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How AI Boosts Holiday Sales with Customer-centric Language

artificial intelligence
AI in retail is just beginning to evolve.

AI has had a banner year. 

And while many in retail have been using machine learning for years to streamline and automate back-end functions like replenishment and inventory management, the new customer-facing applications of the next generation of AI technologies is just starting to take off. 

Yet even though AI is one of the year’s top trending topics, many retailers are still not utilizing these emerging AI solutions to the extent they could to better understand and serve their customers. However, the ones that are using AI to solve specific challenges in their business are seeing tremendous results to their bottom lines.

Of course, there’s more to AI than generative AI, such as computer vision, machine learning, and natural language processing. One of the quickest ways that retailers put these proven AI solutions to work this holiday season was in matching ecommerce shoppers with the perfect gifts for their friends, family, or themselves. 

AI is an ideal solution to scale personalized language for retail categories with thousands of SKUs, such as apparel, accessories, home goods, and beauty. For instance, AI can better interpret a shopper’s intent and understand their unique style and preferences by matching “customer speak” and every permutation of shopping term or search query, with the most relevant products. 

When retailers assign accurate customer-centric attributes to their catalog of products, shoppers have a much easier time finding everything they want. 

Without AI, retailers can perhaps at best assign 3 – 5 attributes to a handful of products. To do it properly—assigning multiple attributes and trend-based themes for each item—is quite frankly an impossible task to do manually. When AI tools are used, these attributes suddenly become scalable across the entire product catalog.

One example of particularly powerful customer-centric attributes leveraged during the holidays are the words associated with the latest trends. From the ever-popular macro trends to the world of TikTok and Instagram-inspired micro trends, trend-based product attributes are an enormous game changer, especially among Gen Z and millennials.

For example, leading up to both "The Little Mermaid" and "Barbie" film releases this past summer, many people were looking for “Mermaidcore” and “Barbiecore”-inspired outfits, accessories, makeup, and decor. While some people searched these trends by name, others were searching for items that can be described with phrases like: 

  • ocean blue shimmer eyeshadow 
  • girly pop prom dress
  • turquoise mermaid gown
  • aqua blue scalloped ruffle skirt
  • pearl-embellished beachy wall decor
  • hot pink ultra-feminine accessories

As a retailer, you may have some of those trends, and trend attributes or descriptions,  listed within your product taxonomy (that’s retailer-speak for “library of attributes”), but certainly not all of them (several are of-the-moment microtrends, after all!).

This practice of enriching your catalog and ecommerce site with customer-centric product attributes, like trends but also occasions and styles, can be applied to a more timely example as well. At this time of year, many people are shopping with a particular occasion in mind. They’re on the hunt for the classic “office holiday party outfit” or “New Year’s Eve dress.” 

We may see Gen Z shoppers searching for “edgy luxe NYE party outfits,” looking for matching dark, velvety blazers and micro shorts. Millennials may be looking for “comfy, unstructured sheer and shimmery” looks, based on their beloved Gilded Comfort trend. 

And even before the consumer knows what they want, inspiration can come from a marketing email, an Instagram ad, or the latest TikTok (hello #TikTokMadeMeBuyIt). 

The upside of enriching product information with customer-centric language isn’t limited to site search and SEO/SEM. In fact, it benefits the entire retail operation, from campaign development and item setup to allocation and demand forecasting.

Let’s face it . . . most of your customers aren’t preparing for holiday parties by searching for “polyester spandex blend boyfriend fit sequined blazers” but many are probably searching for “oversized sequin party jackets.” By attributing your products with both of these terms—and every variation in between—customers will pin-point the exact items they desire . . . and retailers will achieve their ultimate task—completing more sales. 

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