# Dev-o-thon 2023 — Data

来源：https://www.kaggle.com/competitions/dev-o-thon-23/data

采集时间：2026-10-19T15:23:42Z

**Title:** Lead Scoring Algorithm Development Dataset

**Test Description** : The "EST.csv" is a csv file specifically designed to test your model . The Answer should be in csv format containing ID,Status Columns.

**Train Description:**
This dataset contains information about leads that a company has acquired. The purpose of this dataset is to develop a lead scoring algorithm, which will predict the likelihood of a lead becoming a customer based on their demographic and behavioral data.

The dataset is provided as a CSV file named 'Rain.csv'. It contains **28 columns** and more than **100,000 rows** of data. Each row represents a lead, and each column contains a different attribute of that lead. The columns are as follows:

**Email:** The email address of the lead
**Leads_Source**: The source through which the lead was acquired
**Work email**: The work email address of the sales person
**Job title**: The job title of the sales person
**Sales owner:** The name of the branch owner assigned to the lead
**Owner Email**: The email address of the salesperson assigned to the lead
**Territory**: The geographical territory of the lead
**Team**: The team assigned to the lead
**Product_interested**: The product(s) that the lead has shown interest in
**Lead_Zipcode**: The zipcode of the lead's location
**Lead_State**: The state of the lead's location
**Lead_city**: The city of the lead's location
**url-campaign**: The URL campaign through which the lead was acquired
**page-url**: The webpage from which the lead was acquired
**Lead_hour**: The time of day when the lead was acquired
**Fulfillment Status:** The status of the lead's order fulfillment
**Fulfilled at**: The date and time when the lead's order was fulfilled
**Accepts Marketing**: Whether the lead has given permission to receive marketing communications
**Shipping**: The shipping method used for the lead's order
**Total**: The total value of the lead's order
**Discount Amount:** The amount of discount applied to the lead's order
****Payment Method:**** The payment method used for the lead's order
**Refunded Amount**: The amount refunded for the lead's order
**Vendor**: The vendor associated with the lead's order
**Outstanding Balance**: The outstanding balance on the lead's order
**Source**: The original source of the lead
**Status**: The Target Value of The Lead
**ID**: The unique identifier for the lead

The target variable is explicitly defined in the dataset and it is implied that the goal is to predict which leads are most likely to become customers. The algorithm will be evaluated on the basis of its recall and precision metrics.

This dataset is suitable for data scientists and machine learning engineers who are interested in developing lead scoring algorithms. It can also be used to study customer behavior and to identify trends in lead acquisition and conversion.