Venture capitalist and high-end restaurant aficionado Bo Peabody noticed that restaurant rating systems had barely progressed in our current data-driven world.
Having experience in online startups — he founded Tripod, one of the first social networks, while still in college — Peabody decided to put together an app that allows users to input their preferences of anything from cocktails to soundtracks to find a restaurant that approximates their conception of an ideal dining experience. “It’s not so much that we’re trying to tell you that this restaurant is universally better than another one. We’re trying to tell you that this restaurant might be better for you than the next restaurant,” he explained.
The restaurants are rated by survey-taking members who must either apply or be invited to join. Peabody refers to them as Manhattan’s “restaurant nerds” who are already devoted diners at the city’s most notable spots. Eventually, Renzell will offer subscriptions that allow members to have access to exclusive events hosted by the restaurants on the list.
Another aspect that makes Renzell different is that all the data received will be shared with the eateries, which will, in turn, throw parties for Renzell members. “I’ve been shocked by the interest the restaurants have in welcoming a new, modern way of doing ratings,” Renzell said. “We just had an incredible response.”
How did this idea come about?For the last 20 years, I’ve been living two parallel lives. I’ve been a technology and media entrepreneur most of my time living in New York. I’ve done a few startups and been also an investor in several others. In my other life, I’ve been a restaurateur and have owned, together with a partner, as many as three restaurants and a large catering business. All of them are located up in the Berkshires. Our oldest restaurant, which is called Mezze, is in Williamstown, Massachusetts, and we’re celebrating our twentieth year this year, which we’re very proud of. And we have another restaurant in Great Barrington called Allium. And then we have a catering business that does 40 weddings a year as well as a bunch of other events. I’ve been living in New York since the late ‘90s, and within the last five years, I’ve always eaten in the better restaurants in the city, just because I have a passion for it. And it really dawned on me that the whole ratings and reviews ecosystem around restaurants is totally antiquated. And by living my other life of a technology entrepreneur, like all of the different industries that have been modernized by data, I saw that the ecosystem around ratings and reviews for restaurants has been totally left behind. These experiences that people are having in these restaurants, which are now as long as three hours, they’re entertainment experiences and there’s a lot of things that go into them and just having a few people go in and subjectively rate them or too many people who probably don’t have enough context to rate them, is just a bad way to do it. And the right way to do it is to have a big enough group of people where you can get enough data about the restaurant, but a small enough group where you know something about every one of them.
How were the restaurants chosen? We decided that if we were going to take this approach, that we obviously couldn’t do it for hundreds and hundreds of restaurants. In order for it to really work, you have to have a group of people who are anonymous and eating in the restaurants on their own dime. And you have to get enough of them to do it over a long enough period of time so that you can actually make the data science work. So we decided to choose what ended up being 32 different characteristics that we thought made up what it means to be a great restaurant in New York. And we scored 230 restaurants in New York on all those 32 criteria. And then we wrote an algorithm that essentially stack-ranked those 230 restaurants based on those 32 different scores that we gave every one of them. And half of the scores were existing rating systems like Wine Spectator and Michelin and New York Times and the other half of them were primary research that we did around the restaurants’ business principles and the reputations of the owners and all those things. And that’s how we ended up with this stack-rank of the top 230 restaurants and we decided that we would choose 54 and that came from us wanting to have a list that was big enough for it to matter and for our members to be able to have some degree of variability. And also for it to be small enough that all the restaurants on the list would respect each other.
Since high-end restaurants have already proven themselves, why do you think your ratings system will matter?I think it will matter, but only for a pretty small audience. This is not meant for a big audience; this is meant for a relatively small audience that actually cares about the difference and the gradations in the top hundred. And that’s why our survey covers eight different attributes for the dining experience and within those, there are 41 different granular details that we cover. So when we issue our ratings, as a consumer, you’ll be able to go in and say, ‘I care about cocktails, soundtrack, lighting levels and comfort of the seats.’
Who are the survey-taking members? Right now, members are the people who are doing the data collection for us. They’re taking the surveys that are allowing us to create these ratings. We’ve gone through the process of finding 300 people who are going to these places anyway, and we find about five more every day through an application process. Ultimately, the data will be available to everybody, but right now, the people who are our members are just the people who are giving us that data. That will allow us to give any consumer a much better view of what these places do well than they can get from any other ratings source.
Explain how consumers can use Renzell.There’s going to be three different ways that you can potentially interact with Renzell. The first way, which is available now, is to be accepted as a survey-taking member. That’s a free thing. We’re going to give all the data back to the restaurants, and in exchange for that, they’re going to do exclusive events for us. And that we’re going to package up into a membership club where people will pay a yearly fee to be able to go to those events. The ones who will be paying will not be allowed to review. There’s going to be two totally separate apps. The first, which we have today, is for the people taking the surveys. When we gather up all these events, we’re going to build a separate app that people will pay to have access to which will have all of the data in it and access to all the events. The third way is just by looking at all the data which we’re going to release publicly in September of 2016.