In 2025, it was estimated about 95 percent of people in Germany had heard of Black Friday, while around 48 percent had purchased discounted products. This statistic shows the number of people in Germany who had heard of and used Black Friday.

Roughly ************* U.S. consumers surveyed in a recent study said they might go shop in-store for the Black Friday sales in 2024. This made it the most popular response. About the same percent of respondents said that they will definitely not do their Black Friday sales shopping in store.

In 2025, approximately ***** million people in the United States planned to shop on Black Friday. According to the source, *** million U.S. consumers will potentially shop during the Thanksgiving weekend, which marks the start of the holiday season.

Nationally representative survey of UK adults (18+) on planned 2025 Black Friday/Cyber Monday participation and spend, with breakdowns by generation, region, and purchase categories.

Comprehensive dataset tracking U.S. online Black Friday sales from 2020-2024 with projections through 2026, including year-over-year growth rates, mobile commerce share, BNPL transaction volumes, and compound annual growth rate analysis. Data sourced from Adobe Analytics, National Retail Federation, and industry research.

The goal of this dataset is to perform a data analysis project to investigate customer purchase behaviour during Black Friday at Walmart, specifically focusing on understanding if there are differences in spending habits between male and female customers. The analysis aims to provide insights to assist Walmart's management team in making informed business decisions.

Comprehensive dataset tracking mobile device share of Black Friday ecommerce sales from 2020 to 2024, including conversion rates, traffic percentages, year-over-year growth, and demographic breakdowns by generation. Data sourced from Adobe Analytics, Salesforce, and Digital Commerce 360.

Dataset Description

The dataset contains sales transactions captured at various retail stores across the United States during the Black Friday shopping event. It includes a comprehensive set of features that provide insights into customer demographics, product categories, and sales patterns. The dataset is designed to help retailers and e-commerce businesses optimize their sales strategies and maximize profits during this critical shopping period.

Key Features

1. User Information: Includes user demographics such as age, gender, marital status, and occupation.
2. Product Information: Covers product categories, subcategories, and specific product details.
3. Purchase Information: Contains the amount spent by each user for each purchase, in U.S. dollars.
4. Geographical Information: Includes city categories and the number of years the buyer has lived in their city.

Dataset Size

The dataset consists of approximately 550,000 records, providing a robust and representative sample of Black Friday sales data.

Purpose

The primary goal of this dataset is to help retailers and e-commerce businesses predict sales and optimize their pricing strategies to maximize profits during the Black Friday shopping event. This dataset can be used to develop machine learning models that can accurately forecast sales and identify trends in customer behavior.

Potential Use Cases

• Sales Forecasting: Use machine learning algorithms to predict sales based on historical data and optimize pricing strategies.
• Customer Segmentation: Identify and analyze customer demographics and purchasing patterns to tailor marketing campaigns and promotions.
• Product Recommendations: Develop personalized product recommendations based on customer preferences and purchase history.
• Store Optimization: Analyze sales data to optimize store layouts, product placement, and inventory management.

Comprehensive dataset of Black Friday 2024 spending patterns including average spend per shopper ($104), channel-specific spending (online $124, in-store $82), generational spending differences, payment method analysis, and five-year historical trends from 2020-2024 covering 152 million U.S. shoppers.

In late 2025, about *** in ten consumers in the United States said they liked deals with discounts on everything (clearly displayed in percentages) the most when shopping during Black Friday, Cyber Monday, or Singles' Day. About ******* of those who intended to shop during these events liked deals that offer cash back or gift cards.

Historical Black Friday revenue data showing 11-year trends in U.S. online and retail sales with year-over-year growth analysis and market insights.

According to a survey carried out in October 2025, Walmart was the top Black Friday shopping destination of choice for U.S. consumers. ***** out of 10 respondents stated that they planned to shop in-person in Target stores for Black Friday in 2025.

The Black Friday Sales dataset is a comprehensive collection of sales transaction data from a major retail store during a Black Friday event. This dataset includes over 550,000 observations and 12 key variables, offering valuable insights into customer purchasing behavior during one of the biggest shopping days of the year.

-> Key Features: - User ID: Unique ID for each customer. - Product ID: Unique ID for each product. - Gender: Gender of the customer, either male or female. - Age: The age group of the customer, represented in categories (e.g., 18-25, 26-35, etc.). - Occupation: Occupation category code of the customer. - City_Category: The category of the city where the customer resides, classified as A, B, or C. - Stay_In_Current_City_Years: Number of years the customer has lived in the current city. - Marital_Status: Indicates whether the customer is married (1) or not (0). - Product_Category 1, 2, 3: Product categories associated with the purchased item. - Purchase: The amount spent by the customer on the product.

This dataset can be utilized for analyzing patterns in consumer behavior, demographic-based purchasing tendencies, and predicting future sales trends. It's widely used in data science projects for regression, classification, and recommendation systems, making it ideal for feature engineering, model building, and data visualization.

Comprehensive dataset covering Black Friday retailer participation rates, consumer shopping behavior, sales volumes, and global trends across retail categories for 2020-2024.

Comprehensive dataset tracking Black Friday online order volumes, revenue, mobile vs desktop sales share, product category performance, and year-over-year growth metrics from 2020-2024, compiled from Adobe Analytics, Salesforce Commerce Cloud, and National Retail Federation sources covering over 1 trillion retail site visits.

Over 90 percent of shoppers in the United States planned to buy during Black Friday and Cyber Monday in 2025. In the United Kingdom, 87 percent of consumers intended to buy during the mega sales events in 2025.

Comprehensive dataset tracking Black Friday online sales percentages, growth rates, and market trends from 2019 to 2024, including mobile commerce adoption and payment method statistics.

Online media plays a crucial role in the visibility of mega-sale events. Online shopping websites are the most popular channel for surveyed shoppers to notice Black Friday and Cyber Monday in the United States in 2025. ** percent of survey participants are most likely to notice Black Friday and Cyber Monday on social media. Retailer websites and apps are most likely to be noticed by ** percent of Black Friday and Cyber Monday shoppers in the United States in 2025.

In 2025, ***percent of Italian consumers willing to shop during Black Friday stated they would buy fashion items. The most popular category of products was consumer electronics and household appliances, preferred by ** percent of the surveyed consumers.

Social media was the channel most likely to create awareness of Black Friday and Cyber Monday mega sales for Gen Z and millennials in 2025. In contrast, Gen X and baby boomers were much more like to notice mega sales events from TV compared to the younger cohorts.