Name: Wholesale Customers Data
Creator: Kaggle
License: https://www.apache.org/licenses/

About this Dataset

Wholesale Customers Data

Description:
Dive into the world of wholesale customer data and uncover insights into purchasing behavior across different channels and regions. This dataset offers a comprehensive view of annual spending on various product categories, providing valuable information for market segmentation and customer classification.

Features:

Region: Categorical feature indicating the region of purchase, with options including Lisbon, Oporto, or Other.
Fresh: Continuous feature representing annual spending (in monetary units) on fresh products.
Milk: Continuous feature representing annual spending (in monetary units) on milk products.
Grocery: Continuous feature representing annual spending (in monetary units) on grocery products.
Frozen: Continuous feature representing annual spending (in monetary units) on frozen products.
Detergents_Paper: Continuous feature representing annual spending (in monetary units) on detergents and paper products.
Delicassen: Continuous feature representing annual spending (in monetary units) on delicatessen products.
Target Feature: Channel - Categorical feature indicating the type of channel, either Horeca (Hotel/Restaurant/Cafe) or Retail channel.

How the data can be used:

Market Segmentation: Analyze spending patterns to segment customers based on their purchasing behavior, helping businesses tailor their marketing strategies accordingly.
Channel Classification: Develop machine learning models to classify customers into Hotel/Restaurant/Cafe (HoReCa) or Retail channels, enabling businesses to optimize their supply chain and distribution strategies.
Predictive Analytics: Utilize the dataset to build predictive models that forecast future spending trends, aiding businesses in inventory management and demand forecasting.
Customer Insights: Gain insights into the preferences and buying habits of wholesale customers, allowing businesses to identify growth opportunities and improve customer satisfaction.

Tables

Wholesale Customers Data

@kaggle.saurabhbadole_wholesale_customers_data.wholesale_customers_data

19.94 kB
440 rows
8 columns

CREATE TABLE wholesale_customers_data (
  "channel" BIGINT,
  "region" BIGINT,
  "fresh" BIGINT,
  "milk" BIGINT,
  "grocery" BIGINT,
  "frozen" BIGINT,
  "detergents_paper" BIGINT,
  "delicassen" BIGINT
);