Delivering a seamless and personalized customer experience across all touchpoints is essential for staying competitive in today’s rapidly evolving retail and e-commerce landscape. Unified commerce integrates all sales channels and backend systems into a single platform to ensure real-time consistency in customer interactions, inventory management, and order fulfillment. Leveraging the power of data streaming with Apache Kafka and Apache Flink, businesses can harness real-time data streaming to build a comprehensive Customer 360 view and to enable instant insights and tailored experiences. This approach not only enhances operational efficiency but also drives customer loyalty by offering a truly unified and responsive shopping experience. This blog post explores how Kafka and Flink can be pivotal in achieving real-time Customer 360 in the unified commerce ecosystem and how it differs from traditional omnichannel approaches.
Unified commerce is an approach that integrates all customer-facing channels and backend systems into a single platform, providing a seamless, consistent experience across every touchpoint, whether online, in-store, or via mobile. Unlike traditional multichannel or omnichannel strategies, where different channels might operate independently or with partial integration, unified commerce brings everything together in real time. This includes inventory management, customer data, order fulfillment, and payment processing, all managed by a central system.
While both unified commerce and omnichannel aim to provide a seamless customer experience across different channels, they differ in their approach to integration:
“The retail store plays the same role as ground control for space operations” said. Joanne Joliet, Senior Director Analyst at Gartner. The following Gartner slide already implies how crucial hybrid connectivity and real-time correlation are to process data in real-time:
The summary of a Gartner IT Symposium/Xpo quotes a few interesting statements:
Unified commerce is relevant in industries where customer experience and channel integration are critical for success. These include:
Data streaming with Apache Kafka and Apache Flink can significantly enhance unified commerce by enabling real-time data integration, processing, and analysis across various channels and backend systems.
Here is an example of a hybrid retail architecture powered by an event-driven architecture using data streaming to enable Unified Commerce:
By leveraging Kafka and Flink, unified commerce platforms can achieve high responsiveness, scalability, and a seamless customer experience.
When choosing between building a unified commerce platform or buying one, consider that building allows for tailored customization but requires significant time, resources, and expertise. Buying a pre-built solution offers quicker deployment and vendor support, though it may have limitations in flexibility, scalability, and cost efficiency.
Here are some tools, products, and SaaS solutions that support unified commerce:
The choice depends on your existing product portfolio and relationship with vendors. But keep in mind that emerging enterprise architecture trends such as event-driven architecture, microservices, data mesh, and data products enable a true decoupling for higher flexibility, cost-efficient product selection, and consistent data integration between different technologies, APIs, and cloud services. There is no need to implement everything in a monolithic architecture with tight vendor lock-in.
And even if you buy a “complete” Unified Platform with all the features you need, you still need to integrate with the rest of the software and IT applications, systems, and IoT interfaces in your enterprise architecture. Apache Kafka is the leading integration platform providing event-driven real-time communication, reliable transactional processing, and flexible deployment options to deploy in the public cloud or at the edge in a retail store.
Nobody will build an entire unified commerce platform from scratch. This means way too high cost, much effort, and a slow rollout. Hence, the above-listed products are an excellent starting point to implement unified commerce.
Most organizations leverage data streaming with Kafka and Flink to connect independent products, SaaS services, and custom microservices.
By the way: Did you know that even several of the above-listed commercial Unified Commerce products and cloud services leverage data streaming under the hood of their platform? Like the end user, these platforms require flexibility, scalability, consistent integration, and real-time data processing. That’s where Apache Kafka became the de facto standard as the foundation of the enterprise architecture.
Vendors like Salesforce or Shopify heavily rely on Apache Kafka as the foundation of their internal enterprise architecture. Many public articles are available going into the details. Let’s go deeper into one example from the above list: BigCommerce.
BigCommerce is a Unified Commerce platform that enables merchants to create commerce solutions for B2B, B2C, Multi-Storefront, Omnichannel, Headless, and International.
The solution is built on top of a fully managed Confluent Cloud. BigCommerce migrated from open-source Kafka with zero downtime, no data loss, and the ability to auto-scale. The Unified Commerce platform processes 1.6 billion messages each day comprising e-commerce events such as visits, product page views, add to cart, checkouts, orders, etc.
BigCommerce implements various retail use cases in different business units with Apache Kafka using fully managed Confluent Cloud, including:
Like BigCommerce, end users can either build their custom solution or leverage data streaming as the event-driven foundation to connect to a Unified Commerce platform and synchronize it with the other systems and databases in the enterprise architecture.
Unified commerce is a strategic approach that unifies all sales channels and backend systems into a single, integrated platform, enabling real-time data synchronization and a seamless customer experience across all touchpoints. It differs from omnichannel by eliminating the silos between channels, providing a more cohesive and responsive experience.
Unified commerce is relevant in industries like retail, hospitality, e-commerce, and healthcare, where customer experience is critical. A single platform cannot solve all problems. Flexibility, cost-efficiency, and the ability to innovate quickly with a fast time to market, leveraging innovative cloud services, requires the right enterprise architecture integration strategy.
An event-driven architecture powered by data streaming with Apache Kafka and Apache Flink can significantly enhance unified commerce by enabling real-time data processing and analysis across various channels and backend systems.
I published plenty of other retail articles that show data streaming use cases hybrid edge to cloud architectures, and success stories from enterprises around the world. Here are a few examples:
What is your strategy to build a Unified Commerce platform? Which open-source frameworks, products, or cloud services do you use? What strategy does data streaming play? Let’s connect on LinkedIn and discuss it! Stay informed about new blog posts by subscribing to my newsletter.
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