follow the distribution. "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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    }
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   "metadata": {},
   "source": [
    "## 3. Recommendations\n",
    "- **Champions**: recent, frequent, heavy spenders.     \n",
    "    Reward these customers. They can become early adopters for new products and will help promote your brand.\n",
    "- **Potential Loyalists**: recent, average frequency and spent a good amount.     \n",
    "    Offer membership or loyalty programs or recommend related products to upsell them and help them become your Loyalists or Champions.\n",
    "- **Can’t Lose Them**: used to be frequent, heavy spenders, but haven’t been visiting recently.     \n",
    "    Bring them back with relevant promotions. Run surveys to find out what went wrong and avoid losing them to a competitor.\n",
    "- **New Customers**: recent, spent a good amount, but not frequent shoppers.     \n",
    "    Start building relationships with these customers by providing special offers to increase their visits.\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "https://clevertap.com/blog/rfm-analysis/"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "[1] BG/NBD Model    \n",
    "https://medium.com/bolt-labs/understanding-the-customer-lifetime-value-with-data-science-c14dcafa0364    \n",
    "[2] RFM Analysis    \n",
    "https://www.putler.com/rfm-analysis/    \n",
    "https://clevertap.com/blog/rfm-analysis/"
   ]
  }
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