We started this Scenario by polling a simple question:
If you were in New York City, and only two hotels were left on Booking.com and/or Airbnb. They are the same quality of room, in the same area, and at the same price. The only difference is that one of the listings has a Wikipedia article associated with it. Which one would you choose?
In a whopping 98% of our sampling, people choose the property with the Wikipedia article associated with it.
Now imagine, if you could bring even more context to your property, as either (a) a business to make your property stand out, or (b) as the customer who wants to filter out options that are unique.
Now what if you could pick a Booking.com hotel that not only has a Wikipedia article, but also has your favorite brand of soft drinks, alcohol, tv channels, or other amenities? That’s what we’re up to here at Stops.
In this Scenario, we aggregated over 300 Booking.com listings throughout the country of Israel. The results are truly amazing. Whenever a user subscribes to Booking and comes across a Booking.com hotel listing on Stops, they also see other contextual information around that location, like the closest Wikipedia article, Yelp restaurant, fact, WiFi and more. This provides unique context to the property and providing the customer with a wide range of nearby options (not just landmarks!).
Imagine! With the power of Stops, the next time you search for a hotel on a site like Booking.com you will be being able to filter hotels through an even broader range of personal filters (for example, Netflix, Disney, Coca-Cola, Mars, Mountain Dew, New York Times, Advil, etc).
In summary, Stops technology has the power to fuel websites like Booking or Airbnb with contextual data that can help their customers filter and make better choices, according to their tastes.