FunnelScope recently did a study on a large sample of reviews for hotels across several cities. Using our proprietary Natural Language Processing engine, we wanted to figure out what percent of reviews referenced each critical attribute. In other words, create a measurement of what reviewers cared about most often when it came to determining whether they had a good or bad stay at a hotel.
The results are as follows (results are the percent of reviews that referenced an attribute):
Location 65%
Service 58%
Room Quality 45%
Cleanliness 32%
Near Entertainment 29%
Room Size 23%
Comfort of Bed 19%
Near Tourist Attractions 17%
Food Quality 16%
Coziness 14%
Room Amenities 14%
Bathroom Quality 12%
Modern 12%
Luxurious 11%
Parking Expense 10%
Business Oriented 8%
Views 7%
Parking Convenience 7%
Traditional 7%
Family Friendly 6%
Historical 5%
Gym Quality 4%
Bathroom With Bath 2%
From our perspective, the more data we can provide that measure these attributes so users can match to their preferences, the better experience users will have. FunnelScope will run this analysis across other local / travel search verticals and share those results as well.
