Use Cases›E-Commerce

Retail / E-Commerce

In the retail/e-commerce sector, online systems face rigorous demands due to frequent load spikes that can overpower digital storefronts. This leads to missed transactions, profoundly affecting store revenue and customer loyalty.

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Introduction

Retailers confront a daunting challenge in delivering advantageous e-commerce systems. Building a top-tier e-commerce system demands flexibility and speed. Success hinges on providing a personalized shopping experience with relevant content at consistent sub-second latency. Unsatisfied customers readily switch to other sites. Fast response and high availability are imperative. Research by Dynatrace reveals that a mere half-second change in page load times can impact online retailer sales by 10%. To achieve enhanced personalization, retailers have integrated third-party connections to Google, Facebook, Twitter, and chat functions, contributing to longer page load times. In the US, average homepage response times grew by half a second between 2016, from 3.4 to 3.9 seconds. Australian retail sites experienced average load time increases from 5.4 seconds in 2015 to 8.2 seconds in 2016. Globally, the average page load time escalated by 7% compared to 2016, reaching 4.5 seconds from 4.2 seconds. A major, North American fashion retailer saw online sales fall 11% when its website response time slowed by just half a second. When you have total annual sales in the region of $14B across 121 stores in the US and Canada, that’s tens of millions being lost.

Business Requirements

Some of the complex business requirements driving today’s e-commerce systems include:
  • Generating personalized shopping experiences in microseconds using multiple data streams
  • Omni-channel systems that deliver a consistent shopping experience to the customer across mobile and web, and in-store
  • Removal of data and system silos to present a single view of your data (warehousing, supply chain, social, customer)
  • Flexible datastore that allows full-scale updates to an entire product catalog in minutes rather than hours
  • The ability to meet peak demand workloads and then shrink systems at quieter periods to save compute costs
  • Dynamic pricing, comparing against competitors’ catalogs, and then adjusting pricing in real-time
The business requirements listed above require systems and tools that are designed for today’s workloads, and for deployment in the cloud. Despite this, many businesses are attempting to deliver systems using technology that is decades old, resulting in a prohibitive total cost of ownership in terms of hardware, software, and time.

Technical Challenges

IT teams in retail/e-commerce face a wide variety of technical challenges that are driven by the high expectations around customer experience. Customers are easily able to buy goods from another store, and the risk of losing potential customers is especially high in retail. Challenges that retail/e-commerce businesses face today include:
  • Building systems that add new business value while also remaining within tight budgets
  • Cost-effectively running a 24/7 operation with zero downtime
  • Deploying a system with fast and predictable responsiveness even if customer traffic spikes
  • Keeping up with increasing demands for faster responsiveness
  • Minimizing the risk of adding new capabilities via new technologies that could inadvertently hurt the customer experience
  • Integrating disparate data silos that capture important inventory and logistics data that contribute to a positive customer experience
  • Delivering on personalized, real-time offers that create upsell/cross-sell advantages that merchandising teams seek

Why Hazelcast

Hazelcast works with many retail/e-commerce customers that need speed, simplicity, reliability, and security in their IT systems. They tackle the ongoing challenge of customer satisfaction, and building sophisticated software solutions for business advancement is vital. Hazelcast provides the necessary benefits for deploying systems that drive competitive advantage.

Easy to Develop and Deploy

Hazelcast Platform was designed to simplify the application development process by providing a familiar API that abstracts away the complexity of running a distributed application across multiple nodes in a cluster. This allows developers to spend more time on business logic and not on writing custom integration and orchestration code. Our platform can seamlessly integrate with your IT architecture to add new capabilities without having to rip and replace your existing stack. The Hazelcast cloud-native architecture requires no special coding expertise to get the elasticity to scale up or down to meet highly fluctuating workload demands.

Performance at Scale

Whether you process a large volume of transactions, enhance online experiences with faster responsiveness, run large-scale transformations on data, or cut costs with a mainframe integration deployment, Hazelcast Platform is designed for the ultra-performance that today’s banking workloads require. The proven performance advantage is especially valuable for data-focused experimentation that enables ongoing business optimization, especially in data science initiatives including machine learning inference for fraud detection.

Mission-Critical Reliability

With built-in redundancy to protect against node failures, and efficient WAN Replication to support disaster recovery strategies that safeguard against total site failures, Hazelcast Platform was built to provide the resilience to run mission-critical systems. The extensive built-in security framework protects data from unauthorized viewers, and security APIs allow custom security controls for sensitive environments.

Customer Success Story

Generating $18.3 billion in yearly online sales, this global electronics and personal computers provider ranks among the world's top e-commerce sites, second only to Amazon.com. The platform faces extreme burst traffic during product launches and peak shopping days like Black Friday and Cyber Monday. This unique blend of a premium brand experience and high-performance scaling led the e-commerce giant to choose Hazelcast for optimal price performance.

The initial phase involved scaling to open-source Hazelcast with commercial support. After a year, a more significant phase two project transitioned to a dedicated server cluster, upgrading to Hazelcast Platform for off-heap memory management (High-Density Memory Store). They adopted JCache from a proprietary cache abstraction layer, reducing clusters from hundreds to just six servers, each with a 28GB cache space.

This shift allowed the customer to achieve scalable caching aligned with industry standards, lowering costs for licensed software, hardware, development, operations, and talent.

Use Cases

E-commerce stores can more quickly update inventory levels by leveraging fast data storage to track stock counts. This can help ensure that customers don’t get disappointed by purchasing a product that is no longer in stock. Stores get:

  • More efficient order fulfillment
  • Fewer oversell errors
  • Greater customer satisfaction

Many e-commerce store visitors spend a huge amount of time going through pages and pages of products, so catalog responsiveness needs to be fast. By caching product pages in Hazelcast, visitors will get fast page loads on the most popular products. Stores can also:

  • Scale up to handle peak retail events
  • Provide fast responsiveness for a better customer experience
  • Enable more opportunities for cross-sell/upsell

Customers who make purchases via mobile apps are particularly sensitive to delays, so the mobile shopping app has to be extremely responsive. Using Hazelcast platform as a hot data layer to deliver site content to mobile devices with in-memory speeds helps to optimize the mobile buying experience. Stores can leverage:

  • Geo-distribution of backend systems for lower latency
  • Better user experience via faster page loads
  • Competitive differentiation by focusing on content and not infrastructure

Back-office systems need to run quickly to keep up with purchases. By deploying a distributed cache-as-a-service, commonly accessed transaction data can be quickly delivered to various finance and marketing teams. These teams also can:

  • Quickly deploy new analytic apps for further business optimization
  • Reduce load on legacy financial apps
  • Get their jobs done quicker

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