The Shift to AI-Driven Order Management: A DTC Perspective

As retailers expand their direct-to-consumer (DTC) channels to meet modern consumer expectations, they face a range of complex challenges: unpredictable demand patterns leading to stockouts or overstock, complex multi-node fulfillment decisions that impact delivery speed and cost, and last-mile coordination challenges that can make or break customer satisfaction. 

DTC retailers particularly struggle with:

• Real-time inventory visibility: Maintaining accurate inventory data across warehouses, stores, and in-transit stock to prevent overselling and optimize fulfillment.
• Channel inventory optimization: Controlling inventory exposure by region impacts delivery speed and cost for retailers running multi-node fulfillment. The challenge lies in strategically exposing inventory by region or fulfillment type, from stores, warehouses, and fulfillment centers while maintaining the flexibility to shift availability based on selling patterns and promotion performance.
• Store fulfillment: Having to choose between speed and cost across multiple potential fulfillment locations while factoring in inventory levels, carrier capacity, and delivery promises.
• Margin protection: Stock imbalances force difficult tradeoffs between shipping costs in terms of split shipments, promotion depth, and inventory carrying costs when deciding how to fulfill orders and move through inventory effectively.

With so many retailers focusing on DTC these days, it is interesting to see how they are successfully tackling these challenges using new tools and technologies. Efforts to streamline data strategy, boost customer satisfaction, and improve profit margins have been reinvigorated with a new, game-changing element: Generative AI. 

For order management and the last mile, retail operations teams can now leverage Generative AI to optimize fulfillment logistics centralized in their order management platform. And, it all contributes to delivering consistently on the customer experience, being more data-driven, reducing costs, and improving profit margins. 

In this blog, we’ll explore examples of omnichannel retail strategies and how Generative AI is unlocking new opportunities and eliminating frustrating challenges for DTC brands.

Large retailers are shifting focus to DTC

Successful retailers are finding success by focusing on their DTC channels. Here’s how a few notable brands have navigated the transition:

• Steve Madden has shifted its focus to DTC while maintaining traditional retail partnerships. With over $1.7 billion in annual sales, the company improved its gross margins by enhancing the online shopping experience and moving from discounting to loyalty-building initiatives.
• Levi Strauss & Co. has historically sold its products through major retailers like Target and Urban Outfitters. To better serve its DTC customers, Levi Strauss & Co. has opened more brick-and-mortar stores and invested in enhanced inventory management systems.
• Skechers is also pivoting to DTC by expanding order orchestration at its North American distribution center. Automation has improved e-commerce order fulfillment, enabling Skechers to scale its DTC operations more efficiently.

3 key DTC opportunities for retailers

As the retail landscape shifts, retailers are aiming to reach the ever-higher customer expectation bar by focusing on growth and efficiency based on their system maturity and operational scale. Here are three major areas where retailers are investing:

1. Optimizing omnichannel fulfillment with more flexibility

Retailers with less mature omnichannel strategies are launching store fulfillment processes like Buy Online, Pick-Up In-Store (BOPIS), and ship-from-store. This improves e-commerce metrics by increasing delivery speed, reducing shipping costs, and improving customer satisfaction. 

What we’re hearing from fabric customers: A $500M+ ECOM GMV retailer shared how optimizing its fulfillment processes was critical to scaling its e-commerce demand. 

2. Improving customer experience with streamlined systems 

Retailers with customized e-commerce systems are prioritizing the customer service experience. The challenge lies in gathering actionable insights to deliver personalized customer interactions. Without a cloud-based OMS and robust real-time data platform to run their e-commerce operations, gaining visibility into the customer journey is difficult. 

What we’re hearing from fabric customers: Retailers in the $500M–$2B ECOM GMV range are expressing a strong need for enhanced order management insights to support personalized experiences and improve order fulfillment.

3. Reducing total cost of ownership (TCO) with cloud-based solutions 

Larger retailers with legacy systems, like on-premise implementations of Manhattan Associates or IBM Sterling, are seeking to reduce their total cost of ownership. With the high costs of upgrades and maintenance, transitioning to cloud-based platforms lowers those operational expenses and offers real-time data insights. This shift provides scalability, speed, and insights without the burden and expense of managing a complex infrastructure.

What we’re hearing from fabric customers: A retailer with $600M+ DTC e-commerce revenue faced a $10M estimate to upgrade from their on-premises DOM deployment to a new cloud version of their existing system.  

How fabric is empowering DTC retailers with Generative AI

fabric Order Management System (OMS) offers retailers a centralized platform for managing orders, inventory, and fulfillment across multiple channels. By integrating real-time data analysis, trend detection, and intelligent suggestions, fabric OMS ensures seamless operations and a unified view of the DTC customer journey.

fabric’s Generative AI builds on this with an AI-powered assistant that optimizes last-mile order orchestration. Powered by agentic AI that performs specific tasks with the help of large language models (LLMs), this AI assistant offers real-time insights and suggestions for improving DTC operations and other fulfillment efficiency.

Top benefits of an AI-powered assistant

fabric’s Generative AI-powered assistant sits atop fabric’s modern OMS and delivers the following key benefits:

• Intelligent fulfillment orchestration: Eliminates manual tradeoffs between speed and cost by automatically evaluating inventory levels, carrier capacity, and delivery promises across locations. Using analytics insights, AI recommends new fulfillment rules and automation procedures to continuously optimize decisions to meet service levels while minimizing shipping costs and split shipments.
• Seamless store fulfillment: Boosts site conversion and average order value (AOV) by enabling online shoppers to purchase physical store inventory. It provides ship-from-store options and easy-to-use interfaces for store associates to manage orders efficiently. AI-powered store fulfillment optimization dynamically evaluates store capacity, staffing levels, and historical fulfillment performance to intelligently allocate online orders to stores. The AI assistant continuously learns from fulfillment patterns to improve store selection, boost pick/pack efficiency, and balance workload across locations—all while maintaining target service levels and maximizing conversion of store inventory.
• Unified data with AI-powered insights: Centralizes fulfillment data across channels, enabling operators to interact with fabric’s AI assistant for rich analytics around split shipments, on-time delivery, location performance, and other real-time insights, recommendations, and actions to guide better decision-making and deliver personalized customer experiences.
• AI-augmented customer support interactions: Automating responses for common inquiries and enabling proactive customer communication improves service quality, reduces response times, and enables personalized interactions that elevate customer satisfaction and loyalty.

As the DTC landscape evolves, purpose-built technology is critical for success. Retailers aiming to streamline DTC fulfillment, enhance the customer experience, and reduce the costs associated with legacy systems can benefit from a modern OMS powered by AI.

Unlock the full potential of omnichannel retail with fabric

fabric’s AI-powered OMS services enable retailers to modernize their omnichannel strategies, reduce operational complexity, and drive long-term growth. Today, an emerging component of that growth is DTC. By leveraging these tools, businesses can future-proof their entire retail strategy, lower total costs, and improve customer satisfaction and profitability across every channel.

Ready to move ahead in a world where 70% of shopping begins online? Watch our on-demand webinar, “The Future of Retail: Thriving in the Age of AI and Connected Commerce,” led by experts Jay Topper and Jenna Flateman Posner, as they explore how AI is transforming retail operations.

---