Hoppit is the first site to provide an eating-out search engine which filters its results based on the ambience of each outlet.
Tourists already have a variety of options when trying to work out what to do based on their mood. In the US, UK and Canada the I Feel London site, which groups activities by participant mood — energetic, sophisticated, hungover — is one such example. Taking a similar concept and applying it to restaurants, Hoppit is the first site to provide a dining-out search engine which filters its results based on the ambience of venues.
Based in Manhattan and currently available in 25 cities in the US, each restaurant in the Hoppit database is tagged with one of ten “vibes” or types of atmosphere. These include ‘classy & upscale’, ‘hipster’, ‘romantic’ and ‘cozy & quaint’, among others. Users can manage their search results based on these categories, as well as the type of people they will be dining with – whether friends, family, business associate or date — the food they would like to eat, and the noise volume they would like to experience. Hoppit then displays a list of the nearby restaurants suited to the user’s plans and mood. The service uses “natural language processing technology and algorithms” to sort its data, which draws on existing online reviews. Search results are complemented by food and drink deals through sites such as Groupon and Gilt City, which are shown beside the restaurant options.
Hoppit hopes to takes the hassle out of trawling through online testimonials and also helps outlets connect with clientele suited to the ambience of their restaurant. An idea to adapt for locations outside of the cuisine world?