List of Lily AI Customers
Mountain View, 94040, CA,
United States
Since 2010, our global team of researchers has been studying Lily AI customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Lily AI for Personalization and Product Recommendations from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Lily AI for Personalization and Product Recommendations include: Macys, a United States based Retail organisation with 94189 employees and revenues of $23.01 billion, Tapestry, a United States based Retail organisation with 18600 employees and revenues of $6.67 billion, Bloomingdale's Inc., a United States based Retail organisation with 10000 employees and revenues of $1.00 billion and many others.
Contact us if you need a completed and verified list of companies using Lily AI, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Lily AI customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Bloomingdale's Inc. | Retail | 10000 | $1.0B | United States | Lily AI | Lily AI | Personalization and Product Recommendations | 2022 | n/a |
In 2022, Bloomingdale's Inc. deployed Lily AI in the Personalization and Product Recommendations category to enrich product metadata across its e-commerce catalog. The public report cited use of Lily AI's product attributes platform to target site search relevance, recommendation quality and paid advertising feeds in the United States.
The implementation centered on Lily AI's product attributes platform for automated attribute extraction, taxonomy normalization and metadata enrichment, aligning product records with standardized attribute sets to surface visual and semantic signals for search and recommendation models. Configuration work addressed attribute coverage gaps, SKU level tagging and feed enrichment workflows to improve discoverability across site search and Google and paid channels.
Operational scope emphasized e-commerce merchandising, digital marketing and search teams in the United States, with outputs consumed by site search, recommendation engines and marketing feed pipelines. Publicly cited outcomes included improved product discoverability for search, recommendations and advertising performance, reflecting a metadata driven approach to personalization and product recommendations using Lily AI.
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Macys | Retail | 94189 | $23.0B | United States | Lily AI | Lily AI | Personalization and Product Recommendations | 2022 | n/a |
In 2022, Macys implemented Lily AI to provide product attribute enrichment and AI driven product content optimization under the Personalization and Product Recommendations category, supporting e-commerce and marketing business functions. The engagement targeted e-commerce and marketing teams in the United States and focused on improving on site discovery and shopping ad performance through richer, customer centric product attributes.
The implementation centered on automated attribute extraction and normalization, catalog metadata enrichment, and content optimization for product titles, descriptions, and metadata to improve relevance for search and shopper facing merchandising. Lily AI was configured to generate customer centric attributes and map them into merchandising taxonomies to support personalization workflows and content syndication for shopping channels.
Operational coverage was limited to e-commerce and marketing functions within Macys in the United States, with the vendor reported customer list citing Macys in 2022 as a reference. The deployment emphasized catalog enrichment and continuous content pipelines aligned with existing marketing and merchandising processes rather than broad platform substitution.
The engagement aimed to boost impressions, clicks and conversions by making product attributes more customer centric, positioning Lily AI as the catalog intelligence layer for Macys within the Personalization and Product Recommendations domain.
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Tapestry | Retail | 18600 | $6.7B | United States | Lily AI | Lily AI | Personalization and Product Recommendations | 2024 | n/a |
In 2024, Tapestry partnered with Lily AI to enrich product attributes and optimize Google Search, site search, and SEM across its Coach, Kate Spade, and Stuart Weitzman brands. The Lily AI implementation targeted e-commerce and marketing operations in the United States and focused on improving product discovery across the company portfolio.
Implementation centered on product attribute enrichment and semantic tagging, using Lily AI to normalize taxonomy and augment SKU level metadata to support more relevant search and recommendation algorithms. Core functional capabilities included enhanced product metadata extraction, feed optimization for paid search, on-site search relevance tuning, and Personalization and Product Recommendations workflows aligned to merchandising rules.
Integrations focused on search and paid channels, tying Lily AI outputs into Google Search indexing, site search relevance layers, and SEM feed pipelines to improve query matching and ad relevance. Operational coverage spanned digital merchandising, e-commerce product catalogs, and marketing channels across Tapestry's brand portfolio in the United States.
Governance and operational ownership were aligned to e-commerce and marketing teams to embed enriched attributes into taxonomy and merchandising workflows, with phased rollout across brands. Per vendor reporting and public discussion at CommerceNext 2024, the collaboration drove high single to double digit lifts across SEO, SEM, and site search metrics.
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