AI to Rescue Fashion Retail's Holy Grail: Product Assortment
CEO and Co-Founder, Nextail
By Joaquín Villalba
The economic downturn, the call to waste less, and the drive to be customer-centric mean all eyes are on assortments this year.
According to Gartner, retailers will aim to reduce inventory by 30% by the end of next year. Meanwhile, the Business of Fashion - McKinsey State of Fashion 2023 report found that 75% of surveyed retailers aim to cut costs by reducing the number of products and styles they offer, and 45% of fashion executives expect to update assortment mixes to adapt to market conditions.
How can you ensure that your biggest investment, your products, make up assortments that are the most likely to sell at full price and the least likely to be marked down?
Here are 3 ways AI is helping fashion retailers find the sweet spot between cutting inventory costs and remaining relevant to customers through curated assortments.
Granular, hyper-local demand forecasts for curated, local assortments
With 45% of cash-strapped customers delaying discretionary purchases, collections that don’t speak to them at all, will certainly be rejected. So the ability to create highly curated, local assortments will be a key element to a winning strategy.
AI makes it possible to take a bottom-up approach to forecasting to actually understand future demand for products at the SKU-point-of-sale level instead of relying solely on historical data and overly-broad store clusters.
Especially robust AI demand forecasts can bind different data sets such as historical, retailer, and engine-generated data to extrapolate the demand for each product and deliver smart recommendations for which products to stock, in what quantities, sizes, and in which location or channel across a brand’s network.
AI is helping fashion retailers find the sweet spot between cutting inventory costs and remaining relevant to customers through curated assortments. If you’re still using spreadsheet tools, it's time to embed AI into your business.
Automated assortment planning for faster, more sophisticated decisions and less Excel
Continuous in-season analysis and curation as reality changes
Assortments don’t live in a vacuum, and simply whittling them down won’t work if you still want to offer customers an incredible assortment of products. But if you’re still using spreadsheet tools, you won’t be able to manage the complexity required to curate assortments that change over time and by location.
By and large, many Tier 1 retailers continue to rely on basic manual spreadsheets for managing crucial assortment decisions. However, these tools lack the intelligence and automation necessary for orchestrated, dynamic, and forward-looking merchandising.
Worse yet, these tools and approaches force merchandisers to sacrifice accuracy and granularity in favor of reducing calculation complexity. Nevermind the fact that they continue to be manual.
AI, on the other hand, makes it possible to run thousands of automated simulations to recommend the most optimal product mix across stores, channels, and selling periods to maximize sales and profit. And in a matter of minutes. This simply can’t be done manually or on a spreadsheet.
The numbers are stunning. McKinsey estimates that fashion businesses that have already embedded AI into their businesses to increase operational efficiencies could achieve a 118% increase in cash flow by 2030, while those who are just starting this journey could generate a 13% increase. Laggers, on the other hand, will actually see losses.
Even if you had to make assortment decisions 12 months ago, AI makes it possible to run scenarios as stock begins to arrive at your distribution centers to reconsider these decisions to create the best assortments to match the current reality which has likely changed since the time you made your purchase.
Soon, these decision cycles will become so short, the loop will close. Assortments won’t be planned and defined before a season starts, but rather will be dynamic as real-time data will inform new decisions to discontinue products, introduce new products, etc. The pre-season and in-season will become just one continuous activity with the goal of ensuring a fresh, relevant, and appealing product mix season after season.
Joaquín Villalba, CEO and Co-Founder of Nextail, is a retail industry veteran with more than two decades of experience in innovation and retail operations.
Prior to founding Nextail, Joaquin was Head of European Logistics for Zara-Inditex, the world’s largest fashion retailer. In this role, he oversaw more than a thousand retail stores with over $10 billion in annual sales and led technical innovation for the company, creating solutions to manage product flow in high-volume flagship stores.
As an industrial engineer by trade, Joaquín has always been fascinated by improving the way things work. Upon entering the retail industry, he quickly observed many opportunities to transform traditional merchandising processes that prevented retailers from acting fast enough to meet customer demand. It was this inspiration to reinvigorate retail through advanced data and technology that Nextail was founded.
Today, in addition to leading Nextail, Joaquín is a frequent speaker at retail industry events and a lecturer in executive retail programs.