Creating a Data Fabric for Composable Commerce
Powering Real-Time Insights and Personalized Experiences with Google Cloud
In the shift toward composable commerce, brands gain the flexibility to choose best-in-class tools for every function—whether it's a search platform, an OMS, an ERP, or a customer engagement platform. This modular setup enables highly scalable infrastructure and rapid adaptation to market needs, but it also brings a new challenge: managing data across a vast ecosystem of specialized tools. Without a centralized data strategy, brands can struggle to maintain real-time data flow and coherent insights across touchpoints, which limits their ability to deliver unified, personalized experiences.
A data fabric offers a powerful solution, creating a unified data layer that connects and synchronizes data from these diverse systems. By enabling seamless access to real-time data, a data fabric makes it possible for brands to personalize customer interactions in real-time, to deliver reactive and predictive business insights, and to fuel the Generative AI models that are becoming more prevalent in the technologies that brands have invested in to grow their businesses.
The Challenge: Data Fragmentation
While data fragmentation is not a new phenomenon for enterprise brands, when brands move to composable commerce, they may encounter new data complexities. A traditional all-in-one platform can centralize data and manage it from a single system, but composable commerce splits data across multiple specialized tools, often leading to greater fragmentation than a brand may have faced in the past. As inventory, customer profiles, and transaction data are siloed in different systems, brands face challenges in creating a cohesive view of their operations and customer journeys.
This disjointed data environment not only complicates day-to-day operations but also limits a brand’s ability to leverage AI and machine learning features now embedded in many platforms. For example, AI models driving product recommendations or personalized marketing depend on up-to-date, integrated data. When data is missing or outdated, these systems produce inaccurate results, undermining efforts to deliver a personalized, seamless experience.
The Opportunity: Real-Time Data for a Connected, AI-Driven Experience
A unified data fabric can transform this fragmented data landscape by centralizing and synchronizing data, creating a single, accessible source of truth. With real-time data flowing between systems, brands can act faster and with greater precision, whether it's meeting customer demands, improving inventory management, or delivering relevant recommendations. A data fabric provides the agility needed to enable AI-driven insights, ensuring each interaction reflects the latest data and customer behavior.
Consider a brand that can monitor sales trends in real-time across sales channels and regions and respond by automatically updating order routing and shipping rules to adapt to the market demand. With AI models trained on real-time data, brands can predict customer trends and adjust strategies confidently and adjust their operations proactively, ultimately improving sales and customer satisfaction.
How Google Cloud Enables a Data Fabric for Composable Commerce
A data fabric on Google Cloud connects diverse systems, delivers real-time data, and enables actionable insights that power an AI-driven, customer-centric strategy. Here’s how each Google Cloud service plays a part in building this architecture:
Pub/Sub: Real-Time Data Synchronization
Google Cloud’s Pub/Sub messaging service enables real-time data flow between systems, which is crucial for maintaining a consistent customer experience across touchpoints. For instance, if inventory changes in the OMS, Pub/Sub ensures that the updated data is instantly available to the online store, mobile app, and POS systems. This immediacy prevents stockouts and customer frustration by reflecting the latest inventory levels, improving accuracy and customer satisfaction.
Cloud Composer: Workflow Automation and Orchestration
Cloud Composer allows brands to automate complex workflows across systems, reducing manual work and ensuring data flows accurately between applications. For instance, a workflow can be set up so that when a customer makes an in-store purchase, data is updated in the e-commerce system, OMS, and loyalty program— all in real time. This automation keeps systems in sync and enhances customer experience by ensuring that each interaction is informed by the latest data.
BigQuery: A Unified Data Repository
BigQuery acts as a centralized data warehouse, aggregating data from across the commerce stack. By storing data from a variety of systems—like commerce engines, OMS, and CDPs—in one place, brands create a consolidated view of customer behavior, product performance, and operational metrics. With this single source of truth, teams can access the latest data without navigating multiple systems. BigQuery’s scalability also ensures that as data volumes grow, insights remain consistent, enabling brands to maintain accurate, real-time visibility across all operations.
Looker: Actionable Insights and Business Intelligence
Looker empowers brands to make data-driven decisions by visualizing and analyzing trends across the composable stack. Integrated with BigQuery, Looker provides real-time dashboards that display performance metrics, customer trends, and inventory levels. These insights help brands understand customer behaviors, adjust strategies, and optimize campaigns based on accurate data. For example, brands can analyze which products sell best by region and time, allowing them to tailor inventory and marketing efforts to meet localized demand.
Vertex AI: Scalable Personalization and Forecasting
With data centralized in BigQuery and available in real time through Pub/Sub, brands can leverage Vertex AI for advanced personalization and predictive insights. Vertex AI enables brands to build machine learning models that analyze customer behavior and provide personalized recommendations, product suggestions, and dynamic pricing. By delivering insights directly to customer-facing platforms, Vertex AI ensures that brands offer relevant experiences at every touchpoint, improving engagement and conversion rates.
Dataplex: Centralized Data Governance
As data flows across systems in a composable architecture, managing data governance and quality is crucial to ensure compliance and reliability. Dataplex enforces consistent governance policies, helping brands comply with privacy standards like GDPR and maintain data integrity across the data fabric. This oversight protects customer trust and prevents costly compliance issues, giving brands confidence that their data practices meet regulatory requirements.
Gaining Real Business Insights from Unified Data
One of the greatest benefits of a data fabric is its ability to empower brands with actionable insights into business performance, customer trends, and operational efficiency. By unifying data, brands can answer critical business questions that drive strategy:
- Understanding Customer Behavior: With a data fabric, brands can analyze customer journeys across channels, gaining insights into preferences, shopping habits, and responses to marketing campaigns. These insights help refine customer personas, optimize targeting, and personalize messaging based on real-time behavior.
- Improving Inventory Management and Demand Forecasting: Inventory data aggregated in real time allows brands to predict demand more accurately, reducing stockouts and overstock. By analyzing sales data, brands can forecast demand trends, position inventory strategically, and adjust for seasonal changes or regional demand surges. This real-time insight is particularly valuable for brands with large, distributed inventories that need to move products quickly to meet demand.
- Making Data-Driven Business Decisions: With Looker’s intuitive dashboards, decision-makers gain immediate visibility into sales trends, campaign performance, and customer preferences. These insights empower cross-departmental collaboration, as marketing, sales, and inventory teams work with the same data to make informed, aligned decisions. This transparency reduces guesswork and allows brands to respond swiftly to changes in the market.
A Data Fabric that Powers Agility in Composable Commerce
As brands build composable architectures, a data fabric powered by Google Cloud brings the cohesion and agility they need to succeed. By unifying data across diverse systems, enabling real-time data access, and offering robust tools for governance and insights, a data fabric built on Google Cloud supports brands in creating customer-centric experiences and making informed business decisions.
With Pub/Sub, Cloud Composer, BigQuery, Looker, Vertex AI, and Dataplex working in concert, brands can transcend the limitations of data silos, unlocking the power of real-time insights, AI-driven personalization, and predictive analytics. This unified approach helps brands thrive in an increasingly competitive market, delivering consistent, seamless experiences that resonate with today’s digital-first customers.
Everett Zufelt
VP, Strategic Partnerships & Emerging Technology, Orium
As VP Strategic Partnerships & Emerging Technology at Orium, Everett leverages his extensive technical background and over a decade of experience in headless and composable commerce to lead the development of Orium’s offerings. He guides the go-to-market strategy and supports his teams in crafting solutions that enhance the digital capabilities and operational efficiency of scaling commerce brands.