Beli: A New Way to Digest NYC

Imagine being a foodie who has just moved to New York City. Between friends, family, and my TikTok feed, I’m inundated with recommendations for restaurants, coffee shops, bakeries, and more. I can’t sort through the noise. Current products like Google Maps & Yelp allow you to bookmark spots, but with no way to prioritize. My Notes app is an unorganized mess. Additionally, foodies develop preferences over time — no product codifies & incorporates these into their recommendations.

This is where Beli, my latest product obsession, comes in handy. It’s designed for the restaurant-obsessed who struggles to keep track of the many places they’ve been and want to go. Their approach differentiates in 2 major ways.

1/ Restaurant ranking. Most apps ask for the objective 5-star scale — Beli primarily asks you to rank a restaurant compared to another place you’ve visited. It repeats this binary comparison until there’s a clear pecking order, and scores your suggestion relative to your other visits. My hypothesis is that the target customer appreciates the quantified approach to ranking more than the additional friction of this approach.

2/ Social recommendations. There’s a closed network of friends who are presumably actively ranking restaurants. This is uniquely valuable for the foodie — I trust my network’s recommendations. Additionally, Beli tracks customers who have similar rankings to yours & populates a list of restaurants they all ranked highly for you to try. This is ordered by proximity as well, creating the most compelling and actionable recommendation list I’ve seen in a food recommendation product. I can search for recommendations on a map of the city, planning for which place to go to the next time I’m in a certain neighborhood.

Note that there’s one big weakness in Beli — the ranking system is on a 10-point scale, and while I might love the local bakery, it’s meaningless to compare it directly against a Michelin-star restaurant and make a decision. With the hypothesis that Beli is optimizing for restaurant rankings, a couple of potential solutions come to mind: categorized rankings, a secondary ranking algorithm that orders the same type of restaurant, or optimizing the user experience for location-driven recommendations.

I’m confident Beli’s working on all of these suggestions. It’s a small app and is currently invite-only as they iterate on the core product. Their MVP is still helping make NYC’s diverse food culture a little more digestible, and I’m excited to see what they do next!