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E-commerce Annual Sales Report
E-commerce & Online Transactions
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About
This dataset provides a detailed collection of sales transaction data, designed to uncover profitable insights and facilitate strategic growth analysis. It has been meticulously processed, with its original French language content translated into English, and includes no null values or duplicates, ensuring high data quality. The dataset has undergone extensive EDA (Exploratory Data Analysis) and feature engineering, including the extraction of sales performance metrics like annual product purchase trends and the segmentation of address information into city-level data. It is ideal for businesses looking to understand their sales patterns and optimise strategies.
Columns
- Order Date (date): Represents the date and time of each order, spanning from 1st January 2019 to 1st January 2020.
- Order ID (id): A unique identifier for each sales transaction, ranging from approximately 141k to 320k.
- Product (item): Describes the specific product purchased in the transaction. Key items include USB-C Charging Cable and Lightning Charging Cable.
- Product_ean (lean): The European Article Number (EAN) or barcode for the product.
- catégorie (which type): The category of the product, with prominent categories being 'Sports' and 'Vêtements' (Clothing).
- Purchase Address (address): The full postal address where the purchase was delivered, with city information extracted.
- Quantity Ordered (count): The number of units of a specific product ordered in a transaction, typically ranging from 1 to 9.
- Price Each (price): The unit price of the product at the time of purchase.
- Cost price (actual): The actual cost of each product.
- turnover (profit): The calculated profit or turnover generated from each transaction.
Distribution
The dataset is provided as a CSV file named
sales_data.csv, with a size of 25.96 MB. It contains 10 of 11 columns and holds approximately 186,000 valid records. The data primarily covers the calendar year 2019, from 1st January 2019 to 1st January 2020. Specific numbers for exact rows are available per date range for Order Date and per value range for other numerical columns.Usage
This dataset is suited for a variety of analytical applications, including:
- Sales Trend Analysis: Identifying periods of increased or decreased sales.
- Product Performance Evaluation: Understanding which products are most popular or profitable.
- Geographic Sales Analysis: Pinpointing high-performing regions or cities.
- Customer Behaviour Insights: Analysing purchase patterns and popular product combinations.
- Pricing Strategy Optimisation: Comparing unit prices, costs, and profits to refine pricing.
- Inventory Management: Forecasting demand based on historical sales.
Coverage
The dataset primarily covers sales data for the year 2019, from 1st January 2019 to 1st January 2020. While specific demographic details are not included, the
Purchase Address column provides geographic scope primarily within the United States, with the most common address being in San Francisco, CA. The original data's language was French, which has been converted to English.License
CC0: Public Domain
Who Can Use It
This dataset is ideal for:
- Data Analysts and Scientists: For performing exploratory data analysis, feature engineering, and building predictive models.
- Business Strategists: To gain insights into sales performance and market trends.
- Retail Managers: For optimising product offerings, pricing, and inventory.
- Academic Researchers: For studies on retail economics, consumer behaviour, and data analysis techniques.
- Students: As a practical dataset for learning data manipulation, analysis, and visualisation.
Dataset Name Suggestions
- Global Sales Transactions 2019
- Retail Sales Data Insights
- E-commerce Annual Sales Report
- Optimised Sales Performance
- Strategic Business Sales Analytics
Attributes
Original Data Source: E-commerce Annual Sales Report
QUALITY