TL;DR:
- AI is transforming retail, with a focus on customer-facing applications.
- AI helps retailers understand and serve customers better by interpreting their intent and preferences.
- Retailers are adopting AI to match shoppers with the perfect products, especially during the holiday season.
- AI enables the assignment of multiple customer-centric attributes to products, enhancing searchability.
- Trend-based product attributes, particularly popular among Gen Z and millennials, are crucial for success.
- Enriching product information with customer-centric language benefits various aspects of retail operations.
- Customers benefit from more accurate product searches, leading to increased sales.
Main AI News:
Artificial intelligence (AI) has had a remarkable year, and its transformative potential is becoming increasingly evident in the retail sector. While AI has long been used to streamline back-end operations like inventory management, the latest generation of AI technologies is now making waves in customer-facing applications. Despite AI being a top trending topic, many retailers have yet to fully harness these emerging solutions to gain deeper insights into and better serve their customers. However, those who have integrated AI to address specific business challenges are reaping substantial benefits for their bottom line.
AI encompasses various domains, including computer vision, machine learning, and natural language processing. During this holiday season, retailers have quickly adopted these proven AI solutions to connect online shoppers with the perfect gifts for their loved ones or themselves. AI proves particularly valuable in scaling personalized language for retail categories boasting extensive product catalogs, such as apparel, accessories, home goods, and beauty. It excels at deciphering shoppers’ intentions, understanding their unique styles and preferences, and aligning “customer speak” with the most relevant products.
Traditionally, retailers could only assign a limited number of attributes to a handful of products manually, typically ranging from 3 to 5 attributes. Assigning multiple attributes and trend-based themes for each item was virtually impossible to achieve manually. AI tools, however, have made it possible to scale these attributes across the entire product catalog effortlessly.
A prime example of the power of customer-centric attributes during the holidays lies in trend-based product descriptions. Words associated with the latest trends, spanning from macro trends to micro trends inspired by TikTok and Instagram, have a profound impact, especially among Gen Z and millennials. For instance, in anticipation of the releases of “The Little Mermaid” and “Barbie” films last summer, people were on the lookout for “Mermaidcore” and “Barbiecore”-inspired outfits, accessories, makeup, and decor. Shoppers explored these trends using phrases such as:
- 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
While some of these trends might be part of a retailer’s product taxonomy, many are momentary microtrends that may not be included. Enriching your catalog and e-commerce site with customer-centric product attributes, including trends, occasions, and styles, can be applied to more timely examples as well. During this season, individuals are shopping with specific occasions in mind, like the “office holiday party outfit” or the “New Year’s Eve dress.”
Gen Z shoppers may be searching for “edgy luxe NYE party outfits,” with interest in dark, velvety blazers and micro shorts. Millennials, on the other hand, might be looking for “comfy, unstructured sheer and shimmery” looks, inspired by the beloved Gilded Comfort trend. Sometimes, inspiration strikes even before customers realize what they’re searching for, whether it’s from a marketing email, an Instagram ad, or the latest TikTok trend (#TikTokMadeMeBuyIt).
The advantages of enriching product information with customer-centric language extend far beyond site search and SEO/SEM. It positively impacts the entire retail operation, from campaign development and item setup to allocation and demand forecasting.
Let’s be honest; most customers aren’t searching for “polyester spandex blend boyfriend fit sequined blazers” when preparing for holiday parties. However, many may be seeking “oversized sequin party jackets.” By attributing products with both of these terms and their variations, retailers enable customers to pinpoint the exact items they desire, ultimately leading to increased sales.
Conclusion:
The integration of AI in retail, particularly in understanding and responding to customer needs through language, marks a significant shift in the market. Retailers adopting AI-driven customer-centric approaches are likely to outperform competitors by delivering more personalized shopping experiences, resulting in increased sales and customer satisfaction. This trend underscores the importance of harnessing AI’s potential to remain competitive in the ever-evolving retail landscape.
