The solution improves the effectiveness of both organic and paid advertising strategies.
Maximize Google search performance with customer-centric product data
MOUNTAIN VIEW, Calif., March 13, 2024 (GLOBE NEWSWIRE) — Lily AI, (“Lily” or the “Company”), a retail technology platform specializing in AI solutions for retailers and brands, today announced the launch of its most comprehensive Search Engine Optimization (SEO) and Search Engine Marketing (SEM) e-commerce product attribution solution. The new capabilities, specifically developed for Sponsored Ads and Product Listings, enable Lily AI customers to significantly improve product discoverability and increase conversion rates resulting from their paid and organic search strategies.
According to Gartner, search engine volume is predicted to drop 25% by 2026 due to AI chatbots and other virtual agents. Gartner also reports that 82% of all desktop traffic to retailers is from organic and paid search, indicating retailers must make their paid and organic search activities work even harder as they face the double threat of their most lucrative acquisition channels shrinking and being forced to tailor their presence to AI chatbot intermediaries their shoppers will increasingly use.
“We know Google is committed to positive user experiences by providing relevant results at the right time yet continuous updates to their search algorithms and quality scores make it challenging for retailers and brands to navigate these updates and optimize their search efforts,” said Purva Gupta, Co-founder and Chief Executive Officer, Lily AI. “With the introduction of our latest capabilities for Sponsored Ads and Product Listings, our clients can now enjoy the benefits of human-centric product attributes outside of their own eCommerce site, empowering them to connect with the consumers they know the least about — the ones who haven’t previously purchased from them.”
Specifically, retailers and brands who leverage the Lily AI full funnel search solution can easily:
- Enrich Google Merchant Center (GMC) product data with human-centric attributes;
- Ensure products are discoverable via natural language search phrases;
- Match consumer purchase intent with Lily AI’s search-optimized product titles and descriptions, and;
- Drive SERP rankings by deploying Lily AI’s product copy on PDPs.
According to Forrester’s Nikhil Lai, “Because these [AI search] models are patterned on natural language, your content’s quality depends on its humanity. Ironically, the more closely your content’s syntax and sentiment resemble human speech, the more intelligible it is to AI chatbots.” Lily’s new SEO and SEM capabilities bring those human-centric terms to search listings. By adding the terms shoppers use to find products and improving titles and descriptions to help page ranking, more people will be able to discover, evaluate, and purchase the right product, no matter how they reach it.
“As we unveil our latest Google search capabilities, we are thrilled to help our clients reach and inspire desired audiences beyond their current site while simultaneously navigating rising acquisition costs,” said Ahmed Naiem, President and Chief Revenue Officer of Lily AI. “As our customers know, we are dedicated to driving growth for them every step of the way across their value chain; our ability to incorporate human-centric shopping terms in their search activities is another example of our ongoing commitment to help them stand out in a crowded market.”
About Lily AI
Lily AI is a female-founded retail AI company that empowers retailers and brands by bridging the gap between merchant-speak and customer-speak. Leveraging generative AI, computer vision, natural language processing, machine learning, and deep learning, Lily AI enhances shopping experiences by injecting human-centered language throughout the retail ecosystem. Interoperable with eCommerce, marketplace, and product management platforms, Lily AI maximizes existing technology investments to deliver upwards of a 9-figure revenue lift through improved product attribution and descriptions, enhanced discovery, and higher conversion.