"...so while my own personal recommendations may have served as sort of an 'organic proof of concept' - the method wasn't scalable. That's why we built an app to do this automatically."
- Josh Sapienza
Having worked in restaurants for over three decades, I'm often asked to recommend "another great bar" or asked "What’s your favorite restaurant in... any number of cities or "Where would be a good place to take my husband/wife for our anniversary", etc...
But I've always said that asking me to recommend a great meal or "The Best restaurant" in a particular city, is a lot like telling me you’re going out for ice cream and asking me to choose the best flavor. What if I love Pistacchio and you're more of a Mint Chocolate Chip girl?
In other words, "The Best" is subjective.
So, in the interest of wanting everyone to enjoy themselves as much as possible, I've always tried to learn as much as I can about a person's likes and dislikes before making a recommendation.
Whether it's a guest, neighbor, facebook friend, Lyft driver or family friend...I ask questions like:
“Where have you eaten before that you really liked and what did you like most about it?”
“Where have you been that you'd never go back... and what made it so disappointing?”
“What are some of your other favorite places... and why?”
“Do you have any food allergies, dietary restrictions or have any foods that you simply don’t like or wouldn’t even consider trying?”
“What do you consider good service?"
The list goes on and on... and, while it may sound tedious, the more information I gather about someone - the more reliable (and appreciated) my recommendations tend to be.
So, while my own personal recommendations may have served as a sort of an "organic proof of concept" - the method wasn't scalable.
So we built an app that does all this automatically with predictive analytics...which is really just a fancy way of saying "an elaborate computer program finds commonality among people with similar tastes based on their answers to fun personal taste quizzes and their PRIVATE ratings of the restaurants they've visited - then, another equation predicts their compatibility with restaurants & bars anywhere".
We're not saying our method is better than the consensus calculated by Google, TripAdvisor or Yelp... or the one-size-fits-all grades given to restaurants by local food critics. We're just offering a more personal approach to restaurant recommendations.
Course Restaurant Guide also offers the world's most advanced restaurant & bar bucket list maker to help you organize and share your lists of the places you don't want to forget about.
It's ironic - we found that the best way of removing individual bias from restaurant ratings & recommendations was to create a platform that essentially serves as a celebration of bias and diversity.
- Josh Sapienza | UbiquityAdvisors.com
Dig in !