Enhancing Fashion Merchandising Instincts with Data Science

McKinsey & Company recently reported that retailers using AI-based assortment planning solutions have cut SKUs by 36% while lifting sales 1-2%, a leaner merchandising strategy driven by data science. Thanks to AI-driven inventory planning, machine learning and data science, smart retailers are able to better manage SKUs, grow sales and meet customer demands to enhance decisions.

Making The Data Work for Multi-Channel Fashion Merchandising

While algorithms and AI models are setting a new standard for data accuracy, the real success in fashion merchandising comes from combining creative expertise and industry insight with automation and AI insights. Retailers understand the nuances of their markets and customers and they are able to anticipate trends and adjust, to connect with shoppers wherever they are. AI enhances this art by analyzing data at scale and providing performance-based recommendations tailored to each SKU, store and channel.

By taking massive amounts of data in real-time and turning it into precise, actionable insights, AI systems are enabling retailers to make smarter, faster decisions at a granular level. Between dynamic open‑to‑buy decisions, allocation based on localized demand and real‑time decision-making, AI-powered inventory management is making the data work for multi-channel retailers through accurate demand forecasting. 

Best Practices: Blending Science and Art in Retail

7thonline has always reinforced the message that AI is a tool, not a replacement for retail expertise or the human eye. It’s the planner, the designer and the strategist who recognizes emerging trends and applies insight. The most successful retailers approach AI‑driven merchandising as a partnership between technology and people, seamlessly blending the art of merchandising and the science of data.

While algorithms excel at analyzing data and forecasting trends, it’s humans who interpret those insights through the lens of brand vision and creative intuition. AI analyzes customer behavior, regional preferences and past performance to recommend the most optimal product mix, while merchandisers apply their intuition to curate assortments that connect the brand with their shoppers. Merchants carry the brand’s DNA into every assortment decision, ensuring that what’s on the rack resonates not just with a data profile, but with the community it serves. Combining data-driven insights with human creativity, enables retailers to make smarter, faster product decisions. 

The retail industry, particularly in fashion, is driven by individuals with a deep passion for their craft. Many have spent their careers mastering how to anticipate what shoppers will want, before they even want them. Both a learned skill and a purposeful instinct, selecting the right styles, colors and sizes for the right stores at the right time, is an art baked into the shopping experience. The strategic blend of timing, positions and sensory elements, bring a brand’s vision to life and AI helps to ensure that experience will resonate with the target audience.

Use Case Scenarios

In today’s dynamic landscape, blending the art and science of retail can look different in practice. It all depends on your own business needs. The following use cases illustrate how retailers can harmonize creative judgment with advanced technology:

Assortment Planning

Blending data and creative curation, AI-powered assortment planning ensures the product mix reflects both customer demand and brand identity. The data science behind AI systems analyzes the “what” (what product mix, what store, what channel) while merchants fine-tune the “why” using the extensive knowledge they’ve gained on which trends are still in their early stages, compelling storytelling and how shoppers will react. 

Dynamic Replenishment

While predictive analytics and real-time sales data empower dynamic replenishment decisions, such as reorders, these systems only account for seasonality, past trends and product lifecycle stages. It’s up to the merchants to detect shifts before algorithms, such as weather changes, large marketing pushes, influencer buzz and more. Using detailed insights for efficiency and precision, retailers are able to make context-aware decisions, at scale, with specificity, that react to the nuances of real-world events beyond historical data.

Trend Forecasting

AI systems can read the signals, but merchants can read between the lines. With AI systems picking up massive amounts of data from various sources, retailers are able to see early signals on trending products, long before the results hit their sales numbers by bringing breadth and speed to trend detection. Experienced merchants are the ones that know how to interpret these signals through the lens of their brand and customer, to turn the signals into differentiated product decisions. 

In each case, human expertise turns AI’s recommendations into market‑ready decisions that impact the bottom line.

Read more in the September 2025 issue of Fashion Mannuscript here: https://issuu.com/mannpublicationsmagazines/docs/fm_september_2025_full?fr=sYTRjMzg2MDI5NTU

To learn more about enhancing the art of merchandising through data science and AI-powered solutions, email us at info@7thonline.com or book a demo with the team.