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Ulta Skincare Product Review Data
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset features over 4,000 customer reviews of Dermalogica cleansing exfoliators, all sourced from Ulta.com. It was compiled on 27 March 2023 using Python libraries, specifically designed for Natural Language Processing (NLP) tasks. The dataset provides valuable insights into customer opinions and product performance, making it ideal for various analytical applications.
Columns
- Review_Title: The main heading or title given to the review by the customer.
- Review_Text: The complete content of the customer's review.
- Verified_Buyer: Indicates whether the reviewer has been confirmed as a buyer of the product (True or False). Approximately 30% of reviews are from verified buyers.
- Review_Date: The publication date of the review, relative to the data scraping date. Reviews span a period up to two years prior to the scrape date.
- Review_Location: The geographic location provided by the reviewer. Many locations are undisclosed, with a small percentage from Los Angeles.
- Review_Upvotes: The total number of times the review was positively rated by other users.
- Review_Downvotes: The total number of times the review received negative ratings from other users.
- Product: The specific Dermalogica cleansing exfoliator product that the review pertains to. Key products include "Daily Superfoliant" and "Daily Microfoliant", each accounting for approximately 36% of reviews.
- Brand: The brand of the product being reviewed, which is consistently Dermalogica.
- Scrape_Date: The exact date when the data was extracted from Ulta.com, which was 2023-03-27.
Distribution
The dataset contains over 4,000 individual reviews. Data was scraped on 27 March 2023. For the 'Verified_Buyer' column, there are 1,249 (30%) 'true' entries and 2,901 (70%) 'false' entries. Key product mentions are evenly split between 'Daily Superfoliant' and 'Daily Microfoliant', each at 36%. Review dates are categorised into "2 years ago" (22%), "1 year ago" (20%), and other periods (58%). Reviewer locations are largely "Undisclosed" (22%) or other (75%), with a small percentage (3%) from "Los Angeles". Specific numbers for rows or records beyond the total review count are not explicitly detailed, but metrics for upvotes and downvotes are available.
Usage
This dataset is particularly useful for:
- Sentiment Analysis: Determining the overall positive or negative sentiments associated with each Dermalogica product.
- Text Analysis: Extracting insights from review texts, such as common skincare concerns addressed by the products or issues they helped resolve or worsen.
- Inferential Statistics: Analysing statistically significant differences in average sentiment scores across different product reviews.
- Data Visualisation: Creating visual representations like bar plots or word clouds to highlight frequently used words or phrases in relation to specific products.
Coverage
The data encompasses customer reviews of Dermalogica cleansing exfoliators published on Ulta.com. Geographically, while many reviewer locations are undisclosed, some specific cities like Los Angeles are noted, and the dataset is broadly considered to have a global reach. The time range of the reviews extends back from the data scrape date of 27 March 2023, with reviews published up to two years prior. No specific demographic breakdown is provided, though the 'Verified_Buyer' flag offers a binary indication of purchase confirmation.
License
CC-BY
Who Can Use It
This dataset is beneficial for a range of professionals and organisations, including:
- Data Scientists and NLP Engineers: For developing and testing natural language processing models.
- Market Researchers: To understand customer feedback, identify market trends, and assess product performance within the skincare industry.
- Skincare Brands: For gaining insights into customer satisfaction, identifying product strengths and weaknesses, and informing product development strategies.
- Academics and Students: For research projects focused on consumer behaviour, text analytics, or machine learning applications in e-commerce.
Dataset Name Suggestions
- Dermalogica Ulta Cleanser Reviews
- Ulta Skincare Product Review Data
- NLP Dermalogica Exfoliator Reviews
- Dermalogica Reviews from Ulta.com
Attributes
Original Data Source: NLP: NLP: Ulta Skincare Reviews
QUALITY