Founded in 2012, Drop Tank provides end-to-end loyalty solutions for U.S.-based fuel brands. Drop Tank manages gas station loyalty technologies and programs for a large network of retail sites across the US. They process millions of loyalty transactions each year for millions of loyalty program members across thousands of independent gas stations (4,000+). Millions of transactions and diverse point-of-sale (POS) systems bring complexity of both scale and scope to their cloud-based data warehouse and analytics system. Add to that their desire to capture that data for analysis and insights.
Operating in a highly entrepreneurial and fast-paced environment, Drop Tank needed the ability to scale up rapidly while introducing more programs, expanding offers, improving insight capabilities, increasing member engagements, and introducing new partnerships.
To support this kind of growth, Drop Tank faced the following challenges:
- Integrating rapidly with partners
- Scaling transaction volume and retail connections
- Capturing and analyzing data for loyalty
The Vlamis Solution
Vlamis started the engagement with a needs assessment. Within a couple of weeks, Vlamis was able to provide a written assessment, road map, and high-level model design. After a competitive bid process, Vlamis was chosen to implement an end-to-end analytic warehouse solution, letting the analytic needs drive the design of the solution.
Vlamis built data models to support the analytic needs and built the ETL process to populate the model. As test data was being populated, Vlamis started working with the analysts on how to take advantage of the new analytic tool and enriched data now at their disposal.
Vlamis ensured that the analytic system built would be scalable and able to meet Drop Tank’s requirements as their business and analytical needs grow.
As with all projects, nothing goes exactly as planned. When competing business priorities and personnel changes at Drop Tank threatened to derail the project timeline, Vlamis reallocated resources and worked with Drop Tank to address the issues and keep the project on track.” Drop Tank now has a world-class system that meets their analytic needs now and in the future.
Drop Tank’s new analytic system reports their numbers in a fraction of the time required previously and responds to management requests much more quickly. In addition, Drop Tank can improve use of data richness, streamline data accessibility, accelerate decision making, and develop new analytics on a strong foundation.
Drop Tank’s new analytical system has provided the following benefits:
- Transformed Drop Tank from a reporting company to an analytics company.
- Armed Drop Tank executives and managers with better insights into their programs.
- Reduced the amount of time analysts spend extracting data and building reports and increased their focus on the user community and data discovery.
- Unlocked value-added insights, trends, and improvement opportunities.
- Moved from providing weekly/monthly reports to providing daily analysis to their consumers.
- Improved analysis of data with demographics, geo trends, member behavior, and fraud detection.
This picture captures the transformation from reporting to analytics:
- Oracle Autonomous Data Warehouse (ADW) to store the data
- Oracle Data Integrator Marketplace image (ODI) to move the data
- Oracle Analytic Cloud (OAC) to present the data
- Oracle Cloud Infrastructure (OCI) to provide integration services
- Oracle Loyalty Cloud (OLC) as a data source
With even just the first phase of their OAC implementation, Drop Tank can now easily answer vital business questions, such as these:
- What are the demographics of our customers?
- What buying habits do they have?
- How do we incentivize customers to participate with greater frequency?
- How can we use analytical insights to generate incremental value?
Armed with reliable data and analytic insights to drive rapid decision making, Drop Tank is well-positioned for anything the future holds.
For more case studies about Vlamis clients, see our Case Studies page.