Imagine a retail landscape where AI isn’t just a buzzword on the lips of every solution vendor but a transformative force capable of adding true value to the merchandising process. It’s no longer about suggesting that solutions have AI capability of some capacity. Instead, it’s about a complete paradigm shift from siloed optimization to a collaborative, integrated approach that harnesses AI’s full potential throughout end-to-end planning cycles.

A decade of learning, adapting, and unlocking truths

Reflecting on a decade of AI engagements in retail, it’s undeniable: AI thrives in complex, data-rich environments with frequent decision-making. We’re not just talking about marginal improvements; we’re discussing revolution in areas like:

• Demand Planning: Leverage new demand signals to drive breakthrough automation and accuracy for inventory planning and optimization
• Pricing: Simulate and predict experiences and related products to identify the optimal price based on real-time supply and demand, promotional cadence, competitors’ pricing, and customers’ behavioral profiles.
• Customer behavior modeling: Improve predictive models about customers from internal and external data sources for marketing, merchandising, digital commerce, supply chain, and customer service. Behavior models provide a view of customers’ browsing and purchase activities.

AI doesn’t simply execute tasks. It learns, adapts, and reveals hidden patterns in data previously out of reach. Imagine the power of AI-driven root cause analysis uncovering sales’ true drivers or identifying “hero product” attributes that unlock strategic, future-proof planning.

Attribute-based planning: The cornerstone of customer-centric decisions

At the heart of this transformation lies attribute-based planning. This empowers retailers to make data-driven decisions about ranges, channels, and new products, moving away from solely budget-driven assumptions. By anchoring these decisions in customer-centric data, planning becomes a precision exercise, attuned to the market’s heartbeat.

Take assortment planning as an example. With AI-led planning, retailers can curate intelligent, targeted assortments, offering fewer but more relevant styles and colors that resonate with individual customer values. This doesn’t mean limiting choices. Instead, it’s about refining them, cutting through the noise to offer more targeted and desirable selections.

Moving from “one-size-fits-all” to “customer-specific” assortments

The “one-size-fits-all” notion is a relic of the past, replaced by the reign of “customer-specific” assortments. Traditional “wedging” and “clustering” are being upended by AI-powered “local” assortments that are not just market-specific but tailored to individual customers.

According to Gartner, AI and machine learning will be among the top game-changing technologies to be implemented in retail by 2026. It’s a call to action for multichannel retailers to lay the foundations for AI and automation this year.

Embrace AI as a visionary partner to shape the future of fashion retail

It’s time to view AI as a tool and a visionary partner with each customer in mind. This new era demands a shift in perspective – where AI becomes the lens through which all merchandise is viewed, understood, and perfected. Let AI lead assortment planning activities, ensuring every step aligns with the unique tempo of customer desire.

Are retailers ready to reimagine their approach?

The real question remains. Are retailers ready to embrace AI and not just inform but define the future of retail? With Microsoft Azure’s suite of AI-powered solutions, retailers can unlock the full potential of attribute-based planning, intelligent demand forecasting, and personalized customer experiences – paving the way for growth, convergence, and a renewed sense of purpose in 2024.