MOBILE ORDERING
MOBILE ORDERING
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PROBLEM
PROBLEM
The company relied exclusively on offline ordering procedures in its restaurants. During peak hours, this created long queues at checkouts and drive-thru windows, negatively impacting both restaurant efficiency and customer satisfaction.
At the same time, the local market was highly competitive, with numerous third-party food delivery and online ordering platforms already offering excellent digital user experiences. Despite this, customer demand for a native ordering solution within the company’s ecosystem remained strong.
The company’s existing mobile app was limited to menu visualization with low user engagement and lacked essential customer-demand management tools such as personalized offers or a loyalty program.
SOLUTION
SOLUTION
A mobile ordering service that enables customers to place orders directly through the app and collect their meals in restaurants using their preferred fulfillment method — dine-in, takeaway, or drive-thru.
PRODUCT TYPE: customer-facing mobile application
TARGET AUDIENCE: general consumers, restaurant crew
TEAM
TEAM
2 outsourced feature teams
Core team size: 15 people
Overall team line-up: project manager, designer, system analysts, back-end developers, mobile developers, QA engineers, DevOps engineers
STACK
STACK
Native mobile application
Microservice architecture
Customer data platform
Python, Kotlin, Swift
REST APIs
MY CONTRIBUTION
MY CONTRIBUTION
Performed market and customer research
Analyzed operational procedures
Created product vision and strategy
Defined feature roadmap and led the development cycles
Spearheaded integrations with payment gateway, POS and internal financial systems
Led cross-functional project team
Planned and performed service deployment
Monitored service performance and analyzed data for insights
MY ACHIEVEMENTS
MY ACHIEVEMENTS
Launched mobile ordering service in the 850+ restaurants
Generated 35% of incremental sales during the pandemic
Increase app MAU by 40% and transaction frequency by 25%
Reduced peak hours load on the restaurant staff by 33%
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