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Fortune 100 Global Shipper Delivers New Revenue
技术
- 分析与建模 - 实时分析
适用行业
- 运输
适用功能
- 销售与市场营销
用例
- 实时定位系统 (RTLS)
服务
- 数据科学服务
挑战
The company, a Fortune 100 shipping company, was facing a challenge in presenting relevant cross-sell offers to its customers within the stipulated Service Level Agreements (SLAs). The company receives more than 32 million tracking requests daily, each of which presents an opportunity to increase sales and customer satisfaction by serving up relevant content and offers. However, deciding which offers to present required time-consuming calls to multiple disk-bound databases, resulting in data retrieval times at least four times slower than those mandated by SLAs. This lag was cutting into potential cross-sell revenues and putting the company at risk of upsetting customers with a subpar online experience.
关于客户
The customer is a Fortune 100 shipping company that operates in the transportation and logistics industry. The company receives more than 32 million tracking requests daily, each of which presents an opportunity to increase sales and customer satisfaction by serving up relevant content and offers. However, the company was facing a challenge in presenting these offers within the stipulated Service Level Agreements (SLAs). The company was at risk of upsetting customers with a subpar online experience due to the time-consuming calls to multiple disk-bound databases, which resulted in data retrieval times at least four times slower than those mandated by SLAs.
解决方案
The company conducted a rigorous evaluation of three alternatives for improving SLA performance: Terracotta BigMemory, IBM® webSphere® eXtreme Scale and Oracle® Coherence. The company said BigMemory immediately stood out for its ease of use, allowing the company to breeze through a proof-ofconcept implementation for BigMemory in just a few hours. Competing products, meanwhile, required weeks of setup. Even more impressive was BigMemory’s superior speed in head-to-head performance tests. The company went live with a rolling 90 days of customer data in ultra-fast machine memory. By managing customer data in BigMemory, the company accelerated the serving of relevant content by a mind-blowing 85 percent—from 900 to 120 milliseconds.
运营影响
数量效益
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