Embedded Files
~~The Raw Data~~
Reviews - Scraped from Yelp and Google!
Web Scraped (compiled reviews into a sheet) using: https://console.apify.com and https://app.scrapehero.com
Python Machine Learning Model used to analyze reviews
LLM (Large Language Models) - to find food related words / negative connotation for bad reviews!
- with Julius AI
Overall Findings!
From Yelp Data! ^^
From Google Reviews Data! ^^
So, retail/food really is the issue!
Conclusion Made from the following Statistics:
47.2% of Reviews are characterized by Retail/Food (yelp - avg: 2.8 stars)
There was a spike in negative reviews based on food/retail this year (yelp)
31% of reviews are 1 Star - the worst possible rating (Google Reviews)
Almost 30% of reviews mention amenities (Google Reviews)
↓ ↓ ↓ CHECK OUT THE RETAIL AND FOOD PAGES BELOW TO SEE THE SOLUTIONS! ↓ ↓ ↓
Google Sites
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