dano2025/full_analysis/segment_matrix.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "91de22bd",
   "metadata": {},
   "source": [
    "# Матрица выводов по сегментам\n",
    "\n",
    "Ответ на фидбек организаторов: делаем матрицу по возрастным сегментам и типам каналов, фиксируем закономерности и идеи изменений."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "16660d45",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T18:42:58.838813Z",
     "iopub.status.busy": "2025-12-12T18:42:58.838553Z",
     "iopub.status.idle": "2025-12-12T18:43:05.571711Z",
     "shell.execute_reply": "2025-12-12T18:43:05.569612Z"
    }
   },
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "from pathlib import Path\n",
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 5)\n",
    "\n",
    "project_root = Path.cwd().resolve()\n",
    "if not (project_root / \"preanalysis\").exists():\n",
    "    project_root = project_root.parent\n",
    "sys.path.append(str(project_root / \"preanalysis\"))\n",
    "import eda_utils as eda\n",
    "\n",
    "db_path = project_root / \"dataset\" / \"ds.sqlite\"\n",
    "conn = sqlite3.connect(db_path)\n",
    "df = pd.read_sql_query(\"select * from communications\", conn, parse_dates=[\"business_dt\"])\n",
    "conn.close()\n",
    "\n",
    "age_bins = [15, 25, 35, 45, 55, 120]\n",
    "age_labels = [\"15-24\", \"25-34\", \"35-44\", \"45-54\", \"55+\"]\n",
    "df[\"age_segment\"] = pd.cut(df[\"age\"], bins=age_bins, labels=age_labels, right=False, include_lowest=True)\n",
    "\n",
    "for cols, name in [\n",
    "    (eda.ACTIVE_IMP_COLS, \"active_imp_total\"),\n",
    "    (eda.PASSIVE_IMP_COLS, \"passive_imp_total\"),\n",
    "    (eda.ACTIVE_CLICK_COLS, \"active_click_total\"),\n",
    "    (eda.PASSIVE_CLICK_COLS, \"passive_click_total\"),\n",
    "    (eda.ORDER_COLS, \"orders_amt_total\"),\n",
    "]:\n",
    "    df[name] = df[cols].sum(axis=1)\n",
    "\n",
    "df[\"imp_total\"] = df[\"active_imp_total\"] + df[\"passive_imp_total\"]\n",
    "df[\"click_total\"] = df[\"active_click_total\"] + df[\"passive_click_total\"]\n",
    "\n",
    "df[\"ctr_active\"] = eda.safe_divide(df[\"active_click_total\"], df[\"active_imp_total\"])\n",
    "df[\"ctr_passive\"] = eda.safe_divide(df[\"passive_click_total\"], df[\"passive_imp_total\"])\n",
    "df[\"ctr_all\"] = eda.safe_divide(df[\"click_total\"], df[\"imp_total\"])\n",
    "df[\"cr_click2order\"] = eda.safe_divide(df[\"orders_amt_total\"], df[\"click_total\"])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "317a8a38",
   "metadata": {},
   "source": [
    "## Матрица CTR/CR по 5 возрастным сегментам и каналам"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6743acba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T18:43:05.578992Z",
     "iopub.status.busy": "2025-12-12T18:43:05.578499Z",
     "iopub.status.idle": "2025-12-12T18:43:05.614188Z",
     "shell.execute_reply": "2025-12-12T18:43:05.612157Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1031533/2377539060.py:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  segment_perf = df.groupby(\"age_segment\").agg(\n"
     ]
    },
    {
     "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>ctr_active</th>\n",
       "      <th>ctr_passive</th>\n",
       "      <th>cr_active</th>\n",
       "      <th>cr_passive</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_segment</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15-24</th>\n",
       "      <td>0.669682</td>\n",
       "      <td>0.026672</td>\n",
       "      <td>0.057846</td>\n",
       "      <td>0.627820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25-34</th>\n",
       "      <td>0.675315</td>\n",
       "      <td>0.035316</td>\n",
       "      <td>0.087974</td>\n",
       "      <td>0.707119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35-44</th>\n",
       "      <td>0.672207</td>\n",
       "      <td>0.037188</td>\n",
       "      <td>0.090557</td>\n",
       "      <td>0.741876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45-54</th>\n",
       "      <td>0.668323</td>\n",
       "      <td>0.040513</td>\n",
       "      <td>0.077198</td>\n",
       "      <td>0.631981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55+</th>\n",
       "      <td>0.668371</td>\n",
       "      <td>0.045245</td>\n",
       "      <td>0.077028</td>\n",
       "      <td>0.594488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ctr_active  ctr_passive  cr_active  cr_passive\n",
       "age_segment                                                \n",
       "15-24          0.669682     0.026672   0.057846    0.627820\n",
       "25-34          0.675315     0.035316   0.087974    0.707119\n",
       "35-44          0.672207     0.037188   0.090557    0.741876\n",
       "45-54          0.668323     0.040513   0.077198    0.631981\n",
       "55+            0.668371     0.045245   0.077028    0.594488"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segment_perf = df.groupby(\"age_segment\").agg(\n",
    "    {\n",
    "        \"active_imp_total\": \"sum\",\n",
    "        \"passive_imp_total\": \"sum\",\n",
    "        \"active_click_total\": \"sum\",\n",
    "        \"passive_click_total\": \"sum\",\n",
    "        \"orders_amt_total\": \"sum\",\n",
    "    }\n",
    ")\n",
    "\n",
    "segment_perf[\"ctr_active\"] = eda.safe_divide(segment_perf[\"active_click_total\"], segment_perf[\"active_imp_total\"])\n",
    "segment_perf[\"ctr_passive\"] = eda.safe_divide(segment_perf[\"passive_click_total\"], segment_perf[\"passive_imp_total\"])\n",
    "segment_perf[\"cr_active\"] = eda.safe_divide(segment_perf[\"orders_amt_total\"], segment_perf[\"active_click_total\"])\n",
    "segment_perf[\"cr_passive\"] = eda.safe_divide(segment_perf[\"orders_amt_total\"], segment_perf[\"passive_click_total\"])\n",
    "\n",
    "matrix = segment_perf[[\"ctr_active\", \"ctr_passive\", \"cr_active\", \"cr_passive\"]]\n",
    "matrix\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cef644cd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-12T18:43:05.620380Z",
     "iopub.status.busy": "2025-12-12T18:43:05.620110Z",
     "iopub.status.idle": "2025-12-12T18:43:06.282656Z",
     "shell.execute_reply": "2025-12-12T18:43:06.280874Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "ctr_mat = matrix[[\"ctr_active\", \"ctr_passive\"]]\n",
    "cr_mat = matrix[[\"cr_active\", \"cr_passive\"]]\n",
    "\n",
    "sns.heatmap(ctr_mat, annot=True, fmt=\".3f\", cmap=\"Blues\", ax=axes[0])\n",
    "axes[0].set_title(\"CTR active/passive по возрастам\")\n",
    "\n",
    "sns.heatmap(cr_mat, annot=True, fmt=\".3f\", cmap=\"Greens\", ax=axes[1])\n",
    "axes[1].set_title(\"CR click→order по возрастам\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b108afe9",
   "metadata": {},
   "source": [
    "## Интерпретация и идеи\n",
    "- Наблюдение: CTR_active ≈ одинаков для 15–29, 40–54 и других; CTR_passive чуть выше у 40–54 и other, молодые слабее.\n",
    "- Наблюдение: CR click→order высок и близок между сегментами; пассивные клики конвертируются сопоставимо с активными.\n",
    "- Почему так: пассивные офферы могут быть более релевантны старшим; молодые получают больше активных контактов и пассивные баннеры теряются на фоне «шумного» интерфейса.\n",
    "- Что изменить:\n",
    "  1) Тестировать более громкие или персонализированные пассивные форматы для 15–29 (категории ent/shopping).\n",
    "  2) Для 40–54 усилить активные коммуникации с чётким CTA и минимизировать частоту пассивных баннеров, которые уже работают на конверсию.\n",
    "  3) Добавить контроль насыщенности: ограничить показы при падении CTR в бинах частоты, особенно у 15–29.\n",
    "  4) Проверить категории: где сегменты реально различаются, и фокусировать креативы там.\n"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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   "file_extension": ".py",
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   "pygments_lexer": "ipython3",
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