{
  "id": 313480,
  "title": "What is the significance of Sales Channel ID column in transactions_train.csv?",
  "url": "/competitions/h-and-m-personalized-fashion-recommendations/discussion/313480",
  "author_name": "",
  "post_date": "2022-03-17T10:54:06.680575600Z",
  "votes": 6,
  "comment_count": 2,
  "views": 0,
  "content": "<p>What is the significance of Sales Channel ID column in transactions_train.csv?</p>",
  "messages": [
    {
      "id": "1725703",
      "postDate": "03/17/2022 10:54:06",
      "content": "<p>What is the significance of Sales Channel ID column in transactions_train.csv?</p>",
      "rawMarkdown": "What is the significance of Sales Channel ID column in transactions_train.csv?",
      "votes": null
    },
    {
      "id": "1726083",
      "postDate": "03/17/2022 16:33:35",
      "content": "<p>Hi <a href=\"https://www.kaggle.com/aniruddhapa\" target=\"_blank\">@aniruddhapa</a>, this <a href=\"https://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/305952#1684481\" target=\"_blank\">thread</a> has the corresponding answer, saying<br><br>\n<code>sales channel id, 2 is online and 1 store.</code><br><br>\nHope this helps.</p>",
      "rawMarkdown": "Hi @aniruddhapa, this [thread](https://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/305952#1684481) has the corresponding answer, saying<br>\n`sales channel id, 2 is online and 1 store.`<br>\nHope this helps.",
      "votes": null
    },
    {
      "id": "1727283",
      "postDate": "03/17/2022 20:44:36",
      "content": "<p>I think, for example, we can use <code>'sales_channel_id'</code> to classify customers into online and offline users by counting online / offline transactions of each user. I created a notebook related to this point <a href=\"https://www.kaggle.com/negoto/h-m-framework-for-partitioned-validation\" target=\"_blank\">here</a>.<br>\nOr, if we divide transactions by <code>'sales_channel_id'</code> and count occurrences of each article, it will become clear that there are some differences of sales trend by distributive channels.</p>",
      "rawMarkdown": "I think, for example, we can use `'sales_channel_id'` to classify customers into online and offline users by counting online / offline transactions of each user. I created a notebook related to this point [here](https://www.kaggle.com/negoto/h-m-framework-for-partitioned-validation).\nOr, if we divide transactions by `'sales_channel_id'` and count occurrences of each article, it will become clear that there are some differences of sales trend by distributive channels.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1726083,
      "author_name": "abaojiang",
      "author_url": "",
      "post_date": "03/17/2022 16:33:35",
      "content": "<p>Hi <a href=\"https://www.kaggle.com/aniruddhapa\" target=\"_blank\">@aniruddhapa</a>, this <a href=\"https://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/305952#1684481\" target=\"_blank\">thread</a> has the corresponding answer, saying<br><br>\n<code>sales channel id, 2 is online and 1 store.</code><br><br>\nHope this helps.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1727283,
      "author_name": "negoto",
      "author_url": "",
      "post_date": "03/17/2022 20:44:36",
      "content": "<p>I think, for example, we can use <code>'sales_channel_id'</code> to classify customers into online and offline users by counting online / offline transactions of each user. I created a notebook related to this point <a href=\"https://www.kaggle.com/negoto/h-m-framework-for-partitioned-validation\" target=\"_blank\">here</a>.<br>\nOr, if we divide transactions by <code>'sales_channel_id'</code> and count occurrences of each article, it will become clear that there are some differences of sales trend by distributive channels.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1725703": "What is the significance of Sales Channel ID column in transactions_train.csv?",
    "1726083": "Hi @aniruddhapa, this [thread](https://www.kaggle.com/c/h-and-m-personalized-fashion-recommendations/discussion/305952#1684481) has the corresponding answer, saying<br>\n`sales channel id, 2 is online and 1 store.`<br>\nHope this helps.",
    "1727283": "I think, for example, we can use `'sales_channel_id'` to classify customers into online and offline users by counting online / offline transactions of each user. I created a notebook related to this point [here](https://www.kaggle.com/negoto/h-m-framework-for-partitioned-validation).\nOr, if we divide transactions by `'sales_channel_id'` and count occurrences of each article, it will become clear that there are some differences of sales trend by distributive channels."
  },
  "source": "meta"
}