Customer experience optimization is much improved if updates to the system are carried out in real time


The crux of a client-business relationship is response time. With big data analytics, businesses can hope to retain clients and ramp up revenue if they reduce the response time to the minimum. Most business organizations choose to optimize the user response time by taking recourse to batch processing. They serve requests based on an earlier system state and periodically incorporate new state in the system in a batch manner. However, as EPFL researchers show, the customer experience optimization is much improved if updates to the system are carried out in real time.

Memory availability for storing incoming data and metadata was a bottleneck for real-time processing, but the advent of modern storage media has removed that hindrance. Real-time event processing and analytics implies event-driven programming and triggers action based on real-time input. It enables an organization to take immediate action on issues that require accurate responses within seconds or minutes. Many events can benefit from real-time event processing, such as sales leads, orders, and customer service calls. Real-time processing is also a good option for Point of Sale (POS) Systems to manage the inventory and sales of a particular item because it enables the organization to execute payments in real time.

On the other hand, batch data processing works well to process high volumes of data where a group of transactions is collected over a period of time. It needs separate programs for input, process, and output.

Considering the advantages of real-time processing, the current research moves away from batch processing and gravitates toward responses to a wide variety of events in real time. The findings are expected to increase efficiency in real-world scenarios such as dynamic retail, pricing, and managing the supply chain, among others.