As brands start to embrace unified commerce, consolidating all of their data from disparate systems and channels onto a single backend, do they need to shift the way they think about data and their data management strategies? Genevieve Broadhead, Global Lead of Retail Solutions at MongoDB, shares her perspectives on the role of data in a unified world.
Q: Unified commerce has emerged as an industry buzzword. How do you define it, and how is it different from omnichannel?
A: Unified commerce is the evolution of omnichannel. Previously, the focus was on quickly adding new channels—online, mobile, social commerce, etc. Now, the shift is toward integrating those channels to create a seamless, personalized experience for the customer. Instead of separate touchpoints, retailers are working toward a unified system that brings everything together — inventory, customer data, loyalty programs, and more — so that every interaction is connected and consistent.
Q: What role does data play in achieving unified commerce?
A: Data is the foundation of unified commerce. Without unified data, there is no unified commerce. Retailers have historically managed data in silos — customer data in one place, loyalty data in another and inventory data in yet another. Bringing all of this together into a single operational layer enables businesses to create true 360-degree views of customers, inventory and interactions. This is essential for features like buy-online-pick-up-in-store (BOPIS), real-time personalization and seamless cross-channel experiences.
I don’t see the rise of unified commerce as a paradigm shift for retailers, I see it more as an acceleration of current data strategies. This is the direction they’ve been moving anyway. What unified commerce does is ask, ‘Now that you’ve got all your data in one place, what business benefits can you reap of that?’
Global Lead of Retail Solutions, MongoDB
Q: So, what are the key business benefits of unified commerce?
A: One of the biggest advantages is a more personalized and seamless customer experience, which drives higher engagement and loyalty. Beyond that, businesses can gain better insights into customer behavior across all touchpoints, allowing for more targeted marketing, improved demand forecasting and optimized inventory management. For example, understanding both your in-store and online purchasing habits means they can deploy personalized marketing pushes at certain times of day when they know you’re going to be shopping in-store.
If they know that you buy dog food every week, they can suggest that you subscribe and have it delivered every week. On the other hand, with real-time insights, they can start making clever decisions — so, once they know you bought your weekly dog food, they can automatically send a notification to replenish it. With this well-rounded view, they can start automating some things around the supply chain — that's the next level.
Q: Speaking of physical stores, is it difficult to bring them into the unified ecosystem?
A: Traditionally, integrating brick-and-mortar stores into a unified system has been a challenge due to legacy technology. Many retailers have advanced digital experiences online but rely on outdated systems in stores. Bringing the data from these two worlds together can be incredibly complicated, and with Gen Z expecting to have that same personalized experience in-store, there’s suddenly the need for in-store data to become part of and transform the application stack.
By digitizing in-store interactions, retailers can enable better customer recognition, real-time recommendations and improved associate-assisted selling. This is where concepts like clienteling come into play — equipping store associates with access to customer purchase history and preferences to provide a highly personalized shopping experience.
Global Lead of Retail Solutions, MongoDB
This is multimodal data, different types of data from different systems, such as POS, RFID tracking and social media interactions. Brands need a database with a flexible document model to bring it all together.
Q: Is this where MongoDB fits in the equation?
A: Absolutely. MongoDB’s core functionality powers modern applications at the data layer. Where we differ from other technologies is that we offer a flexible document model that allows retailers to consolidate and manage diverse data sources seamlessly. Unlike traditional relational databases, which require rigid schemas, our model allows retailers to integrate new data types without major disruptions.
So, instead of breaking things up into rows and tables as you would in the relational world, you can keep them together in one unit and add new attributes or items in real-time.
For example, let's say for my unified commerce strategy, I want to start understanding sales transactions for a specific in-store customer, I can add that to the customer data model without having to create something completely new and without any kind of application downtime. This flexibility allows retailers to bring more and more data, energizing these single views of data entities, breaking down silos and creating a single view of the customer, inventory and operations across the organization.
As I mentioned earlier, you need unified data for unified commerce, You need to bring together everything from every source to get that unified view. That’s how retailers can put the customer at the core of everything they're doing.
Global Lead of Retail Solutions, MongoDB
Q: How does having this unified view tie into leveraging AI and real-time analytics?
A: Traditionally, businesses separated operational data (used for running applications) from analytical or AI-driven data (used for insights and predictions). The problem is that AI and real-time decision-making require immediate access to operational data.
For example, a retailer might offer personalized recommendations based on past purchases, but to be truly relevant, they also need to consider real-time factors like what's currently in the shopper’s cart, trending products, local weather conditions or nearby events. By merging operational and analytical data, retailers can deliver these real-time AI-driven experiences and improve decision-making across the business.
Q: Is a composable architecture necessary for unified commerce?
A: While not mandatory, composable architecture makes implementing unified commerce much easier. MongoDB serves as a foundational data layer for composable commerce architectures. We’re an enabling member of the MACH Alliance, which means that our technology facilitates building composable architectures. Whether retailers are building custom applications or using composable platforms like commercetools, our solution enables them to store and manage their data in a unified and scalable way.
Q: Final thoughts — what’s next for unified commerce?
A: The industry is moving toward more real-time, AI-driven and hyper-personalized experiences. As consumer expectations rise, retailers must ensure their data is unified and accessible across all channels. The future of commerce lies in leveraging this data effectively — whether through AI-driven recommendations, automated inventory management or smarter supply chain decisions. Unified commerce isn’t just about connecting channels — it’s about using data intelligently to create truly seamless and engaging customer experiences.
To learn more about how unified commerce is enabling retailers to meet rising expectations and explore the three pivotal trends driving the future, download our white paper, Reimagining Retail in 2025: How retailers are adapting, evolving and thriving in a changing world.
Marlies Isabella Riepl is a seasoned marketing expert and the Team Lead, Global Partner Marketing at commercetools, where she spearheads global marketing with strategic partners. Passionate about fostering inclusivity in the tech industry, she co-founded the first “Women at commercetools” employee resource group.