Customer Lifetime Value (CLV).ipynb

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   "source": [
    "# Customer Lifetime Value (CLV)\n",
    "\n",
    "<br>\n",
    "\n",
    "*Customer Lifetime Value is a monetary value that represents the amount of revenue or profit a customer will give the company over the period of the relationship*\n",
    "\n",
    "- How to Identify the most profitable customers?\n",
    "- How can a company offer the best product and make the most money?\n",
    "- How to segment profitable customers?\n",
    "- How much budget need to spend to acquire customers?"
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "cea2aefa",
   "metadata": {},
   "source": [
    "## Calculate Customer Lifetime Value\n",
    "1. **(Basic approach)** You can compute it by adding profit/revenue from customers in a given cycle. For Example, If the customer is associated with you for the last 3 years, you can sum all the profit in this 3 years. You can average the profit yearly or half-yearly or monthly, but in this approach, you cannot able to build a predictive model for new customers.\n",
    "\n",
    "2. Build **a regression model** for existing customers. Take recent six-month data as independent variables and total revenue over three years as a dependent variable and build a regression model on this data.\n",
    "> ![image.png](attachment:image.png)\n",
    "\n",
    "3. CLTV can also implement using **RFM(Recency, Frequency, Monetary) values**\n",
    "\n",
    "4. Using the following equation: **CLTV = ((Average Order Value x Purchase Frequency)/Churn Rate) x Profit margin**\n",
    "> Customer Value = Average Order Value * Purchase Frequency\n",
    "- **Average Order Value(AOV)**: The Average Order value is the ratio of your total revenue and the total number of orders. AOV represents the mean amount of revenue that the customer spends on an order.\n",
    "> Average Order Value = Total Revenue / Total Number of Orders\n",
    "- **Purchase Frequency(PF)**: Purchase Frequency is the ratio of the total number of orders and the total number of customer. It represents the average number of orders placed by each customer.\n",
    "> Purchase Frequency =  Total Number of Orders / Total Number of Customers\n",
    "- **Churn Rate**: Churn Rate is the percentage of customers who have not ordered again.\n",
    "- **Customer Lifetime**: Customer Lifetime is the period of time that the customer has been continuously ordering.\n",
    "> Customer Lifetime=1/Churn Rate\n",
    "- **Repeat Rate**: Repeat rate can be defined as the ratio of the number of customers with more than one order to the number of unique customers. Example: If you have 10 customers in a month out of who 4 come back, your repeat rate is 40%.\n",
    "> Churn Rate= 1-Repeat Rate\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "b8765fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "8453fe1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>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 08:26:00</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 08:26:00</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 08:26:00</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 08:26:00</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 08:26:00</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  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "          InvoiceDate  UnitPrice  CustomerID         Country  \n",
       "0 2010-12-01 08:26:00       2.55     17850.0  United Kingdom  \n",
       "1 2010-12-01 08:26:00       3.39     17850.0  United Kingdom  \n",
       "2 2010-12-01 08:26:00       2.75     17850.0  United Kingdom  \n",
       "3 2010-12-01 08:26:00       3.39     17850.0  United Kingdom  \n",
       "4 2010-12-01 08:26:00       3.39     17850.0  United Kingdom  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"/QXJ/Python/Datacamp/Marketing/Online_Retail.xlsx\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "738bea3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(541909, 8)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "4eef06e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>CustomerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>17850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13047.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>France</td>\n",
       "      <td>12583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13748.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536969</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537255</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538064</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538812</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>14569.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541768</th>\n",
       "      <td>Germany</td>\n",
       "      <td>12713.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4389 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  CustomerID\n",
       "0       United Kingdom     17850.0\n",
       "9       United Kingdom     13047.0\n",
       "26              France     12583.0\n",
       "46      United Kingdom     13748.0\n",
       "65      United Kingdom     15100.0\n",
       "...                ...         ...\n",
       "536969  United Kingdom     13436.0\n",
       "537255  United Kingdom     15520.0\n",
       "538064  United Kingdom     13298.0\n",
       "538812  United Kingdom     14569.0\n",
       "541768         Germany     12713.0\n",
       "\n",
       "[4389 rows x 2 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df = df[['Country','CustomerID']].drop_duplicates()\n",
    "filtered_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "eb5b154b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country       0\n",
       "CustomerID    9\n",
       "dtype: int64"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "0200563d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>CustomerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>17850.0</td>\n",
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       "      <th>9</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13047.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>France</td>\n",
       "      <td>12583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13748.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>536969</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>537255</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>15520.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538064</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>13298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>538812</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>14569.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541768</th>\n",
       "      <td>Germany</td>\n",
       "      <td>12713.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4380 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Country  CustomerID\n",
       "0       United Kingdom     17850.0\n",
       "9       United Kingdom     13047.0\n",
       "26              France     12583.0\n",
       "46      United Kingdom     13748.0\n",
       "65      United Kingdom     15100.0\n",
       "...                ...         ...\n",
       "536969  United Kingdom     13436.0\n",
       "537255  United Kingdom     15520.0\n",
       "538064  United Kingdom     13298.0\n",
       "538812  United Kingdom     14569.0\n",
       "541768         Germany     12713.0\n",
       "\n",
       "[4380 rows x 2 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "fd6aeaad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mfdvHb+CtwzZw/gJgQZfyIWD/jYouIiImVGbkRkS0SJJ+RESLJOlHRLRIkn5ERIsk6UdEtEiSfkREiyTpR0S0SJJ+RESLJOlHRLRIkn5ERIsk6UdEtEiSfkREiyTpR0S0SJJ+RESLJOlHRLRIkn5ERIsk6UdEtMhmJX1J90paIukWSUOlbCdJ10j6bnneseP80yQtk3S3pMM3N/iIiNg4E1HT/xPbs23PKcenAtfangVcW46RtC8wD9gPOAI4W9KUCbh/RESM02Q07xwNXFReXwQc01F+qe1HbN8DLAPmTsL9IyJiAzY36Rv4sqTFkuaXsl1trwQoz7uU8unA/R3XLi9lERFRyZabef3BtldI2gW4RtJdo5yrLmXuemLzB2Q+wO67776ZIUZExLDNqunbXlGeVwGX0zTXPCBpGkB5XlVOXw7s1nH5DGDFBr7uubbn2J4zderUzQkxIiI6bHLSl/Q4SdsNvwZeANwOXAmcWE47EbiivL4SmCdpa0l7ArOARZt6/4iI2Hib07yzK3C5pOGv8wnbX5T0bWChpJOA+4DjAGwvlbQQuANYA5xie+1mRR8RERtlk5O+7e8BB3Qp/xFw2AauWQAs2NR7RkTE5smM3IiIFknSj4hokST9iIgWSdKPiGiRJP2IiBZJ0o+IaJEk/YiIFknSj4hokST9iIgWSdKPiGiRJP2IiBZJ0o+IaJEk/YiIFknSj4hokST9iIgWSdKPiGiRJP2IiBbZnO0So8PMU7+wWdffe+aLeh7DRMUREf2rek1f0hGS7pa0TNKpte8fEdFmVZO+pCnAfwJHAvsCx0vat2YMERFtVrt5Zy6wrGyqjqRLgaOBOyrHEZMoTV39E0PESLWT/nTg/o7j5cCzKscQ0Sr98MenH2Lolzh6HYNsb3YA476ZdBxwuO2/LcevAObaft2I8+YD88vhHwJ3b8ZtdwYe3IzrJ0o/xNEPMUB/xNEPMUB/xNEPMUB/xNEPMcDExLGH7akjC2vX9JcDu3UczwBWjDzJ9rnAuRNxQ0lDtudMxNf6XY+jH2Lolzj6IYZ+iaMfYuiXOPohhsmOo/bonW8DsyTtKen3gHnAlZVjiIhorao1fdtrJL0W+BIwBTjf9tKaMUREtFn1yVm2rwKuqnjLCWkmmgD9EEc/xAD9EUc/xAD9EUc/xAD9EUc/xACTGEfVjtyIiOitrL0TEdEiSfoRES0ycAuulaUeXgTMpOP7s/3eXsUUEd1J2t/27b2Oo00GLukDnwP+B1gCPNqrIMoopY/b/kmvYihx/D7wFmB326+SNAv4Q9uf72VcvSLpaTy2QvCZCvd96Wjv14ihxPHmMeKoXTn6UBm+fSHwCdsP1bqxpJ1Ge9/2jyvGsg1wErAfsE1HDK+c6HsNYtKfYftpvQ4C+APg25JuBs4HvuTe9JpfACwGnl2OlwOfAqom/ZL0/i+wC6DysO3tK8ZwPvA0YCnrKgQGaiTco8rzLsBzgK+W4z8Brq8UA8B2le4zLrafWyoirwSGJC0CLrB9TYXbL6b5+QvYHfhJeb0DcB+wZ4UYhn0UuAs4HHgH8FfAnZNyJ9sD9aBJLC/odRwlFpUf4qXAMuDfgL0qxzBUnr/TUXZrD/4tlgH79PjncUcf/J/4PDCt43ga8Jlex9XrB828nT8DflCS3V3ASyvd+0PACzuOjwTeU/n7/055vq08bwV8dTLuNYg1/RuByyVtAfyGHtQoh9m2pB8CPwTWADsCn5Z0je23Vgrj15K2panRIGkv4JFK9+70gO3JqbmM3w2S9rXdy1VdZ9pe2XH8ALB37SBqNieMEcfTgL+h6Ye7BjjK9s2SngTcQJ1PQM+0/ZrhA9tXS3pnhft2+k15fkjS/jQ5Y+Zk3GgQk/57aJoylrj8yewFSa8HTqRZNOkjwD/Y/k35Y/RdoFbSfzvwRWA3SR8HDgb+utK9Ow1J+iTwWTr+6LhSW3ZxEU3i/2GJYbhCULM58HpJXwIuoflDPA+4ruL9h9VrThjdB2l+P95m+1fDhbZXSPrnSjE8WO71MZqfycuBH1W697BzJe0I/AvN0jSPB/73ZNxo4CZnlV+oI233rBO3xPEO4Dzb3+/y3j41a72SnggcRJPkbrRdfRVBSRd0KXbNmqWkZcCbGdHJ3+1nNMlxvBT4X+Xw67Yvr3n/EsN3bD9d0m22nyZpK5p+p0Nrx9JrpUP37cDzStHXgTNcsSO3pkFM+hcCTwauZv0aZfUhm2X46K6sP1LkvsoxHEvTNvjTcrwDcIjtz9aMox9I+mobk1o3khbZnivp68Df0TQnLLL95Er3X0Jpchz5FvU/ffWMpJfb/tiGRlVNRt4axOade8rj98qjJ8qQzdNp2mw7R4rU/s/89s6apO2HJL2dppll0kl6q+13SfoAXX7Jbb++RhzFXZI+QTOstydNTP0wiqmo1pywAS+ueK9RSdob+HseO5S3RgXhceW52qiqgavpD5O0Hc0v0897dP9lwLNs124bHBnHbSNrTZKW2P6jSvc/yvbnJJ3Y7X3bF9WIo8TSL01MR/VBp3YUkm6lGcGzGFg7XG57caX7TwFeb/t9Ve43aEm/9Hx/FBieePEgcIIrL+Es6TrgT22vqXnfLnGcDzxEsyG9gdcBO9r+6x6G1VqS/sv2wX0QR7fmhJ8Ci23fUjGOg4APAPvQfDKfAvyi5icfSYttH1jrfhuI4Trbf1LlXgOY9L8F/JPt68rxIcC/2X5O5TjOo9nq8Qv0sG9B0uNoPsI/n6Yp4cvAv9r+ReU4pgL/COzL+kMEq7Wxl5p+tyammjX999NM3PssvRvFRGnmmkPT1AXNkMlvA08FPmX7XZXiGKIZwfSpEs8JwFNs/1ON+5cYTgdWAZez/s+k5ozcBcATgE8Cv/3dtH3zRN9rENv0Hzec8AFsX18SX233lUdP+xZKcj+1V/fv8HGa/9AvAl5DM5x1deUYOmchbwMcS5ftOifZ9sAvgRd0lNWaFdzpicAzhps/Sz/Pp2lGsCwGqiR9ANvLJE2xvRa4oFTcahpuevyHzrBoBoTUMlwpfceIGCa8UjSISf97kv6FpokHmjG399QOwvYZte/ZTY87qTo90fZ5kt5g+2vA1yR9rWYAti/rPJZ0CfCVyjH8Tc37jWJ34Ncdx7+h2Uj7V5JqTt77ZVl75xZJ7wJWsq5zswrbNZdb2JCTbH+vs0DSpPzRGcSk/0rgDJqak2jG3Fb/RSvNGW/lsTMeayfbT9F0Un2Ejk6qHhiecbhS0otoatgzehgPwCya5FdNv8yEBT4B3CjpinJ8FHBJ+VRcc8byK2iWeH8t8CZgN2DUxekmQ+kLHNn0eHHFED4NPGNE2aeACe9rGLik72ZVy5rDADdkuDnjxfSuOQNgje1zenDfkf5V0hNoVvz8AE0zx5tqBiDpYdYtsGWasen/WDMG+mQmrO13SroKeC7Nv8drbA+Vt/+qYijH2H4/zcq4ZwBIegPw/loBlKatQ2iS/lU0a+98E5j0pC/pqTQVgCeMWIl1ezr+AE3oPQelI1fS5+g+2QMA2y+pGM5vRwR0DpmU9DXbf1w5jtPpcSdVrNMvM2Eldf2E04PJgzfbfsaIsu/YfnrFGJYAB9AsenaApF2Bj9g+aoxLJ+LeRwPHAC+hmS8x7GHgUtsT3r8xSDX9d5fnl9KMjvhYOT4euLcH8fRLc0Y/dFINt0++n2ZdpEdpFtN608h2zEm691Nt3yVp5MdnYHJGSIyi2sJaY/gC6ypJ29IsI3w3Ta1z0kk6HvhLYE9JncluO+qve/Mr249KWiNpe5pKUpXfD9tXAFdIerbtG2rcc2CSfukcRNI7bT+v463PlanmtfW8OQP6ppMKmjbk/6QZMQPNML1LgGdVuPebgfk0i/GNNCkjJEbR65mwAIycnFf+IL66Ygjfoum03Zn1fy4PA7dVjAOaxQB3AD5MM3Lp58CiyjEcK2kp8CuaBRIPAN5o+2OjX7bxBqZ5Z5ikO4EXDdcgJe0JXGV7n95G1jt90EmFpJtsP2tE2Y22D6oZR2xYt6aWtpE0E9jedtU/PJJusT27rJV1DE0F8TrbB0z0vQampt/hTTTL1w43G8ykbg0G+O0fm9fx2KGStfsWetZJNcJ1kk6l2VDGwMuAL5QVDqv0Maj7loU/pVmGe9Uk37uvtikcEc8WNCNHqg006OhUf8xbVFqLaEPNfcPvVW7226o8vxC4xPaPJU3KjQYu6dv+oprt155aiu6y3YtNQz4LnEcz47GXyzz/Oes6qf5muJOqB3G8rDzPL8/D/6NfSb0+hpNo+hSGJ+8dQrPpzt6S3mH7oxu6cAL01TaFrB/PGpo2/ss2cO6Es90P/x7dmvuG1W72+5yku2iad/6uDPn+n8m40SA27/SsNjcijsc0Z/SC1i2hu5hmP9aHgdtt1+qweyZwv+0fluMTabbFuxc4vfJU988Bf2v7gXK8K3AO8Lc069rvP8n3r7qw1hixHGf7U2OVRT2lr+dnttdK+n2aZqYfTvh9BjDpf4GmNvdVmtrkIZTaHDDZtbnOOP6SZvLPl1l/qGTNj4xIOht4G03H6VtoOqluqTUzVM3G8M8vH1efR9O88zpgNs2euX9eI44Sy3qri6r5/LzE9v61hgnWXFhrjDi6DZVsbZu+pOfw2KbYak2gkk7oVj4ZMQxc8w5NU8o+XWpzz6KZnVsl6QN/RDPb8FDWX0+/5gJjAv6P7YeAD0n6IvU7qaZ01OZfBpxblkO4TNItFeMA+Iakz9PMdITmE8fXyyzUhyrF8C1JH6TCwlrdSDqSpt14uqSzOt7anqaZp3UkfRTYC7iFdbPWTd1+r2d2vN4GOAy4eTJiGMSkP3M44RergL1LTfM3G7poEhwLPNn2r8c8c5LYtqTPUqZy2763B2FMkbSlmyWmD2Ndmz7U//93Ck2iP5jmU+DFwGVuPu7Wqn1XW1hrA1YAQzSTgTrXi3+YHgwp7hNzgH3dw2YP26/rPC7DvSelgjqISb8fanMAtwI70PzR6aUbJT3T9rd7dP9LaBZXe5Cmk+obAJKeQtPXUk35pf50efREr5t2bN8q6XbgBa64gU2fu51mQufKXgfS4Zc0TdITbhDb9MX6tblvsq42VzOO62m2Rvw267fp1x6yeQfNuv730jQnVN+DVM1GGdOAL7us469m9c/H12jW6IfhgR2x7Ar8G/Ak20dK2hd4tu3zasVQ4vgi8JJefhLtF2o2PJpNMyGrJ7+rI5aRmUKzqcxC2xO+LPrAJf1+IanrGjvDM4cr3H932/dJ2mMDcXy/RhyxPklXAxfQbPRzgKQtaYbTVtm+siOO/0czNv9K1u9bqDpfoB/0+ne1SwxraCokx9s+ZaLvNXDNO+qDjaclbQH852QPARzDZ2k2yfi+pMts/1kPY+kbkp4LzLJ9gaSdge1s19xvYWfbCyWdBmB7jaReLHm9ojy2oP/mEFRVM7mPFoOk2TTrEf0FzR4gkzJvYuCSPs2OPz3deLos3nTrcG27R2F0Tuerurhavyqzk+fQNHddQLOj2cdomgJr+YWkJ1I+ypemr6p9G7Bukx9J2zWHzQ5abSLpm7af26X5r+as4L1phlMfT7PQ3CdpWmAmre9nEJP+A71M+B2mAUslLWL9j8+12gm9gddtdizwdJqhcNheUZJeTW+haVLZS9J/AVOB4yrHMLwe00eBncrxg8AJtpfWjqWH/gp6Pjv4LprBDUfZXgYgaVJHUQ1i0h+S9El6vPE0ZUOIHjpA0s9oai3bltfQg+auPvLrMox1uJZdfe9k24tL++0f0vws7rZdcyjxsHOBN7vsJy3pEJpVJp8zyjWD5nLKblU9bAL9M5qa/nWlc/1S1v+UPuEGMen3xcbTpY1uD5r246+UadVTKt6/2r1+hywsHZg7SHoVzbo/H64ZgKT/Bv7d9oc6yj5v+8U14wAeN5zwAWxf34s/gj3W8yZQ25cDl5d/+2No5krsKukc4HLbX57oe2b0ziQpSWU+sJPtvcoicB+yfViPQ2s1SX9KUyEQzY5V11S+/100czh+Cbza9q9rLQExIo7LaZq5hicAvRyYY/uYmnH0UueyE/20BIWalWePA17mSdhRbWCSvqS32n6XpA/QpQ3bdtV9c8sSA3OBm4Z/oUeu/RK9U0bu/KgH8zdutv0MSW+l+Wj/FzQ1uqoJpyzudQbNHrnQLFFyhps9pluhjJoanruyLc0fYhjwJtBBat4Z7rwdGvWseh4ptTgAynjswfgL+zumjJA5E/gx8E6a2u3OwBaSTrD9xZrhAJQKymLgS5TO1Co3l7YBXgM8BVgCvKVHfQo919Ym0EFK+vcBdJtaLunk+uHwNUlvo+lE/VPg72jW1o/6Pkiz0ugTaFZfPdL2jZKeSrNMRM2k/9utEW1fK+lw1u1jXMNFNPv0foNmQ519gDdWvH/02CA173wPOM724hHlZ9AMh6r98XkLmk07hjuUv2S7F5uXtJ7KVnTl9Z3u2Dqzdnu6pGtH9ut0K5vE+/+2ibF8+lzUL23ZUccWvQ5gAh0HfErSs6FZg0fSh4D/RbOmfhWSjpZ0iu1HbX8Y2INmQtDbJFVbOz7W07lz2a9GvFel1iNpm9JBt7OkHSXtVB4zgSfViKH4bVOOm5VPo2UGpqYPIOlpNGNvTwFeVYqPr7moVJlwM8/2/eX4Fpplcx8PXJDRO/WN0WG3je2tNnTtBMbwBppmlCfRLH8w7GfAh21/cLJjKHEM/1vA+v8eA915GesMTNIvtShoNgD/LPAV4LWUWp4rbcsn6du2n9lx/EHbry2vb7R9UI04oj9Jep3tD/Q6jmivQUr697Duo/rwpAuzrgZTZfKFpGW2n7KB9/7b9l414oj+IulQ219V9z2cezFjPFpqYEbv2N6z1zEUN0l6VWnP/y1Jr6ZZrzva6Y9pRg4d1eW96jPGo70GpqbfLyTtwrp1f4Y3CDkQ2Bo4xutv5RgRUVWS/iSRdCiwXzlcavurvYwn+kNZe+dGmnHyX7d9R49DipZJ0o+oSNLWwLNohhIfDDwVuNX2sT0NLFpjYNr0O0bvdFVr9E7EGNbSjJVfSzOy7AFgVU8jilYZmJp+x+gdAbsDPymvdwDu66OO3mgxSb+kWfPmvcBXbP+oxyFFywxM0h9WZuFeafuqcnwk8Hzbb+ltZBHNjG2alS3nAr8GvkXTtn9tTwOL1hjEpL/Y9oEjyoZsz+lVTBEjlcXejqSZpbuL7W17G1G0xSCtvTPsQUn/LGmmpD0k/RPNhsMRPSfpsjKC5/3A44BXADv2Nqpok0FM+sfTbDZ9eXlMLWURPSPpmZL+gGZd/72BT9A08fw58Pu9jC3aZeCad4ZJerztn/c6jghodsyi6Vv6saTn0WyA/TpgNrCP7azAGlUMXE1f0nMk3QHcUY4PkHR2j8OKmNIxbPhlwLm2L7P9LzS7WEVUMXBJH3gfcDilHd/2rcDzehpRBEwpm5YAHEazDs+wgZkvE/1vIP+z2b5/eG/aYm2vYokoLqHZQvNBmo1cvgEg6SnAT3sZWLTLICb9+yU9B7Ck3wNez7pN0yN6wvYCSdcC04Ave11n2hY0bfsRVQxcR66knWmGwz2fZkbul4HXZxmGiIjBTPoH2/6vscoiItpoEJP+zbafMVZZREQbDUybvqRnA88Bpkp6c8db2wNTehNVRER/GZikD/we8Hia72m7jvKf0cx6jIhovUFs3tnD9vd7HUdERD8amKQv6T9sv1HS52jW1V+P7Zf0IKyIiL4ySM07Hy3P7+5pFBERfWxgavoRETG2QarpA82YfOB0YA+a70+AbT+5l3FFRPSDgavpS7oLeBOwmI41d7IXaUTEANb0gZ/avrrXQURE9KNBrOmfSTMZ6zPAI8Pltm/uWVAREX1iEJP+dV2KbfvQ6sFERPSZgUv6ERGxYQPTpj9ivR1oJmg9CHzT9j09CCkiou8M0naJ2414bA/MAa6WNK+XgUVE9IuBb96RtBPwlSytHBExWDX9rsqOWRrzxIiIFhj4pC/pUOAnvY4jIqIfDFJH7hIeu7rmTsAK4IT6EUVE9J+BadOXtMeIIgM/sv2LXsQTEdGPBibpR0TE2Aa+TT8iItZJ0o+IaJEk/YiIFknSj4hokST9iIgW+f+cZpKg96gx0AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# top 10 country's customer\n",
    "filtered_df['Country'].value_counts()[:10].plot(kind = 'bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "f0e529af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 495478 entries, 0 to 541893\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count   Dtype         \n",
      "---  ------       --------------   -----         \n",
      " 0   InvoiceNo    495478 non-null  object        \n",
      " 1   StockCode    495478 non-null  object        \n",
      " 2   Description  494024 non-null  object        \n",
      " 3   Quantity     495478 non-null  int64         \n",
      " 4   InvoiceDate  495478 non-null  datetime64[ns]\n",
      " 5   UnitPrice    495478 non-null  float64       \n",
      " 6   CustomerID   361878 non-null  float64       \n",
      " 7   Country      495478 non-null  object        \n",
      "dtypes: datetime64[ns](1), float64(2), int64(1), object(4)\n",
      "memory usage: 34.0+ MB\n"
     ]
    }
   ],
   "source": [
    "# filter cusomters from UK\n",
    "uk_df = df[df['Country'] == 'United Kingdom']\n",
    "uk_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "ef9b8c40",
   "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>Quantity</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>495478.000000</td>\n",
       "      <td>495478.000000</td>\n",
       "      <td>361878.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.605486</td>\n",
       "      <td>4.532422</td>\n",
       "      <td>15547.871368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>227.588756</td>\n",
       "      <td>99.315438</td>\n",
       "      <td>1594.402590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-80995.000000</td>\n",
       "      <td>-11062.060000</td>\n",
       "      <td>12346.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>14194.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.100000</td>\n",
       "      <td>15514.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>4.130000</td>\n",
       "      <td>16931.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>80995.000000</td>\n",
       "      <td>38970.000000</td>\n",
       "      <td>18287.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Quantity      UnitPrice     CustomerID\n",
       "count  495478.000000  495478.000000  361878.000000\n",
       "mean        8.605486       4.532422   15547.871368\n",
       "std       227.588756      99.315438    1594.402590\n",
       "min    -80995.000000  -11062.060000   12346.000000\n",
       "25%         1.000000       1.250000   14194.000000\n",
       "50%         3.000000       2.100000   15514.000000\n",
       "75%        10.000000       4.130000   16931.000000\n",
       "max     80995.000000   38970.000000   18287.000000"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ab91721",
   "metadata": {},
   "source": [
    "*you can observe some of the customers have ordered in a negative quantity, which is not possible. So, you need to filter Quantity greater than zero*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "1e203708",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 486286 entries, 0 to 541893\n",
      "Data columns (total 8 columns):\n",
      " #   Column       Non-Null Count   Dtype         \n",
      "---  ------       --------------   -----         \n",
      " 0   InvoiceNo    486286 non-null  object        \n",
      " 1   StockCode    486286 non-null  object        \n",
      " 2   Description  485694 non-null  object        \n",
      " 3   Quantity     486286 non-null  int64         \n",
      " 4   InvoiceDate  486286 non-null  datetime64[ns]\n",
      " 5   UnitPrice    486286 non-null  float64       \n",
      " 6   CustomerID   354345 non-null  float64       \n",
      " 7   Country      486286 non-null  object        \n",
      "dtypes: datetime64[ns](1), float64(2), int64(1), object(4)\n",
      "memory usage: 33.4+ MB\n"
     ]
    }
   ],
   "source": [
    "uk_df = uk_df[uk_df['Quantity'] > 0]\n",
    "uk_df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ccca5de",
   "metadata": {},
   "source": [
    "### 1. Filter required Columns and calculate CLV\n",
    "*Here, you can filter the necessary columns for calculating CLTV. You only need her five columns CustomerID, InvoiceDate, InvoiceNo, Quantity, and UnitPrice.*\n",
    "\n",
    "- **CustomerID** will uniquely define your customers.\n",
    "- **InvoiceDate** help you calculate numbers of days customer stayed with your product.\n",
    "- **InvoiceNo** helps you to count the number of time transaction performed(frequency).\n",
    "- **Quantity** is purchased item units in each transaction\n",
    "- **UnitPrice** of each unit purchased by the customer will help you to calculate the total purchased amount."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "f073531c",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "   CustomerID         InvoiceDate InvoiceNo  Quantity  UnitPrice  tot_value\n",
       "0     17850.0 2010-12-01 08:26:00    536365         6       2.55      15.30\n",
       "1     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df = uk_df[['CustomerID', 'InvoiceDate', 'InvoiceNo',\n",
    "               'Quantity', 'UnitPrice']].reset_index(drop = True)\n",
    "# add a total price\n",
    "uk_df['tot_value'] = uk_df['Quantity'] * uk_df['UnitPrice']\n",
    "uk_df.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2c130d2",
   "metadata": {},
   "source": [
    "- Calculate the number of days between the present date and the date of last purchase from each customer.\n",
    "- Calculate the number of orders for each customer.\n",
    "- Calculate sum of purchase price for each customer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "6ca6529c",
   "metadata": {},
   "outputs": [
    {
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       "            InvoiceDate  InvoiceNo  Quantity  tot_value\n",
       "CustomerID                                             \n",
       "12346.0               0          1     74215   77183.60\n",
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       "12820.0             323         59       722     942.34"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"uk_data_group=uk_df.groupby('CustomerID').agg({'InvoiceDate': lambda date: (date.max() - date.min()).days,\n",
    "                                        'InvoiceNo': lambda num: len(num),\n",
    "                                        'Quantity': lambda quant: quant.sum(),\n",
    "                                        'tot_value': lambda price: price.sum()})\n",
    "uk_data_group.head()\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "55b6142d",
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      "text/plain": [
       "            InvoiceDate  InvoiceNo  tot_value  Quantity\n",
       "CustomerID                                             \n",
       "12346.0               0          1   77183.60     74215\n",
       "12747.0             366        103    4196.01      1275\n",
       "12748.0             372       4596   33719.73     25748\n",
       "12749.0             209        199    4090.88      1471\n",
       "12820.0             323         59     942.34       722"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df_group = uk_df.groupby('CustomerID')\\\n",
    ".agg({'InvoiceDate': lambda date: (date.max() - date.min()).days,\n",
    "      'InvoiceNo':'count', 'tot_value':'sum', 'Quantity': 'sum'})\n",
    "uk_df_group.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "1b030660",
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   "outputs": [
    {
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       "<p>3921 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            num_days  num_orders  tot_value  quantity\n",
       "CustomerID                                           \n",
       "12346.0            0           1   77183.60     74215\n",
       "12747.0          366         103    4196.01      1275\n",
       "12748.0          372        4596   33719.73     25748\n",
       "12749.0          209         199    4090.88      1471\n",
       "12820.0          323          59     942.34       722\n",
       "...              ...         ...        ...       ...\n",
       "18280.0            0          10     180.60        45\n",
       "18281.0            0           7      80.82        54\n",
       "18282.0          118          12     178.05       103\n",
       "18283.0          333         756    2094.88      1397\n",
       "18287.0          158          70    1837.28      1586\n",
       "\n",
       "[3921 rows x 4 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df_n = pd.DataFrame(uk_df_group)\n",
    "uk_df_n.columns = ['num_days', 'num_orders', 'tot_value','quantity']\n",
    "uk_df_n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b58e35f",
   "metadata": {},
   "source": [
    "> CLTV = ((Average Order Value x Purchase Frequency)/Churn Rate) x Profit margin.\n",
    "\n",
    "> Customer Value = Average Order Value * Purchase Frequency\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d38ec12a",
   "metadata": {},
   "source": [
    "#### 1. Calculate Average Order Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "4b0dec48",
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "            num_days  num_orders  tot_value  quantity  avg_order_value\n",
       "CustomerID                                                            \n",
       "12346.0            0           1   77183.60     74215     77183.600000\n",
       "12747.0          366         103    4196.01      1275        40.737961\n",
       "12748.0          372        4596   33719.73     25748         7.336756\n",
       "12749.0          209         199    4090.88      1471        20.557186\n",
       "12820.0          323          59     942.34       722        15.971864"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df_n['avg_order_value'] = uk_df_n['tot_value'] / uk_df_n['num_orders']\n",
    "uk_df_n.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78757aab",
   "metadata": {},
   "source": [
    "#### 2. Calculate Purchase Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "b1a2f7a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "90.37107880642694"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purchase_freq = sum(uk_df_n['num_orders'])/uk_df_n.shape[0]\n",
    "purchase_freq"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "818dc3af",
   "metadata": {},
   "source": [
    "#### 3. Calculate Repeat Rate and Churn Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "967c66e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9818923743942872"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# repeat rate\n",
    "repeat_rate = uk_df_n[uk_df_n['num_orders']>1].shape[0]/uk_df_n.shape[0]\n",
    "repeat_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "355d3aa3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.018107625605712774"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# churn rate\n",
    "churn_rate = 1 - repeat_rate\n",
    "churn_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "d7b9cbe2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(90.37107880642694, 0.9818923743942872, 0.018107625605712774)\n"
     ]
    }
   ],
   "source": [
    "print((purchase_freq, repeat_rate, churn_rate))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10ac85b5",
   "metadata": {},
   "source": [
    "#### 4. Calculate Profit Margin\n",
    "\n",
    "<br>\n",
    "\n",
    "*Profit margin is the commonly used profitability ratio. It represents how much percentage of total sales has earned as the gain. Let's assume our business has approx 5% profit on the total sale.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "672cf299",
   "metadata": {},
   "outputs": [
    {
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       "</table>\n",
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      ],
      "text/plain": [
       "            num_days  num_orders  tot_value  quantity  avg_order_value  \\\n",
       "CustomerID                                                               \n",
       "12346.0            0           1   77183.60     74215     77183.600000   \n",
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       "12748.0          372        4596   33719.73     25748         7.336756   \n",
       "12749.0          209         199    4090.88      1471        20.557186   \n",
       "12820.0          323          59     942.34       722        15.971864   \n",
       "\n",
       "            profit_margin  \n",
       "CustomerID                 \n",
       "12346.0         3859.1800  \n",
       "12747.0          209.8005  \n",
       "12748.0         1685.9865  \n",
       "12749.0          204.5440  \n",
       "12820.0           47.1170  "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# profit margin\n",
    "uk_df_n['profit_margin'] = uk_df_n['tot_value'] * 0.05\n",
    "uk_df_n.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "8db17c24",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "            num_days  num_orders  tot_value  quantity  avg_order_value  \\\n",
       "CustomerID                                                               \n",
       "12346.0            0           1   77183.60     74215     77183.600000   \n",
       "12747.0          366         103    4196.01      1275        40.737961   \n",
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       "12820.0          323          59     942.34       722        15.971864   \n",
       "\n",
       "            profit_margin           CLV  \n",
       "CustomerID                               \n",
       "12346.0         3859.1800  3.852060e+08  \n",
       "12747.0          209.8005  2.033140e+05  \n",
       "12748.0         1685.9865  3.661610e+04  \n",
       "12749.0          204.5440  1.025963e+05  \n",
       "12820.0           47.1170  7.971198e+04  "
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df_n['CLV'] = uk_df_n['avg_order_value'] * purchase_freq / churn_rate\n",
    "uk_df_n.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "13c4dac0",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "            num_days  num_orders  tot_value  quantity  avg_order_value  \\\n",
       "CustomerID                                                               \n",
       "12346.0            0           1   77183.60     74215     77183.600000   \n",
       "12747.0          366         103    4196.01      1275        40.737961   \n",
       "12748.0          372        4596   33719.73     25748         7.336756   \n",
       "12749.0          209         199    4090.88      1471        20.557186   \n",
       "12820.0          323          59     942.34       722        15.971864   \n",
       "\n",
       "            profit_margin           CLV  cust_lifetime_value  \n",
       "CustomerID                                                    \n",
       "12346.0         3859.1800  3.852060e+08         1.486579e+12  \n",
       "12747.0          209.8005  2.033140e+05         4.265538e+07  \n",
       "12748.0         1685.9865  3.661610e+04         6.173424e+07  \n",
       "12749.0          204.5440  1.025963e+05         2.098545e+07  \n",
       "12820.0           47.1170  7.971198e+04         3.755789e+06  "
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df_n['cust_lifetime_value'] = uk_df_n['CLV'] * uk_df_n['profit_margin']\n",
    "uk_df_n.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5778b31",
   "metadata": {},
   "source": [
    "### 2. Prediction Model for CLV\n",
    "#### predict CLTV using Linear Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "35e73902",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "   CustomerID         InvoiceDate InvoiceNo  Quantity  UnitPrice  tot_value\n",
       "0     17850.0 2010-12-01 08:26:00    536365         6       2.55      15.30\n",
       "1     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34\n",
       "2     17850.0 2010-12-01 08:26:00    536365         8       2.75      22.00\n",
       "3     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34\n",
       "4     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "dab9a201",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Dec-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17850.0</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>536365</td>\n",
       "      <td>6</td>\n",
       "      <td>3.39</td>\n",
       "      <td>20.34</td>\n",
       "      <td>Dec-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17850.0</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>536365</td>\n",
       "      <td>8</td>\n",
       "      <td>2.75</td>\n",
       "      <td>22.00</td>\n",
       "      <td>Dec-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17850.0</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>536365</td>\n",
       "      <td>6</td>\n",
       "      <td>3.39</td>\n",
       "      <td>20.34</td>\n",
       "      <td>Dec-2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17850.0</td>\n",
       "      <td>2010-12-01 08:26:00</td>\n",
       "      <td>536365</td>\n",
       "      <td>6</td>\n",
       "      <td>3.39</td>\n",
       "      <td>20.34</td>\n",
       "      <td>Dec-2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CustomerID         InvoiceDate InvoiceNo  Quantity  UnitPrice  tot_value  \\\n",
       "0     17850.0 2010-12-01 08:26:00    536365         6       2.55      15.30   \n",
       "1     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34   \n",
       "2     17850.0 2010-12-01 08:26:00    536365         8       2.75      22.00   \n",
       "3     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34   \n",
       "4     17850.0 2010-12-01 08:26:00    536365         6       3.39      20.34   \n",
       "\n",
       "   month_yr  \n",
       "0  Dec-2010  \n",
       "1  Dec-2010  \n",
       "2  Dec-2010  \n",
       "3  Dec-2010  \n",
       "4  Dec-2010  "
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk_df['month_yr'] = uk_df['InvoiceDate'].apply(lambda x: x.strftime('%b-%Y'))\n",
    "uk_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "b2cfea01",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>month_yr</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Apr-2011</th>\n",
       "      <th>Aug-2011</th>\n",
       "      <th>Dec-2010</th>\n",
       "      <th>Dec-2011</th>\n",
       "      <th>Feb-2011</th>\n",
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       "      <td>12747.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>301.70</td>\n",
       "      <td>706.27</td>\n",
       "      <td>438.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>303.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>376.30</td>\n",
       "      <td>310.78</td>\n",
       "      <td>771.31</td>\n",
       "      <td>312.73</td>\n",
       "      <td>675.38</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12748.0</td>\n",
       "      <td>1100.37</td>\n",
       "      <td>898.24</td>\n",
       "      <td>4228.13</td>\n",
       "      <td>1070.27</td>\n",
       "      <td>389.64</td>\n",
       "      <td>418.77</td>\n",
       "      <td>1113.27</td>\n",
       "      <td>2006.26</td>\n",
       "      <td>1179.37</td>\n",
       "      <td>2234.50</td>\n",
       "      <td>10639.23</td>\n",
       "      <td>2292.84</td>\n",
       "      <td>6148.84</td>\n",
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       "      <td>859.10</td>\n",
       "      <td>572.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12820.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>210.35</td>\n",
       "      <td>0.00</td>\n",
       "      <td>170.46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
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       "      <td>0.00</td>\n",
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       "      <td>217.77</td>\n",
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      "text/plain": [
       "month_yr  CustomerID  Apr-2011  Aug-2011  Dec-2010  Dec-2011  Feb-2011  \\\n",
       "0            12346.0      0.00      0.00      0.00      0.00      0.00   \n",
       "1            12747.0      0.00    301.70    706.27    438.50      0.00   \n",
       "2            12748.0   1100.37    898.24   4228.13   1070.27    389.64   \n",
       "3            12749.0      0.00   1896.13      0.00    763.06      0.00   \n",
       "4            12820.0      0.00      0.00      0.00    210.35      0.00   \n",
       "\n",
       "month_yr  Jan-2011  Jul-2011  Jun-2011  Mar-2011  May-2011  Nov-2011  \\\n",
       "0         77183.60      0.00      0.00      0.00      0.00      0.00   \n",
       "1           303.04      0.00    376.30    310.78    771.31    312.73   \n",
       "2           418.77   1113.27   2006.26   1179.37   2234.50  10639.23   \n",
       "3             0.00      0.00      0.00      0.00    859.10    572.59   \n",
       "4           170.46      0.00      0.00      0.00      0.00      0.00   \n",
       "\n",
       "month_yr  Oct-2011  Sep-2011  \n",
       "0             0.00      0.00  \n",
       "1           675.38      0.00  \n",
       "2          2292.84   6148.84  \n",
       "3             0.00      0.00  \n",
       "4           343.76    217.77  "
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk = uk_df.pivot_table(index = 'CustomerID', \n",
    "                       columns = 'month_yr', values = 'tot_value', \n",
    "                       aggfunc = 'sum', fill_value = 0).reset_index()\n",
    "uk.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "f184effa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>month_yr</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Apr-2011</th>\n",
       "      <th>Aug-2011</th>\n",
       "      <th>Dec-2010</th>\n",
       "      <th>Dec-2011</th>\n",
       "      <th>Feb-2011</th>\n",
       "      <th>Jan-2011</th>\n",
       "      <th>Jul-2011</th>\n",
       "      <th>Jun-2011</th>\n",
       "      <th>Mar-2011</th>\n",
       "      <th>May-2011</th>\n",
       "      <th>Nov-2011</th>\n",
       "      <th>Oct-2011</th>\n",
       "      <th>Sep-2011</th>\n",
       "      <th>CLV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>12346.0</td>\n",
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       "      <td>0.00</td>\n",
       "      <td>77183.60</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12747.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>301.70</td>\n",
       "      <td>706.27</td>\n",
       "      <td>438.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>303.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>376.30</td>\n",
       "      <td>310.78</td>\n",
       "      <td>771.31</td>\n",
       "      <td>312.73</td>\n",
       "      <td>675.38</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4196.01</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12748.0</td>\n",
       "      <td>1100.37</td>\n",
       "      <td>898.24</td>\n",
       "      <td>4228.13</td>\n",
       "      <td>1070.27</td>\n",
       "      <td>389.64</td>\n",
       "      <td>418.77</td>\n",
       "      <td>1113.27</td>\n",
       "      <td>2006.26</td>\n",
       "      <td>1179.37</td>\n",
       "      <td>2234.50</td>\n",
       "      <td>10639.23</td>\n",
       "      <td>2292.84</td>\n",
       "      <td>6148.84</td>\n",
       "      <td>32619.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12749.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1896.13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>763.06</td>\n",
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       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>859.10</td>\n",
       "      <td>572.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4090.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12820.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>210.35</td>\n",
       "      <td>0.00</td>\n",
       "      <td>170.46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>343.76</td>\n",
       "      <td>217.77</td>\n",
       "      <td>942.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "month_yr  CustomerID  Apr-2011  Aug-2011  Dec-2010  Dec-2011  Feb-2011  \\\n",
       "0            12346.0      0.00      0.00      0.00      0.00      0.00   \n",
       "1            12747.0      0.00    301.70    706.27    438.50      0.00   \n",
       "2            12748.0   1100.37    898.24   4228.13   1070.27    389.64   \n",
       "3            12749.0      0.00   1896.13      0.00    763.06      0.00   \n",
       "4            12820.0      0.00      0.00      0.00    210.35      0.00   \n",
       "\n",
       "month_yr  Jan-2011  Jul-2011  Jun-2011  Mar-2011  May-2011  Nov-2011  \\\n",
       "0         77183.60      0.00      0.00      0.00      0.00      0.00   \n",
       "1           303.04      0.00    376.30    310.78    771.31    312.73   \n",
       "2           418.77   1113.27   2006.26   1179.37   2234.50  10639.23   \n",
       "3             0.00      0.00      0.00      0.00    859.10    572.59   \n",
       "4           170.46      0.00      0.00      0.00      0.00      0.00   \n",
       "\n",
       "month_yr  Oct-2011  Sep-2011       CLV  \n",
       "0             0.00      0.00  77183.60  \n",
       "1           675.38      0.00   4196.01  \n",
       "2          2292.84   6148.84  32619.36  \n",
       "3             0.00      0.00   4090.88  \n",
       "4           343.76    217.77    942.34  "
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "uk['CLV'] = uk.iloc[:, 2:].sum(axis=1)\n",
    "uk.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f410f3fb",
   "metadata": {},
   "source": [
    "#### Selecting feature\n",
    "*divide the given columns into two types of variables dependent(or target variable) and independent variable(or feature variables). Select latest 6 month as independent variable.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "1f430f74",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = uk[['Dec-2011','Nov-2011', 'Oct-2011','Sep-2011','Aug-2011','Jul-2011']]\n",
    "y = uk[['CLV']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eccda6f",
   "metadata": {},
   "source": [
    "#### Splitting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "d24d8bfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#split training set and test set\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y,random_state=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff76d498",
   "metadata": {},
   "source": [
    "#### Model development"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "d7a71554",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import model\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "# instantiate\n",
    "linreg = LinearRegression()\n",
    "\n",
    "# fit the model to the training data (learn the coefficients)\n",
    "linreg.fit(X_train, y_train)\n",
    "\n",
    "# make predictions on the testing set\n",
    "y_pred = linreg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "ada16cec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[208.50969617]\n",
      "[[0.99880551 0.80381254 1.60226829 1.67433228 1.52860813 2.87959449]]\n"
     ]
    }
   ],
   "source": [
    "# print the intercept and coefficients\n",
    "print(linreg.intercept_)\n",
    "print(linreg.coef_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68a1f9ff",
   "metadata": {},
   "source": [
    "#### How well does the model fit the data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "85b00f81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-Square: 0.9666074402817512\n"
     ]
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "\n",
    "# compute the R Square for model\n",
    "print(\"R-Square:\",metrics.r2_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c781e5c0",
   "metadata": {},
   "source": [
    "*This model has a higher R-squared (0.96). This model provides a better fit to the data.*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eb82541",
   "metadata": {},
   "source": [
    "#### Evaluate the model\n",
    "For regression problems following evaluation metrics used (Ritchie Ng):\n",
    "\n",
    "- **Mean Absolute Error (MAE)** is the mean of the absolute value of the errors.\n",
    "- **Mean Squared Error (MSE)** is the mean of the squared errors.\n",
    "- **Root Mean Squared Error (RMSE)** is the square root of the mean of the squared errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "1d6fa4e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 595.0282284701236\n",
      "MSE 2114139.8898678934\n",
      "RMSE: 1454.0082151995887\n"
     ]
    }
   ],
   "source": [
    "# calculate MAE using scikit-learn\n",
    "print(\"MAE:\",metrics.mean_absolute_error(y_test,y_pred))\n",
    "\n",
    "#calculate mean squared error\n",
    "print(\"MSE\",metrics.mean_squared_error(y_test, y_pred))\n",
    "# compute the RMSE of our predictions\n",
    "print(\"RMSE:\",np.sqrt(metrics.mean_squared_error(y_test, y_pred)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "929edef0",
   "metadata": {},
   "source": [
    "*RMSE is more popular than MSE and MAE because RMSE is interpretable with y because of the same units.*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b52da5d",
   "metadata": {},
   "source": [
    "### 3. Pros and Cons of CLTV\n",
    "\n",
    "<br>\n",
    "\n",
    "*CLTV helps you to design an effective business plan and also provide a chance to scale your business. CLTV draw meaningful customer segments these segment can help you to identify needs of the different-different segment.*\n",
    "\n",
    "*.**Customer Lifetime Value** is a tool, not a strategy. CLTV can figure out most profitable customers, but how you are going to make a profit from them, it depends on your strategy. Generally, CLTV models are confused and misused. Obsession with CLTV may create blinders. Companies only focus on finding the best customer group and focusing on them and repeat the business, but it’s also important to give attention to other customers.*"
   ]
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   "source": []
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