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Randomized Restaurant Apps

Clean the Sky - Positive Eco Trends & Breakthroughs

The Hangry Website Helps Users Find a Nearby Place to Dine

— December 13, 2016 — Lifestyle
The Hangry website is a great way to break a tie when it comes to deciding on a place to eat. Everyone is familiar with the dilemma of finding a restaurant for date night when one side is dead set on Korean and the other won't budge from Greek. The Hangry website forces users to put their trust in the hands of a random computer selection, helping people to get food rather than argue.

The term "hangry" refers to the uncharacteristic irritability that people begin to affect when they haven't had a meal in a while. Such hanger can only be harmful to a relationship, so using Hangry to solve restaurant battles is essential.

The site is effectively a random restaurant generator that gives weighting to the nearest places. By clicking "Find a place!" the site will pop up a random restaurant, letting users decide from there.
Trend Themes
1. Randomized Restaurant Selection - Opportunity to create apps and websites that randomly select nearby restaurants, helping users overcome indecision and find new dining experiences.
2. Food Decision-making Assistance - Opportunity to develop technology that assists users in making decisions about where to eat, reducing conflicts and stress.
3. Location-based Food Discovery - Opportunity to create platforms that leverage location data to suggest nearby restaurants, offering users convenient dining options.
Industry Implications
1. Restaurant Technology - Opportunity for the restaurant industry to innovate by adopting or creating technology solutions that enhance the dining experience and assist users in making food choices.
2. Mobile App Development - Opportunity for mobile app developers to create apps that randomly select nearby restaurants, providing users with a unique and exciting way to find dining options.
3. Location-based Services - Opportunity for location-based service providers to develop platforms that suggest nearby restaurants based on user preferences and current location, offering personalized dining recommendations.
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