Improving your burger and fries experience.
McDonald’s France wanted to improve customer experience at a variety of intersections globally.
They wanted to capitalize on the power of data to build a complete perspective of a customer’s lifetime value (CLV), with visibility into each step of their journey.
We helped them move from a traditional data warehouse to a data lake, reducing the effort required to analyze or process data sets across different properties and applications.
About the Business
McDonald’s is the world’s leading global foodservice retailer with over 36,000 locations in over 100 countries. More than 80% of McDonald’s restaurants worldwide are owned and operated by independent local business men and women. McDonald’s and its franchisees employ 1.9 million people worldwide.
The Business Challenges
McDonald’s is famous for cheeseburgers and fries, but with 1.5 million customers a day, and each transaction producing 20 to 30 data points, it has also become a technology organization. With all that data available for use, McDonald’s wanted to build a complete perspective of a customer’s lifetime value, with visibility into each step of their journey. Understanding likes and dislikes based on data analysis would provide McDonald’s the opportunity to improve customer experience at a variety of intersections globally.
McDonald’s, with its multi-national reach, generates and collects an abundance of data. Creating insight from that data required a new approach to data management to ensure flexibility and scalability. The technology necessary to accomplish McDonald’s analytics goals is both cost effective and efficient in the cloud – key catalysts for initiating the project within McDonald’s groups, gaining buy-in from key stakeholders, and engaging the business quickly.
With so much data available, and the goal of improving customer experience as motivation, McDonald’s France prioritized three types of data sources – sales, speed of service, and customer experience. While collecting, aggregating, and cleaning data is a huge feat on its own, McDonald’s France also had to navigate a high level of data integration complexity.
As an omnichannel restaurant, McDonald’s juggles information from point of sales systems with sales happening online, offline, and across dozens of different locations. Data sources include multiple data vendors, mobile apps, loyalty programs, customer relationship management (CRM) systems, and other digital interfaces. Combined in one digital ecosystem, this data is the force that drives the entire customer journey. Once consolidated, the opportunity is to find correlation between the customer data that transforms the puzzle into a holistic view of the customer experience.
The 2nd Watch Solution
To meet its data collection and analysis needs, McDonald’s France needed a modern data platform equipped with data processing capabilities and cloud architecture. Focused on data insights rather than data management, the McDonald’s team partnered with 2nd Watch to ingest the various data sources into a data lake, reducing the effort required to manage and analyze the data to meet the business demands.
During the process, McDonald’s emphasized the importance of ongoing data collection from anywhere and everywhere across their many data sources. From revenue numbers and operational statistics to social media streams, kitchen management systems, commercial, regional, and structural data – they wanted everything stored for potential future use. Historical data helps establish benchmarks, forecast sales projections, and understand customer behavior over time.
The Business Benefits
McDonald’s France now has visibility into speed of service with a dedicated dashboard focused on speed of service, customer lifetime value, and conversion rate to help grow the business. The analytics also help the national teams make data-driven, accurate decisions and implement operational changes to impact operational efficiency using knowledge around prep time to influence fulfilment.
While their data journey has only begun with this first step of capitalizing on the power of data to understand and increase customer lifetime value (CLV), these initial steps opened the door to new data and prescriptive analytics possibilities. The models established by McDonald’s France will be used as an example to expand data investments throughout the McDonald’s corporation.