Customer Analytics Roadmap

The national retail pharmacy company with over 8,500 stores nationwide had recently implemented a new loyalty program and wanted to identify customer buying habits and use the data to drive increased sales. 

Overview

The opportunity presented was to ensure the creation of an analytics architecture that would provide a scalable method for leveraging customer analytics for marketing and also provide a strong foundation for future phases.

Strategy and Goals

RCG was entrusted with a Customer Analytics roadmap to define the current state, future state, and implementation plan for the Customer Data Mart. The effort included engaging all business teams via workshops which included Customer Insights, Marketing, Merchandising, Advertising, Store Operations, Finance, Accounting, eCommerce, Campaign Management, and Vendor Management.

RCG’s Architectural Approach started with our clients’ business drivers and business needs. As with similar projects this project was delivered incrementally, with each sequential phase providing additional value to our client. This allowed them to realize the benefits quickly, as they reduced their payback period. All work for the design and construct was done with a dual-shore model with on-site and offshore resources. Once the system was moved to production, the team started enhancements and the next phase of development.

The Final Results

The client has a clear understanding and adherence to best practices via a scalable ETL design architecture. RCG was able to guide the client in demonstrating the types of analytics that could be generated and helped drive the required customer insights with KPIs, scorecards, and dashboards along with the following solution benefits:

• An enterprise-wide view of customers
• Scalable customer analytics process for marketing to increase customer engagement and promote effective Loyalty marketing

Agile design to deliver Customer Segmentation and Direct Marketing analytics required to drive profitable shifts in customer behavior.

The Conclusion

The technical environment represented challenges to meet those goals because it became increasingly difficult to get the data required by the business managers to analyze effectively. RCG wanted to ensure the creation of an ETL design architecture that would meet both the tight deadlines of their immediate effort and provide a strong foundation for future phases of the Customer data analytics project.

The client data warehouse was a landing ground for a vast number of data sources that were not integrated and lacked standardization.  The client was looking for more efficiency and integration of data from one source of customer data. It also needed data quality, integrity, and reliability in order to provide daily and weekly analytics on key customer metrics.