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McDonald's Customer Experience Data
Reviews & Ratings
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides insights into customer experiences at McDonald's restaurants, focusing on negative Yelp reviews. It encompasses 1525 observations detailing ratings, reviews, and city locations, alongside classified sentiments. The primary purpose is to offer a sentiment analysis of low-rated McDonald's reviews, with contributors having categorised the reasons for dissatisfaction. These reasons include issues such as rude service, slow service, problems with orders, bad food, poor neighbourhood conditions, dirty locations, high cost, or missing items.
Columns
- _unit_id: A unique identifier for each unit.
- _golden: Indicates if the entry is a golden record.
- _unit_state: The state of the unit.
- _trusted_judgments: The number of trusted judgments for an entry.
- _last_judgment_at: The timestamp of the last judgment.
- policies_violated: Specifies if any policies were violated.
- policies_violated:confidence: The confidence score for policies violated.
- city: The city where the review originated.
- policies_violated_gold: Golden standard for policies violated.
- review: The full text of the customer review.
Distribution
The dataset comprises 1525 individual observations or records. While a specific file format is not detailed for this dataset, data files on the platform are typically provided in CSV format. The exact number of rows and columns is clear from the observation count and listed columns.
Usage
This dataset is ideal for:
- Sentiment analysis of customer feedback in the fast-food industry.
- Natural Language Processing (NLP) research and model training, particularly for text classification and sentiment prediction.
- Identifying common customer pain points and areas for operational improvement within restaurant chains.
- Marketing analysis to understand brand perception and customer satisfaction drivers.
- Academic studies on consumer reviews and public opinion.
Coverage
The dataset covers customer reviews from various random metro areas, including notable contributions from Las Vegas (27%) and Chicago (14%). The data appears to primarily originate from a single day, 21st February 2015, based on the review timestamps. It focuses on the experiences of customers who dined at McDonald's establishments.
License
CCO
Who Can Use It
- Data scientists and machine learning engineers for building and testing sentiment analysis models.
- Market researchers and brand managers seeking to analyse customer satisfaction and identify areas for brand improvement.
- Restaurant operators and business analysts interested in understanding operational shortcomings and customer grievances.
- Students and academics conducting research on consumer behaviour, text analytics, or the fast-food industry.
Dataset Name Suggestions
- McDonald's Yelp Review Sentiment Analysis
- Fast Food Negative Customer Reviews
- McDonald's Customer Experience Data
- Yelp Reviews: McDonald's Feedback Insights
Attributes
Original Data Source: McDonalds Yelp! Reviews
QUALITY