AI Tools Retailers Can Use to Succeed This Shortened Holiday Shopping Season

The holiday season is the most successful and stressful period for retailers. Throughout the year, retailers monitor inventory levels, replenish stores and determine the correct price promotion equation. These tasks are just as important during the holidays — however, the way retailers complete them is different. Moreover, the margin for error is much smaller, especially this year.

The 2024 holiday shopping season will be shorter than usual, with Thanksgiving falling on Nov. 28, shortening the window between it and Christmas. This is a phenomenon that hasn’t happened since 2019.

This shorter window will affect assortment, pricing and promotion strategies. Likewise, despite the need for higher inventory levels (and seasonal products), retailers have limited space and must choose which inventory to prioritize. The supply chain also presents a significant challenge — specifically, how many products can one transfer in this year’s limited period?

In order to maximize this shortened holiday window and overcome these challenges, retailers should turn to artificial intelligence (AI) tools to enhance forecasting and labor management.

Digital Twins and Social Listening

One of the fundamental differences about this shorter holiday period is that the demand forecast won’t be the same as last year, nor will it be like 2019 (which was pre-COVID). As such, retailers must adjust demand forecasting, including assortment management, pricing, promotion planning, merchandising and supply chain management, to compensate for this shorter shopping window. Ultimately, they need to create a digital twin of a store and see how it works under the new conditions and handles new challenges. AI could be used across multiple components — e.g., to predict demand; find optimal combinations of assortment, pricing, promo, and shelf; model store efficiency; among others.

It's crucial that retailers gather data from as many sources as possible to feed their digital twin models. For example, retailers can use sales data from brick-and-mortar stores, e-commerce platforms, marketplaces, mall kiosks and other sales channels. A mix of historical and current data is also important. When historical data is less applicable, it’s important to include new data sources, such as social listening, and AI could be a great help there, too. Retailers can then input this wealth of data into their models to get more precise predictions, ensuring inventory is at the right levels to prevent stock-outs or overstocks.

Some AI tools can also be utilized to peek into the fluctuating preferences of the retailer’s target customers. These tools bolster forecasts with the latest information about what people want to buy and how they plan to adapt to the shorter holiday season.

Optimizing Labor Management

Another area where AI can be effective this year, especially during the holiday season, is staffing. During the holidays, retailers bring on seasonal workers, many of whom might be contractors, students or part-time workers unfamiliar with the products or store and warehouse processes. AI tools enable retailers to onboard and train these workers at scale. Likewise, some retailers provide their staff with AI applications to help them search for information about the latest products.

AI can also optimize workforce management. Demand and sales forecasts connect directly to labor requirements, and AI models, given the right data, can optimize labor distribution. Holidays likewise are hectic for employees who work longer hours late into the evening. Managers have to be mindful of changes to breaks and shifts for hourly workers. By infusing AI into this environment, retailers can allocate schedules and workloads appropriately, ensuring adherence to labor rules and regulations.

Additionally, AI tools — specifically generative AI — can lighten workloads and speed up the product launch process by automating product content creation. For example, generative AI can create a basic description for a new seasonal product, and then an employee can tweak that by hand for tone of voice, keywords, etc.

Ensuring a Successful AI Implementation

AI will add value across a retailer’s operations, from processes and departments to managers and employees. However, because retailers are such complex entities, it's impossible to simply “drop” AI into retail operations and expect immediate results. An AI implementation requires considerable expertise in data science, infrastructure, governance, change management, etc. These disciplines are not independent but highly interconnected.

Most retailers lack the in-house expertise to implement AI effectively, making it crucial to partner with a third party. The right partner will bring proven, diverse technical and retail experience and recognize that AI is not a one-time setup but a continuous journey, requiring active support for sustained success this holiday season and beyond.

Martin Ryan is vice president of retail at EPAM Systems, Inc., a provider of digital engineering, cloud and AI-enabled transformation services, and a leading business and experience consulting partner.

Vitaly Vavilov is head of consumer and retail analytics at EPAM Systems.