Software AG Case Studies Fortune 100 Global Shipper Delivers New Revenue

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	Fortune 100 Global Shipper Delivers New Revenue Software AG

Fortune 100 Global Shipper Delivers New Revenue

Software AG

Technology Category	Analytics & Modeling - Real Time Analytics
Applicable Industries	Transportation
Applicable Functions	Sales & Marketing
Use Cases	Real-Time Location System (RTLS)
Services	Data Science Services
Challenge	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. Read More
About Customer	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. Read More
Solution	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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Applicable Industries

Transportation

Applicable Functions

Sales & Marketing

Use Cases

Real-Time Location System (RTLS)

Services

Data Science Services

Challenge

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.

About Customer

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.

Solution

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.

Impact #1	Increased revenue by presenting offers in just 120 milliseconds, an 85 percent improvement
Impact #2	Consistently exceeding SLAs
Impact #3	BigMemory adopted as global, companywide platform for in-memory data management

Impact #1

Increased revenue by presenting offers in just 120 milliseconds, an 85 percent improvement

Impact #2

Consistently exceeding SLAs

Impact #3

BigMemory adopted as global, companywide platform for in-memory data management

Benefit #1	85% improvement in presenting relevant offers & content faster
Benefit #2	Direct impact on bottom line
Benefit #3	Consistently exceeding SLAs

Benefit #1

85% improvement in presenting relevant offers & content faster

Benefit #2

Direct impact on bottom line

Benefit #3

Consistently exceeding SLAs

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Overview

Fortune 100 Global Shipper Delivers New Revenue

Operational Impact

Quantitative Benefit