Consumer satisfaction data helps people understand how users feel about a product or service based on real experiences. One common area where this data is widely used is mobile food delivery apps.
Figure 1: Dataset containing food delivery app reviews and ratings.
Source: Kaggle
Food delivery apps such as Uber Eats, DoorDash, and SkipTheDishes collect large amounts of data through user ratings and written reviews. This data allows consumers and researchers to compare apps and identify patterns in customer satisfaction. The data not only helps us review the apps used to order/deliver food but also provides insights into the quality of the restaurants themselves.
A new popular app called Beli is sweeping the nation as a new and trendier version of Yelp. Beli has features that make it feel more like social media and less like reviewing. This means people can hear accurate reviews and data from their real life friends, helping them to make trustworthy food choices.
Figure 2: New trending food review app.
Source: Beli
The most common types of consumer satisfaction data include star ratings, written reviews, and review trends over time. Ratings are usually displayed on a scale from one to five stars.
Written reviews provide more detailed feedback about delivery time, customer service, pricing, and app usability. When many reviews are examined together, they can reveal consistent strengths or problems within an app.
By comparing ratings and reviews across multiple platforms, consumers can identify which food delivery apps are the most reliable. A sudden drop in ratings may suggest issues caused by an app update, pricing changes, or delivery problems.
Websites such as Trustpilot focus on customer service experiences, including refunds and complaint resolution. Trustpilot often uses raw review data, similar to datasets found on Kaggle, to generate summaries of overall customer satisfaction.
Figure 3: Trustpilot overview showing customer satisfaction scores.
Source: Trustpilot
Reviewing written complaints allows consumers to identify common issues such as late deliveries, missing items, or poor customer support.
Figure 4: Company that helps restaurants collect feedback.
Source: SuperOrder
Companies such as Super Order also collect feedback data for restaurants, helping businesses better understand customer experiences and improve service quality.
When used together, review datasets and consumer feedback websites allow users to make informed decisions based on real customer experiences rather than advertisements.
Kaggle – Food Delivery App Reviews Dataset: https://www.kaggle.com/datasets/skamlo/food-delivery-apps-reviews
Trustpilot – Consumer Reviews and Ratings: https://www.trustpilot.com
SuperOrder – Restaurant Feedback and Survey Tools: https://www.superorder.com