The 3.5 Star Restaurant Challenge
Putting Freddie Wong’s theory on finding quality Chinese restaurants to the test with Categorized Theme Discovery.
Freddie Wong (aka FreddieW) is well known for his competitive gaming, filmmaking, podcasting, and as of recently, his theory on how to find authentic Chinese restaurants. We’re big fans of his content in our remotely distributed global office, so it was no surprise that this Tik Tok was the talk of our #random slack channel when it was published. According to FreddieW, the ideal Chinese restaurant isn’t the spot with a 5-star rating, but a 3.5-star rating. “People on Yelp are insufferable,” he says, commenting on people’s tendency to put down restaurants for poor service, even if the food is immaculate. According to him, 3.5 stars is the sweet spot between poor service and authentically delicious Chinese food.
As a proud New Yorker and Chinese food lover, I appreciated this advice for navigating the endless number of Chinese restaurants in the concrete jungle. Scrolling through Yelp and searching for the best ratings, or in this case, the most mediocre ratings, can give you a general idea of the quality of a restaurant. If you’re like me though, you want to know more than what a few star symbols can tell you. So we took an NYC Chinese Food Yelp Reviews dataset and ran it through our handy-dandy Category Theme Discovery narrative. The best part? It took all of about 5 minutes to analyze and understand the results of thousands of reviews and put Freddie’s theory to the test. 🤯
The 3.5-Star Theory in Action ✨
Using Categorized Theme Discovery, I wanted to isolate the 3.5-star restaurants to see if Freddie’s theory holds up, and compare them to a 5-star joint. You might remember our article “Top 5 Complaints Users Have About Spotify” a few blogs back. TLDR; we analyzed Spotify reviews using our Theme Discovery component to identify key issues users were facing when using the app. In this case, however, it’s more important to identify the themes that exist between each restaurant instead of among all of them collectively.
The city (New York, that is, where we consider NYC to be THE city) is notorious for its extreme price tag, which makes finding affordable restaurants with good food feel like hitting the lottery. 🤑According to Yelp reviewers, Golden Dragon Kitchen offers quality food that won’t break the bank, (Theme 2.) True to Freddie’s Tiktok though, poor service (Theme 5) and great food (Theme 1) seem to be a few of the top themes of this dataset! Despite the mediocre service, it seems that Golden Dragon Kitchen has good food, enough to boost its Yelp reviews to a solid 3.5.
Exceptions to the Rule
Freddie’s theory doesn’t seem to always hold up though. Golden Dragon Kitchenhas 5 stars and stellar reviews, combining good food with friendly and attentive service. This goes to show how much we can learn by analyzing qualitative data as opposed to relying on ratings that lack specificity.
Looking for ratings is a quick way to understand the quality of a restaurant, but as Freddie proved with his 3.5-star theory, looks can be deceiving 👀Analyzing consumer reviews can give us way more insight into how people really feel, and AI sentiment analysis tools can help streamline this process. Qualitative data gets a bad rep sometimes because of its subjectivity and the time it takes to analyze — who would want to read thousands of reviews every time they get hungry? Thankfully, Resultid is a flow designed to help us understand messy data better and faster, and not just when we’re restaurant researching either. Categorized Theme Discovery is the tool to use to find themes across multiple different groups with qualitative data, from conducting competitive analysis research to understanding professional candidates when recruiting. There are a million stories to tell with qualitative data — it’s just a matter of using the right tools to get us there. 🛠️
