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Brazil Online Retail Pricing and Reviews
Retail & Consumer Behavior
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About
Explores data covering over 2,200 unique clothing items extracted from the catalogue of Brazil's largest online shopping and selling platform. This resource was collected via web scraping on 15 September 2023. The collection focuses on key metrics essential for market research, including original item prices, applied discounts, final purchase prices, customer review ratings, and categorized sales volumes. Both a clean version, ready for advanced data analysis and machine learning applications, and a raw version, ideal for training in data cleaning techniques, are provided.
Columns
- ID: A unique identifier for each observation.
- Título: The product listing title displayed to shoppers.
- Preco_original: The item's initial stated price.
- Desconto_percentual: The proportionate reduction applied to the price.
- Preco_com_desconto: The ultimate price the item is sold for after the discount.
- n_vendidos_categoria: A category field indicating the volume of items sold, grouped according to ranges used by the website (e.g., 0–5000, 5000–10000).
- Marca: The brand name associated with the clothing item.
- Material: The primary material composition of the apparel.
- Gênero: Denotes the "Gender" target for the item (e.g., Feminino, Masculino).
- Temporada: Indicates the season the piece relates to, such as Autumn/Winter or Primavera/Verão (Spring/Summer).
- Nota: The numerical average customer review score.
- N_Avaliações: The total count of customer reviews submitted for the product.
- Review1, Review2, Review3: The first, second, and third customer reviews featured on the product page.
Distribution
The clean version of the data contains 2,206 observations structured across 14 columns. It is typically supplied in a CSV file format. Many key metric columns, such as pricing, brand, and discount data, are fully populated with 100% valid entries. However, detailed information like customer review ratings (
Nota) has a notable percentage of missing values (approximately 29%). The overall usability score for the data is rated highly at 10.00. Updates to this data product are anticipated on an annual basis.Usage
This data is excellent for practitioners focused on data analysis and building machine learning models. Potential applications include:
- Forecasting product sales based on attributes like brand, material, and seasonal categorization.
- Performing market basket analysis and competitive pricing research within the Brazilian e-commerce sector.
- Training models to predict customer satisfaction using average ratings and review sentiment analysis.
- Studying the impact of discounts (
Desconto_percentual) on final price and sales volume. - Practicing data cleaning and wrangling skills utilising the raw version of the extracted information.
Coverage
The data focuses geographically on Brazil, capturing listings from the country’s largest online sales platform. The collection period is singular, based on the extraction date of 15 September 2023. The scope covers various apparel items, categorized by gender and seasonal relevance.
License
CC0: Public Domain
Who Can Use It
- E-commerce Analysts: To benchmark pricing strategies and track sales performance in the Brazilian market.
- Data Scientists: For training recommendation engines, pricing elasticity models, or sentiment analysis models.
- Retail Researchers: To understand local trends in material usage, seasonality, and brand preference.
- Students/Trainees: Utilising the raw data version to develop and refine skills in data preparation.
Dataset Name Suggestions
- Brazilian E-commerce Apparel Data 2023
- Brazil Online Retail Pricing and Reviews
- Clothing Sales Metrics from Brazil’s Top Platform
- September 2023 Brazilian Fashion E-commerce Snapshot
Attributes
Original Data Source: Brazil Online Retail Pricing and Reviews
QUALITY