Restaurant Brands International (RBI) is a global fast-food company and one of the world's largest quick service restaurants chains managing over 29,000 restaurants in more than 100 countries. The company owns a few of the world's most prominent and iconic quick service restaurant brands, that are independently operated and serving their respective guests, franchisees and communities for decades.
RBI was looking to enable analytics for omni-channel sales and marketing by migrating and integrating data from various source systems (3rd Party vendors, customer data platforms, POS systems et. al.) and accelerate analytics centric innovation in customer, store and product initiatives. They were looking to implement strategic initiatives targeting several “ground-up” analytics capabilities to enhance business growth, operational efficiency, customer satisfaction and retention.
Existing data platform had fragmented datasets and needed to be modernized through integration of near real-time data to understand customer behavior, patterns, preferences and develop personalized campaigns.
Customer data and insights were not being used effectively for product innovation.
Effective loyalty data usage for enhanced customer engagement was lacking.
There was a need to consolidate customer purchase history, guest survey and/or call center records to share insights to restaurants on issue root-cause and enable resolution.
Minimal integration existed with 3rd party delivery aggregators to understand speed and fulfilment.
Advanced analytics use cases could not be enabled due to the lack of robust data foundation.
The analytics platform was modernized on the pillars of AWS’s Well Architected Framework. A comprehensive data foundation (Data Lake) implementation integrated data from heterogenous sources.
Designed and implemented the customer identification and segmentation solutions and built the Customer 360 golden record to generate 360-degree view of the customer.
The team applied architecture patterns like serverless and event-based computing, leveraging the AWS Lambda service for event driven code execution. This enabled near-real time automated data processing & data propagation from source to AWS S3 storage, Redshift using AWS Glue and Informatica jobs.
Data Encryption was enabled using AWS KMS service. Anonymized sensitive data using Hash Key functions.
Implemented application and platform monitoring using AWS CloudWatch. It was used to monitor Glue job status through CloudWatch logs as well as for monitoring Infrastructure like EC2 instances for CPU and memory availability and utilization, triggering events to SNS topic in failure scenarios.
Great Program Management, overall supervision of literally 50+ tracks we are running, and Kiran is on the top of all. He has been managing the entire program, resources, milestones, communications at various levels and ‘war room’ specialist. Trianz always thinks pro-actively on projects risks, missed milestones and put pro-active measures in place to mitigate the risk.
Director, Data & Analytics
Realized significant cost gains of over 30% by analyzing the current spend and recommended switching to Reserved Instances for EC2 & EMR servers.
Reduced the turnaround time for issue identification and resolution by 20% leveraging automated monitoring and notifications of cloud resources.
End-to-end data storage and automated data ingestion framework using AWS services that enabled a flexible, scalable & secure platform.
The modernized analytics platform enabled 15+ unique data products like Customer 360, Store 360, Product 360, Prime+Profitability among others that are giving the business teams valuable insights and helping them improve customer loyalty and engagement and retention.
Integration of 3rd Party aggregator data and POS data has enabled rich insights into delivery times and customer order patterns.
Enabled Metrics like ACR, SOS etc., for Business and franchisee teams in making quicker decisions on improving speed of service.
Published: 202-11-24