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Web Store Transaction Records
E-commerce & Online Transactions
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About
This dataset provides actual online retail sales data from an unnamed business between 2017 and 2019. Its primary purpose is to offer insights into online business performance. The data originates from a small business that experienced a significant reduction in employees, from 25 to 5, due to the economic downturn associated with the coronavirus. This dataset is provided to help the business through informative analyses and visualisations, aiding in its recovery and strategic planning. It includes key metrics such as online sales, profit, units sold, shipping details, and returns.
Columns
The dataset comprises six distinct columns:
- Product Type: Describes the category of items sold, such as 'Basket', 'Art & Sculpture', or 'Other'. There are 18 unique product types within the 1767 valid records.
- Net Quantity: Represents the exact quantity of products sold. This column contains 1775 valid records with a mean of 3.71, standard deviation of 6.24, ranging from a minimum of -1 to a maximum of 96.
- Gross Sales: Indicates the total sales value before any deductions. This column has 1775 valid records, with a mean of 200, standard deviation of 465, ranging from 0 to 14,935.
- Discounts: Shows the discount applied to sales. It contains 1775 valid records, with a mean of -6.32, standard deviation of 20.9, and values from -594 to 0.
- Returns: Records the value of returned items. This column includes 1775 valid records, with a mean of -5.39, standard deviation of 46.6, and values ranging from -1609 to 0.
- Total Net Sales: Represents the final sales value after all adjustments. It has 1775 valid records, a mean of 188, standard deviation of 414, and values from -106 to 12,732.
Distribution
The dataset is provided as a CSV file, specifically
business.retailsales.csv, with a file size of 47.27 kB. It is structured with 6 columns. The data contains a varying number of records, with 'Product Type' having 1767 valid entries and other numeric columns ('Net Quantity', 'Gross Sales', 'Discounts', 'Returns', 'Total Net Sales') each containing 1775 valid records.Usage
This dataset is ideal for developing informative kernels and visualisations to support a small business. Specific use cases include:
- Analysing online sales trends and patterns between 2017 and 2019.
- Evaluating profitability and identifying key drivers of revenue.
- Understanding the impact of discounts and returns on overall sales.
- Identifying top-selling product types and low-performing items.
- Supporting strategic decisions to help a business recover from economic downturns.
Coverage
The dataset covers online retail sales activity over a three-year period, from 2017 to 2019. The sales data pertains to an unnamed online business. No specific geographic or demographic scope is detailed within the provided information.
License
CC0: Public Domain
Who Can Use It
This dataset is valuable for:
- Data Analysts and Scientists: For performing sales trend analysis, predicting future performance, and creating predictive models.
- Business Strategists: To assess business health, identify areas for operational improvement, and develop recovery plans.
- Researchers: For studying the impact of economic conditions on small businesses and consumer behaviour in online retail.
- Students and Educators: As a practical example for data cleaning, analysis, and visualisation projects.
Dataset Name Suggestions
- Online Retail Performance 2017-2019
- E-commerce Sales Analysis Dataset
- Small Business Sales Data (2017-2019)
- Retail Sales Activity Log
- Web Store Transaction Records
Attributes
Original Data Source: Web Store Transaction Records
QUALITY