Dataset: E-commerce Multichannel Direct Messaging 2021-2023

About this Dataset

E-commerce Multichannel Direct Messaging 2021-2023

About

This dataset contains multi-channel messages of medium sized online store for 2 years.

Channels: email, web push, mobile push, SMS.

Campaign types: bulk, triggers, transactional.

Notice: this dataset contains messages-demo.csv file limited to 10M messages. The full file with 721M messages is available here: messages.csv (21.5Gb).

Data collected by REES46 CDP project.

Files description

Here is a brief description of files. You can find the detailed description of every property in this notebook.

holidays.csv

Bulk campaigns usually set before holidays and sale outs. This file contains not full list of Russian holidays and commerce activities so you can see how bulk campaigns are related to these dates.

campaigns.csv

All messages are related to some kind of campaigns:

Bulk campaigns are sent for sale outs and before holidays to stimulate sales and bring back customers.
Trigger messages (like abandoned cart) are sent automatically based on user's behavior. More users visited website/app – more trigger messages are sent.
Transactional messages are used for some kind of information delivery process: bonuses added, order delivery status changed, etc.

Keep in mind: campaign_id is unique only for the specific campaign_type. Two campaigns with different campaign_type can have the same campaign_id. So the unique campaign identifier is campaign_type + campaign_id.

Additional properties are added to every campaign to describe its meaning (topic) or subject parameters (emoji, call to action, etc).

messages.csv or messages-demo.csv

Messages table contains a list of all messages sent with its statuses and meta info:

Campaign
Channel
Type
Opened (when)
Clicked (when)
Purchase
Etc. See attached dataset for detailed info of every property

client_first_purchase_date.csv

The file has 2 columns:

Client ID
Date of the first purchase ever

More datasets

Checkout another datasets:

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.

Tables

Campaigns

@kaggle.mkechinov_direct_messaging.campaigns

72.2 KB
1907 rows
19 columns


CREATE TABLE campaigns (
  "id" BIGINT,
  "campaign_type" VARCHAR,
  "channel" VARCHAR,
  "topic" VARCHAR,
  "started_at" TIMESTAMP,
  "finished_at" TIMESTAMP,
  "total_count" DOUBLE,
  "ab_test" VARCHAR,
  "warmup_mode" VARCHAR,
  "hour_limit" DOUBLE,
  "subject_length" DOUBLE,
  "subject_with_personalization" VARCHAR,
  "subject_with_deadline" VARCHAR,
  "subject_with_emoji" VARCHAR,
  "subject_with_bonuses" VARCHAR,
  "subject_with_discount" VARCHAR,
  "subject_with_saleout" VARCHAR,
  "is_test" VARCHAR,
  "position" DOUBLE
);

Client First Purchase Date

@kaggle.mkechinov_direct_messaging.client_first_purchase_date

12.89 MB
1854736 rows
2 columns


CREATE TABLE client_first_purchase_date (
  "client_id" BIGINT,
  "first_purchase_date" TIMESTAMP
);

Holidays

@kaggle.mkechinov_direct_messaging.holidays

2.81 KB
48 rows
2 columns


CREATE TABLE holidays (
  "date" TIMESTAMP,
  "holiday" VARCHAR
);

Messages Demo

@kaggle.mkechinov_direct_messaging.messages_demo

528.61 MB
10000000 rows
32 columns


CREATE TABLE messages_demo (
  "id" BIGINT,
  "message_id" VARCHAR,
  "campaign_id" BIGINT,
  "message_type" VARCHAR,
  "client_id" BIGINT,
  "channel" VARCHAR,
  "category" VARCHAR,
  "platform" VARCHAR,
  "email_provider" VARCHAR,
  "stream" VARCHAR,
  "date" TIMESTAMP,
  "sent_at" TIMESTAMP,
  "is_opened" VARCHAR,
  "opened_first_time_at" TIMESTAMP,
  "opened_last_time_at" TIMESTAMP,
  "is_clicked" VARCHAR,
  "clicked_first_time_at" TIMESTAMP,
  "clicked_last_time_at" TIMESTAMP,
  "is_unsubscribed" VARCHAR,
  "unsubscribed_at" TIMESTAMP,
  "is_hard_bounced" VARCHAR,
  "hard_bounced_at" TIMESTAMP,
  "is_soft_bounced" VARCHAR,
  "soft_bounced_at" TIMESTAMP,
  "is_complained" VARCHAR,
  "complained_at" TIMESTAMP,
  "is_blocked" VARCHAR,
  "blocked_at" TIMESTAMP,
  "is_purchased" VARCHAR,
  "purchased_at" TIMESTAMP,
  "created_at" VARCHAR,
  "updated_at" VARCHAR
);