PLASTIC JUNGLE cut through the wild world of data.
Customer Company Size
SME
Region
- America
Country
- United States
Product
- Sisense
- ElastiCube
Tech Stack
- ETL
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Predictive Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Retail
- E-Commerce
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Software Design & Engineering Services
- System Integration
About The Customer
Plastic Jungle was founded to help customers tame the plastic gift card jungles of their junk drawers. The company’s unique service allows people to trade unwanted gift cards for the gift cards they actually want to use. To date, the company has sold over $30M worth of gift cards and 400 merchants partner with Plastic Jungle, whose technology has verified, traded, and sold millions of gift cards to date. The company aims to provide a seamless and efficient platform for users to manage their gift cards, ensuring they can easily exchange them for more desirable options.
The Challenge
Plastic Jungle’s business success is predicated by its ability to move faster than the competition. When the company brought in a new CFO in 2012, he aimed to deploy a data solution that would match the company culture. Speed, accuracy and agility were the key tenants for the company data approach. “We wanted to make sure we didn’t paint ourselves into corner by taking a traditional approach to data warehousing.” That meant a solution that could grow to massive amounts of data, and allow regular business users to work with data quickly without requiring a huge investment that would leave them beholden to the product.\n\nPlastic Jungle's BI requirements included the ability to:\n• Manage and sustain the entire operations aspect of Plastic Jungle’s data warehouse with little or no operating support from the engineering and IT staff\n• Allow business users to create any ad-hoc reports they required\n• Provide the abstraction layer between the schema and the metrics that the business sought\n• Refresh in close to real-time – a minimum of once per day, and ideally every couple of hours\n• Not incur a significant capital outlay
The Solution
After conducting extensive research, Bhattacharya had narrowed down options to an open source BI tool, a leading commercially available tool, and Sisense. The team chose Sisense because of the technology’s immediate return on investment. Sisense did not require a dedicated IT person to support its deployment and use. “The other tools seemed to require a technical or development team to implement and manage,” he said. Plastic Jungle didn’t believe that success in the world of data should require people in addition to software. The old approach to data simply didn’t fit with the company’s efficient and forward-looking operations.\n\n“The other great advantage”, says Bhattacharya, “is Sisense’s approach to complex data operations. You don’t have to be a PhD of Analytics to build and maintain a Sisense solution. Even for ETL, Sisense’s flexibility allows anyone to work with data in a few clicks. The company’s secret sauce, the ElastiCube, is simply superior.”
Operational Impact
Quantitative Benefit
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