AI Makes Retail Language More Accessible to Shoppers

As AI reshapes many industries, retailers are encouraged to leverage this technology to translate complex industry jargon into consumer-friendly language, according to recent research from Lily AI, a platform specializing in optimization.

Over the past 30 years, retailers have invested heavily in improving customer satisfaction through tailored product selections and personalized upselling. However, many still struggle to provide clear and relevant product descriptions that resonate with how consumers search and think.

Personalization in e-commerce remains a work in progress. Shoppers frequently find it difficult to locate desired products because descriptions often fail to align with their search terms or expectations.

The study by Lily AI highlights shifting shopper behaviors, outlines what retailers must do to keep pace, and shows how AI can usher in a new phase for online retail experiences.

Purva Gupta, CEO and Co-founder of Lily AI, emphasizes that despite efforts to curate high-quality product assortments, retailers and brands often miss out on sales opportunities by not fully optimizing product content.

“Clearer, more detailed product descriptions not only improve customer satisfaction but also drive sales and operational efficiency, both on customer-facing platforms and backend systems,” Gupta explained in an interview with E-Commerce Times.

As AI continues to influence online shopping, retailers need to harness its capabilities to enhance product content with accurate details that help consumers easily find and confidently purchase products.

“Retailers risk losing customer loyalty, brand reputation, and revenue without a solid foundation of relevant and precise product data,” Gupta warned.

Search Difficulties Impact Sales Growth

Despite technological advances, many consumers experience frustration when searching for products online, whether through search engines, social media, or e-commerce platforms.

Gupta shared findings revealing that 84% of shoppers may perform up to six searches before finding what they want, and 80% give up before completing a purchase. Additionally, nine out of ten shoppers often visit physical stores because online product information is insufficient to make a buying decision.

“In today’s competitive market, making it hard for consumers to find products online leads to lost sales and dissatisfied customers,” Gupta said.

The research also shows that different generations use varied channels to discover products. While Amazon is the primary starting point across age groups, Gen Z leans towards social media, Millennials favor large retail websites, and Baby Boomers and Gen X rely more on traditional search engines.

Uneven AI Adoption Challenges Retailers

Many retailers face challenges optimizing product content to align with how consumers search. Effective product descriptions must be consistent and tailored across multiple platforms, enabling accurate discovery regardless of the search method or channel.

Gupta explains that when product language is harmonized—for example, a “midnight French terry athleisure top” should appear in searches for “blue hoodie” on TikTok or “navy sweatshirt” on Google—retailers can reach a wider audience.

However, the adoption of AI-powered tools is uneven. About 40% of consumers reported using newer AI-driven search engines, making it crucial for retailers to optimize content for generative AI systems like Google AI, ChatGPT, or Perplexity.

Failing to do so risks declining organic traffic, lower sales, reduced brand visibility, and losing ground in AI-driven recommendations.

Bridging the Gap Between Consumer and Machine Language

Gupta points out a major problem: many product descriptions use technical merchant language that lacks consumer-friendly phrasing and context. This disconnect hampers AI’s ability to understand and recommend products effectively.

“When product content doesn’t speak the language of consumers or AI systems, shoppers turn to competitors,” she said.

Poor product content also negatively impacts advertising and conversion rates by reducing traffic and sales. Product Content Optimization (PCO) uses AI to close this gap by understanding diverse consumer search patterns and providing the most relevant product matches, no matter the platform or search method.

Addressing Consumer Language Barriers

PCO automatically enriches product data with terms that resonate with consumers, merchants, and AI algorithms, improving product visibility across search engines, social media, marketplaces, and AI-powered tools.

For instance, if a sweater labeled “Cardinal Luxe” doesn’t explicitly say “red cashmere,” PCO technology recognizes those connections and surfaces the product to shoppers searching with those keywords.

Gupta emphasizes that such optimization ensures products can be found even when exact matches don’t exist, resulting in more impressions and higher conversion rates.

Can AI Reduce Cart Abandonment?

Research shows that nearly 90% of shoppers visit physical stores because online product descriptions leave questions unanswered. Clear, concise product content can help reduce cart abandonment and returns by providing consumers with the information they need to make confident purchases online.

Survey respondents cited reasons for in-store purchases such as wanting to see or try items (52%), assess quality (48%), clarify fit (42%), insufficient details online (29%), or confusing descriptions (20%).

She also noted that 85% of shoppers would consider buying a similar product from another retailer if they can’t find what they want with their original brand or store choice.

Looking Ahead: AI’s Role in Retail’s Future

Gupta envisions AI transforming e-commerce through 2030 and urges retailers to prepare for these changes by adopting AI early and experimenting with new approaches.

She stresses the growing overlap between digital commerce and marketing, pointing out that product data is crucial to the success of both.

“Agentic AI is here to stay and will only improve. Retailers and brands must embrace AI to stay competitive and relevant,” Gupta concluded.

She also cautioned that achieving these benefits requires retailers to rethink their processes, emphasizing that optimizing product content and re-engineering workflows go hand in hand to fully leverage AI advancements.