PriceRunner Case Study
In today’s “Now Economy,” consumers demand highly relevant and hyper-personalized experiences as they interact with brands on a multitude of devices and channels, expecting a seamless shopping journey. Online retailers must consolidate and analyze the customers’ real-time and historical data from all engagement channels, in the moment, to offer a highly personalized shopping experience.
This case study discusses how PriceRunner, a leading price comparison site in the Nordics and UK, provides consumers impartial, real-time comparisons, and how they support high peak periods such as the night before Black Friday without compromising performance. The solution leverages GigaSpaces always-on in-memory computing platform with Apache Kafka stream processing and Elastic search’s search engine. The GigaSpaces Platform provides a load-balanced environment that can flexibly and quickly scale out when necessary without compromising performance and speed.