To stand out amidst fierce competition, retailers can distinguish themselves by delivering personalized, omnichannel shopping experiences. They can offer consumers new services quickly and consistently across all retail channels, with data-driven innovation. However, achieving this requires integrating a multitude of systems, and streamlining data and application management to meet the ever-growing expectations of today’s consumers. Shoppers expect immediate responses when they are searching for items, tracking orders and redeeming coupons; if a retail site doesn’t provide fast responses customers will move on, leading to churn and lost sales.

Delivering a seamless, data-driven omnichannel shopping experience requires advanced, effective technology. Established retailers use a number of systems, including PIMs, CRMs, and ERPs, that are usually acquired incrementally as the business expands. Many of these systems operate on outdated data technologies that struggle to adapt to the contemporary demands of consumers. Additionally, these systems may not be able to meet surges in demand during events such as Black Friday. This technical burden impedes progress and obstructs retailers from seizing opportunities in the ecommerce landscape. These technical challenges become especially pronounced when retailers want to introduce new digital services rapidly, and at scale. 

Retail – Real-Time Processing

Real-time data forms the backbone of customer-facing services in retail, driving responsiveness and performance. However, many retailers are unable to fully utilize their data since they cannot access the data easily, nor can they efficiently unite all sources of data to be able to glean valuable insights. For example, areas such as risk modeling and loyalty programs require both real-time and historical data sources, to be able to provide data-driven analytics in retail. Organizations that are not able to repurpose historical patterns for real-time functions are not able to leverage their data effectively. It’s akin to having a drawer filled with valuable yet aging items – the challenge lies in extracting their worth. 

Supply chains are an essential component of retail operations, and organizations must synchronize between the various systems to efficiently manage stock levels and product distribution. Failure to provide accurate, real time inventory data can result in negative customer experiences and lost revenue. The integration of event-driven real-time data in the retail supply chain is indispensable for the company’s customer retention and its bottom line.

Mergers and acquisitions are quite common in the retail industry, leading to significant challenges to the IT teams who are tasked with unifying the various systems and eliminating redundancies. Moreover, data quality poses a persistent concern, as any inaccuracies introduce risk into decision-making for real time processing and operations. 

Retailers aim to maximize business value from all data sources, to be able to provide fast online responses, and harmonious digital and in-store experiences. Technically, this requires simplifying data access and easing the burden on legacy systems, since response time is limited by the slowest element in the chain.

Real-Time Consolidation of Multisource Data: Mission Possible

Traditionally, retail organizations grappled with the complexities of connecting multiple data sources to applications. At the core of their architecture lie various backend systems such as SQL, SAP, Oracle, and IBM DB2, coupled with an API layer that facilitates communication with modern applications. However, this setup often resembles a tangled web of connections, prone to maintenance challenges and latency issues.

Imagine a scenario where this convoluted network of connections is replaced with a streamlined solution. Enter an Operational Data Hub such as GigaSpaces Smart DIH, an innovative architecture that decouples digital services from their systems of record. The Hub eliminates the spaghetti-like complexity of traditional setups by elegantly unifying heterogeneous data sources, facilitating smoother data access, and delivering extremely high performance and scale. Smart DIH exposes data microservices to digital apps in real-time, ensuring data consistency across all digital channels and providing an enhanced 360 view of the customer. This comprehensive, up to date view of the customer enables the retailer to deliver a superb omnichannel customer experience. 

Smart DIH architecture for retail operations

By incorporating Change Data Capture (CDC) technology, an open event bus and a powerful in-memory-data-grid, Smart DIH enables organizations to run powerful business logic such as retail loyalty, personal offers and location based experiences. The platform provides instant access to data at the edge where the online apps are running.  

Due to the open design of the Smart DIH platform, integration with almost any data store and application is possible. The platform delivers powerful compute capabilities and offers always-fresh data. Smart DIH integrates with retail systems such as ERPs, WMSs, and CRMs, as well as any application capable of sending data to Kafka. This design allows any application capable of interacting with REST endpoints to consume data and business logic. By decoupling digital applications from backend systems, Smart DIH reduces reliance on backend applications, alleviating the burden of excessive calls and eliminating the dependence on downtime for maintenance. Furthermore, its scalability ensures seamless support for millions of concurrent users on the front end. 

Smart DIH offers versatility, operating both on-premises, in the cloud and in hybrid configurations, empowering organizations to leverage its capabilities wherever needed. 

To learn more about how Smart DIH powers retail operations, read the Smart DIH Retail Solution Overview.

Data-Driven Retail Businesses

In a rapidly evolving and highly competitive landscape, retailers must offer unparalleled customer experiences, requiring innovative features and top performance. This translates into practical business and operational steps that need to be undertaken:

• Accelerate revenue generation: roll out new personalized offers across all channels to increase engagement and customer loyalty and reduce churn 
• Offer a unified shopping experience: provide a cohesive and responsive shopping experience across all retail channels and regions, promoting customer satisfaction and loyalty
• Streamline development of new services: develop and launch new offers swiftly, to gain a competitive edge in the market
• Integrate data effortlessly: integrate data APIs with front-end applications across retail channels and regions rapidly, enhancing the customer experience with the delivery of fresh, accurate data with ultra-low latency 
• Ensure scalability: ensure that the infrastructure is designed to scale to meet shopping peaks and support millions of concurrent transactions and users, even during peak loads 
• Optimize IT Infrastructure: scale the IT footprint dynamically to meet business demands and address shopping peaks, minimizing overload by reducing API calls to backend systems

To Wrap It Up

No doubt there is a pressing need for retailers to modernize their data infrastructure to meet the high demands of today’s customers, without completely replacing legacy systems. Fragmented data sources and outdated systems pose multiple challenges to retailers who want to provide a unified shopping experience and stay competitive in the evolving retail environment. An operational data hub such as Smart DIH streamlines data management with low code microservices, offering efficient delivery of new digital services in days. 

By leveraging Smart DIH’s ability to unite disparate data sources and scale, retailers can enhance agility, and efficiency, and offer superb customer experiences, allowing for seamless rollout of new offers, integration of data across channels, and scalability to meet peak demands.