Nextail, a retail technology company specializing in artificial intelligence and machine learning solutions for the fashion industry, has won three awards in the 2025 Just Style Excellence Awards. The company received awards in the categories of Innovation (Merchandising Optimization), Product Launches (Inventory Optimization), and Research and Development (Fashion Inventory Engine).
The Just Style Excellence Awards honor the most significant achievements and innovations in the apparel and textile industry. Powered by GlobalData’s business intelligence, the Awards recognize the people and companies leading positive change and shaping the future of the industry.
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Nextail won the Innovation award for transforming merchandising processes with advanced, demand-driven technology. It received the Product Launches award for its intelligent inventory optimization solution that streamlines stock management across retail networks. Additionally, the company was recognized with the Research and Development award for developing a global inventory engine that sets new standards in fashion retail optimization.
Innovation in merchandising optimization: Advancing demand-driven retail
Nextail’s merchandising optimization platform was recognized for fundamentally transforming how fashion retailers approach these core business decisions. Traditionally, retailers relied on manual, reactive processes that were prone to forecasting errors and inefficiencies, often resulting in costly overstock or understock situations. Nextail’s platform replaces and greatly surpasses these legacy methods with a demand-first, AI-driven approach that places actual customer demand at the center of all merchandising decisions.
A key differentiator is the platform’s ability to operate at a “hyper-granular” level —down to the SKU, point of sale, and even day—enabling retailers to capture micro-patterns in demand that would otherwise go unnoticed. For example, the system can sense similar sales rates, ensuring that each location receives the optimal mix of products and sizes. This level of precision has been particularly impactful for brands like Guess, which reported a 5-percentage point increase in full-price sell-through and a 7.5% coverage reduction in stockouts after implementing Nextail’s system.
Nextail’s algorithms are developed by a team with deep roots in the fashion industry, including leadership positions at leading retailers such as Inditex. This expertise is embedded in the platform’s ability to handle fashion-specific complexities, such as seasonality, product lifecycle dynamics, and low-data scenarios for new product launches. The system’s unified mathematical optimization model manages multi-price scenarios, margin-based scarcity, and complex pack-handling, allowing retailers to maximize profitability even in challenging inventory situations.
The platform’s rapid and seamless integration into existing retail systems has led to full adoption among Nextail’s customer base, with some retailers reporting measurable results within months of implementation. For instance, Gina Tricot achieved a 9.6 percentage point increase in sell-through and a 13% reduction in store stockouts, while Hackett London saw a 75% reduction in time spent on replenishment and a 25% decrease in lost sales. These outcomes underscore why Nextail was recognized for innovation in merchandising optimization, as the platform delivers tangible business impact and operational efficiencies that are unattainable through traditional processes.
Product launches: Intelligent inventory optimization for fashion retail
Nextail’s award in the Product Launches category highlights its inventory optimization engine, which addresses one of fashion retail’s most persistent challenges: managing end-of-season stock imbalances. Traditionally, merchandising teams spent significant time manually planning and executing stock transfers, often with limited visibility into the impact of their decisions. This led to lost sales from stock trapped in underperforming locations, while other stores faced stockouts and excess inventory was marked down or wasted.
Nextail’s solution automates and intelligently manages these stock transfers using AI-powered forecasting and optimization algorithms. The system analyzes near real-time sell-through rates, stockout data, and store performance to recommend the optimal movement of products across the retail network. This hyperlocal intelligence ensures that products are transferred to locations where they are most likely to sell at full price, reducing the need for markdowns and minimizing leftover inventory.
A notable feature is the solution’s ability to handle complex, large-scale scenarios—processing up to 500,000 product-store combinations in a single run. This scalability is essential for retailers with extensive store networks and diverse product assortments. For example, Merkal, a leading footwear retailer in Spain, leveraged Nextail’s solution to achieve a 12-percentage point increase in sell-through for transferred units and a 4% reduction in stockouts. Similarly, Style Union, a rapidly growing Indian retailer, used the platform to achieve a 2% store out-of-stock rate and sold over 5,500 additional units at full price within four months of implementation.
The system’s scenario-based planning and real-time impact tracking allow merchandising teams to simulate different transfer strategies and immediately see the projected and actual outcomes. This not only reduces manual workload by up to 80% but also supports more agile, data-driven decision-making. Additionally, by consolidating 86.5% of end-of-season leftovers for resale, the solution contributes to retailers’ sustainability goals by reducing waste and the environmental impact of unsold inventory.
These capabilities have resulted in measurable business improvements, such as a 3% increase in overall sell-through and significant operational time savings, as evidenced by case studies from participating retailers. Nextail’s inventory optimization engine exemplifies how advanced technology can address longstanding industry pain points, earning recognition in the Product Launches category.
Research and development: The universal fashion inventory engine
Nextail’s recognition in the Research and Development category is rooted in its creation of a universal fashion inventory engine—a matheuristic optimization model designed specifically for the complexities of fashion retail. Unlike traditional heuristic approaches, which often rely on rules of thumb and manual adjustments, Nextail’s engine employs advanced mathematical programming to deliver optimal inventory decisions across allocation, replenishment, and transfers.
The engine is engineered to process millions of SKU-store combinations efficiently, accommodating the unique requirements of fashion retail such as visual merchandising rules, size curve constraints, seasonal demand fluctuations, and complex bundle configurations. For example, the engine can determine when it is optimal to break product packs or prepacks, move stock between multiple locations, and assign inventory to different usage types—all while considering operational costs, shipping constraints, and profit maximization objectives.
This universal approach enables retailers to unify their inventory management processes, eliminating the need for multiple disconnected systems or manual interventions. The engine’s flexibility supports multi-objective optimization, balancing the need to maximize full-price sales with the realities of operational costs and business rules. Its scalable architecture has been demonstrated in real-world scenarios, handling up to 500,000 product-store combinations and supporting networks with multiple warehouses, distribution centers, and stores.
The impact of this R&D investment is evident in the results achieved by Nextail’s clients. Retailers have reported up to a 3% improvement in sell-through rates and an 80% reduction in manual planning time, as the engine powers end-to-end optimization from initial allocation to in-season rebalancing. For instance, Hackett London reduced international shipments by 50% and cut replenishment preparation time by 75% after adopting Nextail’s solutions powered by the engine.
By integrating fashion-specific constraints directly into its core logic and enabling seamless collaboration between data science, engineering, and product teams, Nextail’s inventory engine sets a new benchmark for technical innovation in the apparel sector.
“We’re honored to receive this recognition, which reflects over a decade of working alongside fashion retailers to rethink how inventory and merchandising decisions are made. This recognition is a true testament to our drive to spark real, transformational change in the fashion industry, helping teams make faster, data-informed decisions and operate more successfully and with greater agility and responsibility.”
– Carlos Miragall, CEO
Company Profile
AI-driven merchandising execution solutions purpose-built for fashion
Nextail has been driving business value in fashion for over a decade in Spain and far beyond with in-season merchandising solutions. With fashion at our very core, everything from our AI and machine learning prediction models, global optimization engine, and platform embed industry best practices for faster, smarter inventory decisions—guaranteed. Our dedicated team of retail experts takes customers from start to success, challenging the status quo and ensuring financial impact.
Links
Website: https://nextail.co/
