Urbanspoon last week released a redone version of its popular app, supplementing its shake-to-suggest slot machine with interactive maps and lists of restaurants favored


Assessing the "Where Should I Eat?" Apps

Urbanspoon last week released a redone version of its popular app, supplementing its shake-to-suggest slot machine with interactive maps and lists of restaurants favored by Eater or helmed by James Beard-nominated chefs. Another new feature notifies registered users when they're in the vicinity of a restaurant they've been wanting to try.

When the Urbanspoon app debuted in 2008, the concept of smart phone as culinary concierge was brand new; Apple featured Urbanspoon in its promotional materials as an example of the iPhone's amazing capabilities. Now, Urbanspoon is racing to keep up with the many other free apps promising to connect diners with the best possible meal (or cheapest or nearest, depending on how search filters are set.)

Since I recently made plans for lunch with a friend who's just started working near Westlake Center, I decided our date would be an interesting test case for the many restaurant-finding apps introduced over the last year. We'd settled on a time, but not a meeting place, so I put it to eight different apps to come up with the perfect venue between our offices. While a few of the apps were mortally daunted by the task, there were a few excellent suggestions in the bunch. Read on for the results:


A homegrown app, Chewsy was developed by off-duty Microsoft workers frustrated in their search for great wings. They wanted to create a site which steered users to the best dishes, not the most impressive chef, friendliest service or cleanest bathrooms: The "food nearby" tab on Chewsy is organized by menu items, not restaurants. That means it's probably a better app for an eater with a specific craving than a pair of eaters seeking a mutually-agreeable lunch spot.

Chewsy advised we seek out the mushroom bisque at ART Restaurant, which is a fairly reasonable suggestion. But its recommendations are based on reader reviews, and there aren't yet very many for our neighborhood. The app includes a comprehensive list of nearby restaurants, but clicking on most of the names summons the message "Be the first to add a review!"


Ness is beautiful. The homepage is segmented into six categories (cafe, all cuisines, dessert, sushi, seafood, steakhouse), each illustrated with slivers of gorgeous food photographs.

The Ness system is supposed to work much like Netflix: Users rate restaurants on a five-point scale, and Ness generates personalized suggestions based on their likes and dislikes. The more ratings, the better the results. The problem is Ness isn't especially creative, so when I asked for recommendations, it listed nearby restaurants which I'd just told Ness I liked. Its top lunch suggestion was Beecher's Handmade Cheese, to which I'd already given four stars.

Ness' runner-up pick was Saigon Deli: Ness was 84 percent sure I'd like it. Unfortunately, the app doesn't provide much corroboration for its advice. Clicking on "Saigon Deli" brings up an address, phone number and hours, but a brief description and additional pretty pictures would be more helpful to a user trying to evaluate an unfamiliar restaurant.



Like Chewsy, Forkly focuses on particular menu items and is driven by user interaction: Frequent contributors can gain influence points for endorsing food and drinks that other diners like.

But for eaters who aren't planning on playing the Forkly game, the app is still very useful. After setting a location range on a map, users can search for food, breakfast, coffee, wine, drinks, dessert, beer or cocktails. And, unlike many of the other apps, there's enough information entered here to make every selection viable. Forkly didn't have any trouble coming up with a place to eat pie near my house (although photo galleries become scanter as searches move further away from downtown.)

For lunch, Forkly steered me to the beef Bourguignon at RN74; crab salad with orange emulsion at ART and maccheroni with roasted tomato and cavolo nero marinara at Il Corvo, a restaurant I didn't find on any of the other apps.


Google last year bought Alfred, which uses algorithms to devise restaurant recommendations.

The app's initial set-up involves rating dozens of restaurants, so "Alfred" - depicted as a mustachioed butler with a dinner plate hood for a head - can get wise to what its boss wants. Users can then search for restaurants based on the usual criteria (distance, price, cuisine) and more oddball requirements: Alfred suggests I go to Vermillion if I'm looking for "something artsy."

But despite all the time I spent training Alfred, the app was flummoxed by my request for an individualized lunch recommendation. It suggested I try Pike Place Chowder, "because I thought you might like a surprise."


I'm probably not the ideal Nosh user. Backed by the co-founder of Google Voice, Nosh is designed to help eaters share pictures of their food with their friends. But I don't belong to Facebook, so - by Nosh standards - I don't have any friends. And without any friends to guide me, Nosh looks like a pretty barren place. All I was able to access was a list of nearby facilities with food licenses: Nosh's first choice for lunch is the Puget Sound Regional Council, a transportation planning office.


While many of the new apps are designed to narrow the number of restaurant choices, Urbanspoon swamps users with information. Eaters can click links for "Hottest in Seattle, "Urbanspoon Top Picks" and "Bargain Gems," among other lengthy lists. Many users are likely to resort to the old slot machine feature, which skews toward restaurant with positive reviews - regardless of what the editorial lists say. Urbanspoon suggested we lunch at Okinawa Teriyaki.


Fondu advertises itself as a cross between Yelp and Twitter. The description's accurate, but the concept's lacking. Users can scan a database of one- or two-sentence reviews by search term. For lunch, Fondu sent me to Happy Teriyaki, on the basis of this write-up from martidav: "The regular Teriyaki chicken is my fave. It's cheap and satisfies." Again, I found myself limited as a non-Facebooker: It's possible that if the summations came from people I knew instead of martidav, I'd find the app moderately useful.


Chef's Feed


I'd planned to delete all the food apps from my phone after writing this post, but Chef's Feed is staying. Again, the recommendations are dish-focused, but they're supplied by accomplished chefs instead of anonymous eaters. The chefs who've provided brief descriptions of the menu items they love include Jason Stratton, Jason Wilson, Jerry Traunfeld, Josh Henderson - and those are just the chefs whose first names start with the letter 'J'. If you've heard of a Seattle chef, he or she is probably represented here.

The data's searchable by restaurant, distance, dish or chef, the latter which helps users determine which advisors have simpatico palates. Turns out Daisley Gordon and I have pretty similar tastes.

Chef's Feed isn't flawless: BuiltBurger, which closed months ago, is still listed, and the restaurant information doesn't include hours. But there are other apps for that. The suggestions here are smart and strong, and while dedicated local eaters will already be familiar with most of the dishes, I wouldn't hesitate to use the app when traveling in another city (Chef's Feed currently covers nine cities, including Austin, Chicago, Los Angeles and New York, and another dozen cities are set to debut soon.)

The app doesn't presume to choose a restaurant for the user, but it's an easy enough task to count up which restaurants in a given neighborhood received the most support. Downtown, it's Serious Pie (Shaun McCrain likes the soft-egg pizza; Maria Hines is a fan of pancetta and clam and Mark Fuller goes for fennel sausage) and Le Pichet. According to Renee Erickson, the baguettes have "just the right amount of chewiness." Jason McClure adds the liver terrine is "usually the thing I want to eat at the end of both great days and bad days." Sounds like a lovely spot for lunch.

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