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Gamified Restaurant Discovery Mobile Application

Client

The client is a technology startup that has emerged as a leading player in the local restaurant discovery space, covering major cities along the East Coast of the United States. The company was founded in 2014 with the goal of creating a collaborative marketing platform for local restaurant owners.

Industry

Hospitality

Overview

The mobile application incorporates a gamified approach to discover local restaurants and avail dynamic discounts. It offers a fighting chance for local eateries that struggle to compete with well-established restaurant chains. The application also serves as a marketing and analytics platform, enabling restaurants to post promotions, daily specials, and customer reviews.

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Business Requirement

A solution that connects local restaurants and diners through a unified mobile platform.

For Diners
  • Gamified experience to promote user engagement
  • Find nearby restaurants and view offers
For Restaurants
  • Showcase and manage business offerings
  • Increase footfall on slow days
  • Dynamic pricing
  • Get actionable insights on sales

QBurst Solution

The gamified mobile application enables users to spin a wheel and win discounts at participating restaurants in the neighborhood. The Optimal Discount Computation Algorithm determines optimal discounts based on factors such as app usage, day of week, time of day, weather conditions, and restaurant performance. The application integrates popular application such as Uber and Maps to help users commute and navigate to the restaurants.

Merchants benefit from the application’s advertising platform by announcing promotions and offers to attract customers on slow days. The advanced analytics engine enables merchants to analyze aspects such as footfall, spend patterns, and time/duration of visit.

Elastic load balancer in the backend distributes the load between API servers for seamless performance while auto scaling ensures app availability at all times. MongoDB replica sets created with primary and secondary servers ensure redundancy and high availability of data.

End Result

The application has achieved phenomenal growth since launch.

  • From 100+ users at the time of launch to 250K+ users in 18 months
  • From 8 restaurants to 1500+ restaurants in 18 months
  • From one city to 16 cities in 18 months
  • 25% MAU (Monthly Active Users)

Key Features

User Application
  • View restaurants in a neighborhood
  • GPS verified check-ins
  • Re-engagement notifications
  • View menu, pictures, reviews, and location
  • Avail discounts based on day, time, and weather
  • Rate and review checked-in restaurants
  • Earn points for spinning, dining, and posting reviews
  • Upgrade user level (gold, silver, green)
  • Share app, discounts received, and restaurant ratings on social media
Merchant Application
  • Customize restaurant page by adding menu, photos, promotions, and more
  • View GPS verified ratings and reviews submitted by customers
  • Connect with users who have submitted ratings and reviews
  • Get actionable insights to make better business decisions
Admin Web Application
  • Manage restaurants, users, and other app-related information
  • Configure discounts and run promotions
  • Send push notifications to users and restaurant owners
  • View real-time mobile app analytics

Technologies

  • Appium
  • REST Assured
  • Xcode
  • TestNG
  • Eclipse
  • Selenium 3
  • Winium
  • ANT
  • Java

Business Requirement

A solution that connects local restaurants and diners through a unified mobile platform.

For Diners
  • Gamified experience to promote user engagement
  • Find nearby restaurants and view offers
For Restaurants
  • Showcase and manage business offerings
  • Increase footfall on slow days
  • Dynamic pricing
  • Get actionable insights on sales

QBurst Solution

The gamified mobile application enables users to spin a wheel and win discounts at participating restaurants in the neighborhood. The Optimal Discount Computation Algorithm determines optimal discounts based on factors such as app usage, day of week, time of day, weather conditions, and restaurant performance. The application integrates popular application such as Uber and Maps to help users commute and navigate to the restaurants.

Merchants benefit from the application’s advertising platform by announcing promotions and offers to attract customers on slow days. The advanced analytics engine enables merchants to analyze aspects such as footfall, spend patterns, and time/duration of visit.

Elastic load balancer in the backend distributes the load between API servers for seamless performance while auto scaling ensures app availability at all times. MongoDB replica sets created with primary and secondary servers ensure redundancy and high availability of data.

End Result

The application has achieved phenomenal growth since launch.

  • From 100+ users at the time of launch to 250K+ users in 18 months
  • From 8 restaurants to 1500+ restaurants in 18 months
  • From one city to 16 cities in 18 months
  • 25% MAU (Monthly Active Users)

Key Features

User Application
  • View restaurants in a neighborhood
  • GPS verified check-ins
  • Re-engagement notifications
  • View menu, pictures, reviews, and location
  • Avail discounts based on day, time, and weather
  • Rate and review checked-in restaurants
  • Earn points for spinning, dining, and posting reviews
  • Upgrade user level (gold, silver, green)
  • Share app, discounts received, and restaurant ratings on social media
Merchant Application
  • Customize restaurant page by adding menu, photos, promotions, and more
  • View GPS verified ratings and reviews submitted by customers
  • Connect with users who have submitted ratings and reviews
  • Get actionable insights to make better business decisions
Admin Web Application
  • Manage restaurants, users, and other app-related information
  • Configure discounts and run promotions
  • Send push notifications to users and restaurant owners
  • View real-time mobile app analytics

Technologies

  • iOS, Android
  • JavaScript
  • KeychainItemWrapper
  • Facebook SDK
  • Python
  • Location Services
  • Flurry Analytics
  • Maps

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