Optimizing the Multi-Channel Customer Experience for a Restaurant Chain
by Christine Germeroth | December 13, 2021
An American fast-casual restaurant chain has rapidly grown to over 200 locations in 15 countries. Their success and popularity come from their distinct customer service experience, which brings back customers time and time again.
One of our client’s greatest challenges is ensuring a consistent customer experience during each visit and across all restaurants. The company needs to understand their customers’ expectations, likes and dislikes, and behavior to repeatedly and seamlessly delight each customer, in each interaction, and in each sales channel.
However, it wasn’t clear how customers used their multiple sales channels or how this influenced their purchasing behavior. The company lacked access and insight into critical customer data but understood that this data could be used to enhance the customer experience. For this project, the business and technical objectives include:
Increasing operational efficiency by automating and centralizing their data infrastructure
Consolidating the view of restaurant data for use by BI tools and other business applications
Building operational ability to update records and solve data quality issues in one platform
Data Strategy Approach
In close collaboration with the client, our initial discovery and review of their current environment revealed that there was:
No single cross-channel view of guest data
No timely and simple access to restaurant operations data
No centralized repository of transactional data
Insufficient governance and control for its data infrastructure
To bridge these gaps, the client asked Keyrus to:
Define a holistic data strategy that outlines the supporting architecture and toolset capable of meeting long-term business and technology objectives
Detail a specific and actionable implementation roadmap adapted to existing resources and data readiness
In our proposed data strategy roadmap and solution, Keyrus recommended implementing a data warehouse, fully productionalized and configurable ETL framework, and a data governance solution to consolidate all of their data to meet their business needs.
The solution architecture is hosted in AWS and consists of:
DWH/BI solution (Talend and Snowflake) focusing on guest data and item-level sales data
Data governance solution (Semarchy xDM) focusing on mastering all restaurant location related information
Dashboards (Tableau) for visualizing the data
Supporting implementation with a change management effort
Centralizing Sources and Cleaning Data
First, we centralized the main sources of restaurant data from their point of sales and ordering systems and several excel sheets. We used a combination of Talend and Semarchy xDM to handle data uploads and provide back-to-consuming applications.
After profiling the data, we used enrichers and validations in the Semarchy xDM platform to clean and enrich the existing data to ensure high-quality restaurant data for matching, consumption, and use across the organization (primarily in the DWH and BI-layers).
Consolidating the Data
The different sources of data were then consolidated using Semarchy’s extensive matching capabilities. Additionally, survivorship rules were configured to identify what values from what sources to keep for the single golden source of data.
Ensuring Smooth User Experience
The Keyrus team built business-friendly views of company data using Semarchy’s extensive UI functionality to support use cases such as cross-channel customer analysis.
As new restaurant locations open or existing ones change, workflows ensure that current restaurant updates and new restaurant locations get vetted by data stewards before being exposed to users and before these location values are used in reporting.
Our solution fully aligns with the organizational objectives in both the short-term and long term. The client now has one centralized solution throughout the organization to conveniently access all restaurant-related information.
Keyrus’ actionable data roadmap allowed for immediate implementation and the following outcomes:
Data is validated, updated, maintained, and governed using solution functionality and workflows
Expanded use of Tableau and self-service analytics across the organization
Opportunities for further development and integration of technologies in the data landscape are clearly outlined
Now that the data across multiple sales channels (mobile app, website, in-person cash transactions, kiosks, and third-party delivery) are consolidated, the team can gain insights on:
Customer acquisition and channel conversion analysis
Customer purchasing frequency analysis
Cohort analysis by purchasing behavior
The client is now equipped with reporting dashboards on sales, customer demographics, and purchasing behaviors to drive and enhance their customer experience.