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eCommerce behavior data from multi category store
Aesthetics
|...
许可协议: CC-BY-SA 4.0

Overview

About

This file contaisn behavior data for 7 months (from October 2019 to April 2020) from a large multi-category online store.

Each row in the file represents an event. All events are related to products and users. Each event is like many-to-many relation between products and users.

Note: if this dataset is too large for you, you can try smaller dataset from cosmetics store.

There are different types of events. See below.

Semantics (or how to read it):

> User user_id during session user_session added to shopping cart (property event_type is equal cart) product product_id of brand brand of category category_code (category_code) with price price at event_time

More datasets

Due to Kaggle's limit to max 20Gb of files per dataset, I can' upload more data to this dataset. Here you can find additional archives (Dec 2019 - Apr 2020).

File structure

event_time

Time when event happened at (in UTC).

event_type

Events can be:

  • view - a user viewed a product
  • cart - a user added a product to shopping cart
  • remove_from_cart - a user removed a product from shopping cart
  • purchase - a user purchased a product

Typical funnel: view => cart => purchase.

product_id

ID of a product

category_id

Product's category ID

category_code

Product's category taxonomy (code name) if it was possible to make it. Usually present for meaningful categories and skipped for different kinds of accessories.

brand

Downcased string of brand name. Can be missed.

price

Float price of a product. Present.

user_id

Permanent user ID.

user_session

Temporary user's session ID. Same for each user's session. Is changed every time user come back to online store from a long pause.

Multiple purchases per session

A session can have multiple purchase events. It's ok, because it's a single order.

Many thanks

Thanks to REES46 Marketing Platform for this dataset.

Using datasets in your works, books, education materials

You can use this dataset for free. Just mention the source of it: link to this page and link to REES46 Marketing Platform.

数据概要
数据格式
image,
数据量
2
文件大小
549.16MB
发布方
Michael Kechinov
| 数据量 2 | 大小 549.16MB
eCommerce behavior data from multi category store
Aesthetics
许可协议: CC-BY-SA 4.0

Overview

About

This file contaisn behavior data for 7 months (from October 2019 to April 2020) from a large multi-category online store.

Each row in the file represents an event. All events are related to products and users. Each event is like many-to-many relation between products and users.

Note: if this dataset is too large for you, you can try smaller dataset from cosmetics store.

There are different types of events. See below.

Semantics (or how to read it):

> User user_id during session user_session added to shopping cart (property event_type is equal cart) product product_id of brand brand of category category_code (category_code) with price price at event_time

More datasets

Due to Kaggle's limit to max 20Gb of files per dataset, I can' upload more data to this dataset. Here you can find additional archives (Dec 2019 - Apr 2020).

File structure

event_time

Time when event happened at (in UTC).

event_type

Events can be:

  • view - a user viewed a product
  • cart - a user added a product to shopping cart
  • remove_from_cart - a user removed a product from shopping cart
  • purchase - a user purchased a product

Typical funnel: view => cart => purchase.

product_id

ID of a product

category_id

Product's category ID

category_code

Product's category taxonomy (code name) if it was possible to make it. Usually present for meaningful categories and skipped for different kinds of accessories.

brand

Downcased string of brand name. Can be missed.

price

Float price of a product. Present.

user_id

Permanent user ID.

user_session

Temporary user's session ID. Same for each user's session. Is changed every time user come back to online store from a long pause.

Multiple purchases per session

A session can have multiple purchase events. It's ok, because it's a single order.

Many thanks

Thanks to REES46 Marketing Platform for this dataset.

Using datasets in your works, books, education materials

You can use this dataset for free. Just mention the source of it: link to this page and link to REES46 Marketing Platform.

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