# Lily AI

> Lily AI is the product intelligence company behind Lily Max, an agentic engine that enriches retail product catalogs and proves lift with controlled tests across Google Ads, Meta Ads, AI shopping assistants and onsite search. Founded 2015. CEO: Purva Gupta.

## Company
- [About Lily AI](https://www.lily.ai/about): Lily AI is the product intelligence company behind Lily Max, an agentic engine that enriches retail product catalogs and proves lift with controlled tests across Google Ads, Meta Ads, AI shopping assistants and onsite search.
- [In the press: news, funding, and announcements](https://www.lily.ai/press): Lily AI in the press: funding announcements, product news, and media coverage across The New York Times, Bloomberg, Forbes, WWD, Ad Age, and more.
- [Careers](https://www.lily.ai/careers)
- [Purva Gupta](https://www.lily.ai/authors/purva-gupta): Co-founder and CEO. Purva Gupta is the co-founder and CEO of Lily AI, the product intelligence company behind Lily Max. She writes about product data, controlled testing, and how AI surfaces decide which products shoppers see.

## Product
- [How Lily Max works](https://www.lily.ai/how-it-works): See how Lily Max agents find product-data gaps, generate AI-ready enrichments, run controlled tests, and deploy the winners across every surface AI sells on.
- [Pricing](https://www.lily.ai/pricing): Lily pricing scales with your catalog, channels, and ad spend. Every plan includes matched-spend testing so you only scale what's proven to lift revenue.
- [Google Ads Feed Optimization](https://www.lily.ai/google-ads): Optimize your Google Merchant Center feed for Shopping, Performance Max, and Demand Gen. Product-led paid performance, measured against a control.
- [Meta Ads Catalog Optimization](https://www.lily.ai/meta-ads): Optimize your Meta Commerce Manager catalog for Advantage+ catalog ads, retargeting, and prospecting across Facebook and Instagram. Measured against a holdout.
- [AI Discovery & Agentic Commerce](https://www.lily.ai/ai-discovery): Make your products legible to AI. Optimize feeds, schema, and bot-facing content so answer engines and shopping agents can understand, cite, and recommend them.
- [Onsite Search & PDP Optimization](https://www.lily.ai/onsite): Optimize PDP copy, onsite search, filters, and facets so shoppers find and buy on the site you own. Richer product data, measured against a control.
- [Lily Max for Enterprise](https://www.lily.ai/enterprise): One product intelligence engine across every AI commerce surface. Built for catalog scale and complex verticals, and proven with controlled tests.
- [Lily Max for Agencies & Partners](https://www.lily.ai/agencies): Bring product intelligence to every client. Manage catalogs in one place, white-label the engine, and grow accounts with controlled-test proof of lift.

## Topics
- [Product feed optimization](https://www.lily.ai/topics/product-feed-optimization): Product feed optimization is the work of improving the product-language record (titles, attributes, descriptions and taxonomy) that Google Shopping, Meta Advantage+, onsite search and AI assistants all read before deciding whether to show your product.
- [Product data: attributes, taxonomy and enrichment](https://www.lily.ai/topics/product-data): Product data is the structured record of attributes, taxonomy and enriched descriptions that makes a catalog legible to the search engines, ad platforms and AI agents that decide what shoppers see.
- [AI discovery and agentic commerce](https://www.lily.ai/topics/ai-discovery): AI discovery and agentic commerce cover the surfaces where an AI assistant or agent, rather than a person, reads product data to decide which products to recommend, compare or buy.
- [Proof: controlled tests and case studies](https://www.lily.ai/topics/proof): Proof means measured lift against a control: matched-spend A/B tests and holdouts that separate what a change to product data caused from what would have happened anyway.

## Guides
- [Agentic commerce: what it is, what changed in 2026, and what a brand actually has to do](https://www.lily.ai/blog/agentic-commerce): Agentic commerce is AI agents buying on a shopper's behalf. What changed in 2026, what an agent reads from your catalog, and what to fix before Q4.
- [Does feed optimization increase sales? The anatomy of a controlled test](https://www.lily.ai/blog/does-feed-optimization-increase-sales): Does feed optimization increase sales? Yes, against a control. Get the full test design: matched spend, 28-day holdout, difference-in-differences.
- [How AI Shopping Assistants Actually Pick Which Products to Recommend](https://www.lily.ai/blog/how-ai-shopping-assistants-pick-products): AI shopping assistants retrieve before they rank. See what each surface reads from your product record, and which missing attributes disqualify you.
- [What actually goes in Google Merchant Center conversational attributes](https://www.lily.ai/blog/merchant-center-conversational-attributes): What actually goes in Google Merchant Center conversational attributes: worked before-and-after values for apparel and home, plus where to mine them.
- [Merchant Center suspended for misrepresentation: the checklist, in the order we find them](https://www.lily.ai/blog/merchant-center-misrepresentation-suspension): Merchant Center suspended for misrepresentation? Work this checklist in the order we find them, catch every mismatch, and appeal once with the whole fix.
- [Product attributes: which ones each discovery surface reads, and what a good one looks like](https://www.lily.ai/blog/product-attributes-101): Which product attributes each discovery surface reads, what a well-formed value looks like, and the 2026 Merchant Center fields to fill in first.
- [Product Data Enrichment: What It Means When the Machines Are the Reader](https://www.lily.ai/blog/product-data-enrichment): Product data enrichment is not filling empty fields. Get the working definition, the four readers, the boundary with PIM, and a way to measure lift.
- [Product feed optimization: what it is, what actually moves revenue, and how to prove it](https://www.lily.ai/blog/product-feed-optimization): Product feed optimization is a vocabulary problem. The three layers, the eight changes that move revenue, and how to prove the lift with a control.
- [Product taxonomy: where a product sits, and which queries it is eligible for](https://www.lily.ai/blog/product-taxonomy): A product taxonomy decides which queries your catalog is eligible for. Learn to map it, structure it and maintain it across search, Shopping and AI.
- [The Role of Product Content in AI Search and Discovery](https://www.lily.ai/blog/the-role-of-product-content-in-ai-search-and-discovery): Product discovery is experiencing its biggest shift since digital commerce began. This report gives retailers a framework for structuring product content so generative engines can surface it.
- [The Readiness Gap: Why 70% of Shoppers Are Ahead of Retailers in AI Commerce](https://www.lily.ai/blog/the-readiness-gap-why-70-of-shoppers-are-ahead-of-retailers-in-ai-commerce): Shoppers are adopting AI-powered shopping faster than retailers can adapt. This report reveals how consumers use AI to search, compare, and buy, and what brands must do to stay visible.
- [5 Ways Smarter Product Content Can Boost Your Google Ads ROI This Holiday Season](https://www.lily.ai/blog/5-ways-smarter-product-content-can-boost-your-google-ads-roi-this-holiday-season): Holiday 2025 is shaping up to be one of the most competitive seasons on Google, where performance depends less on keyword strategy than on how well Google can understand what you sell.
- [Product Discovery Disrupted: From SEO to GEO and Beyond](https://www.lily.ai/blog/product-discovery-disrupted-from-seo-to-geo-and-beyond): See why AI disrupted search and shopping for the better, and how to succeed in the new world of AI-powered search and shopping across paid, organic, and owned on-site.
- [What is GEO vs SEO? Retail FAQs](https://www.lily.ai/blog/geo-vs-seo-for-retail-and-shopping-faqs): Ask 10 CMOs whether they should be concerned about GEO and you will get 10 different answers. Here are the most common questions about generative engine optimization, unpacked.
- [What is Product Content Optimization? 3 Things to Know](https://www.lily.ai/blog/what-is-product-content-optimization-3-things-to-know): In an AI-dominated retail world, basic product copy and bare minimum product data no longer cut it. Three things every retailer, brand, and agency needs to know about product content optimization.
- [The Search for Smarter Shopping: The Power of Product Content](https://www.lily.ai/blog/the-search-for-smarter-shopping-the-power-of-product-content): Findings from a consumer shopping survey conducted by Lily AI in January 2025, on the heels of the 2024 holiday season, assessing consumer sentiment toward online search and discovery.
- [A-Z Glossary: Key Concepts in AI-Powered Search, Commerce, and Advertising](https://www.lily.ai/blog/a-z-glossary-defining-key-concepts-in-ai-powered-search-commerce-and-advertising): Do you know your product attribution from your measurement attribution? An A-Z glossary of product attributes and content enrichment, AI search and discovery, measurement, and agentic AI.
- [How AI Connects With Consumers Shopping for the Holidays . . . Wherever They Are!](https://www.lily.ai/blog/consumers-shopping-for-the-holidays): Economic uncertainty and a shorter holiday season make 2024 feel faster-paced and unpredictable. Retailers cannot just remind holiday shoppers they exist; they have to inspire them.
- [The Inaugural Retail AI Index: Celebrating the Top 100 Brands and Retailers](https://www.lily.ai/blog/retail-ai-index-100-brands-retailers): The inaugural 2024 Retail AI Index, completed with Radii Group, ranks the top 100 brands and retailers and shows how AI is visibly reshaping apparel, footwear, beauty, and home.
- [When Is the Right Time to Implement Product Content Optimization for Descriptions, Attributes, and Metadata?](https://www.lily.ai/blog/when-is-the-right-time-to-invest-in-product-content-optimization): It is always the right time to improve your product data. But re-platforming, piloting, or building in-house can make it feel otherwise, so here is a plan for every stage.
- [Report: How AI Bridges the Retail Consumer Expectation Gap](https://www.lily.ai/blog/report-how-ai-meets-retail-consumer): Our report with RETHINK Retail surveyed over 1,000 North American consumers across fashion, home, and beauty to address the gaps between consumer expectations and what retailers deliver.
- [C-Suite Questions About AI Answered](https://www.lily.ai/blog/c-suite-questions-about-ai-answered): 55% of retail executives say they’ll invest in AI for marketing and 39% to enhance customer experiences. Answers to the cost, technology, and results questions the c-suite asks most.
- [How to Fast-Track AI Evaluation & Onboarding with Your Business Technology Team](https://www.lily.ai/blog/business-technology-ai-eval-onboarding): When implementing AI, effective collaboration with your Business Technology team is critical. How to convey business impact, ease of set-up, and high safety standards from the onset.
- [How to Effectively Co-Champion Technology Investments with Your Data & Analytics Business Partners](https://www.lily.ai/blog/win-data-analytics-experts-lily-ai): Lily AI can significantly augment decision-making and operational efficiency, but championing it means conveying that potential to data and analytics professionals from the onset.
- [Trend Attribution 101: Capitalizing on Cycles Sooner](https://www.lily.ai/blog/trend-attribution-101-capitalizing-on-cycles-sooner): It’s not enough to identify a trend. A look at the fads, mainstream, and classic trend cycles, and how AI-powered trend attribution makes current trends actionable today.
- [Thrift the Look with Lily AI’s Fashion Product Attribution](https://www.lily.ai/blog/thrift-the-look-with-lily-ais-fashion-product-attribution): Online thrift shopping keeps growing, so for National Thrift Shop Day we’re sharing our top tips for making the most of resale in retail.
- [The Top 3 Tips for Transforming Product Discovery](https://www.lily.ai/blog/the-top-3-tips-for-transforming-product-discovery): Even with all the right products, you have a very real problem if shoppers can’t locate them. Our top three tips for transforming online product discovery.
- [6 Steps to E-Commerce Site Search That Converts](https://www.lily.ai/blog/6-steps-to-ecommerce-site-search-that-converts): When shoppers type a specific term into a retailer’s search bar, they too often meet irrelevant or blank results. This guide covers the challenges and six steps to better on-site search.
- [The Top 6 Tips for Improving Site Search](https://www.lily.ai/blog/the-top-6-tips-for-improving-site-search): Search is where modern retail e-commerce begins. A look at the most common on-site search challenges, and a preview of our top six tips for overcoming them.
- [The Step-By-Step Guide to Using Enhanced Product Attribution Data](https://www.lily.ai/blog/the-step-by-step-guide-to-using-enhanced-product-attribution-data): Retailers have underinvested in a critical area: their own product data. This guide covers seven ways to elevate the customer experience with AI-powered product attribution.
- [How Better Website Navigation Can Improve Your Customer Experience and Sales](https://www.lily.ai/blog/how-better-website-navigation-can-improve-your-customer-experience-and-sales): The average webpage visit lasts less than a minute. Whether you’re planning a new site or optimizing an existing one, here’s how to turn browsers into buyers with clear navigation.

## Proof
- [How a fast-growing performance apparel brand turned product data into a 7.3% revenue lift on Google Shopping](https://www.lily.ai/case-studies/performance-apparel-google-shopping-revenue-lift): A controlled 26-day Google Shopping test — with no change to bids or budget — drove a revenue lift confirmed causal with difference-in-differences analysis.
- [How a global prestige beauty company turned product content into cross-channel performance and AI-recommendation visibility](https://www.lily.ai/case-studies/prestige-beauty-cross-channel-ai-visibility): Controlled tests across a portfolio of makeup and skincare brands showed that enriching product content lifted revenue and efficiency on Google and Meta — and improved how often the brands surfaced in AI product recommendations.
- [How a global home furnishings retailer grew Google Shopping revenue 5.7%, while clicks went down](https://www.lily.ai/case-studies/home-furnishings-google-shopping-revenue-lift): A controlled 28-day A/B test in Google Merchant Center showed that enriching product data — with no change to bids or budget — drove more revenue from better-qualified traffic, even as clicks fell.
- [How A.L.C. boosted full-catalog product discovery on Google](https://www.lily.ai/case-studies/alc-full-catalog-discovery-on-google): A.L.C. enriched its product attributes with Lily AI to expand discoverability across its full catalog, on-site and on Google, driving a major lift in non-branded search and net sales.
- [thredUP increases sell-through by 15% with enriched product data](https://www.lily.ai/case-studies/thredup-sell-through-15-percent): AI-driven deep tagging from Lily AI gave thredUP shoppers two to three times as many ways to search and discover its single-SKU inventory, lifting sell-through by 15%.
- [A global luxury retailer increases relevant results for descriptive searches by up to 30x](https://www.lily.ai/case-studies/luxury-retailer-descriptive-search-30x): Over half of this retailer's on-site searches were attribute-heavy, long-tail queries its manual attribution couldn't serve. Lily AI's consumer-centric attributes increased relevant results by up to 30x.
- [A large multi-brand retailer boosts product discovery, projecting a $22M revenue increase](https://www.lily.ai/case-studies/multi-brand-retailer-22m-product-discovery): Richer Lily AI attribution lifted on-site discoverability 8.5% and search-driven demand 3.3% for a large multi-brand specialty retailer, projecting to a $22M revenue increase across brands.
- [Lily AI recommendations increase RPV by 0.65%, driving $20-30M in incremental demand](https://www.lily.ai/case-studies/multi-brand-retailer-rpv-recommendations): Layering Lily AI's granular attributes onto an existing Certona recommendation engine produced more relevant recommendations, lifting revenue per visit and order size for a $20-30M incremental-demand projection.
- [Lily AI demand forecasting drives 7-8 digit revenue lift with accuracy at scale](https://www.lily.ai/case-studies/demand-forecasting-accuracy-at-scale): Lily AI's visual-similarity models replaced manual proxy-product guesswork, cutting a retailer's forecasting cycle from three months to one and projecting a $7-48M topline revenue lift.
- [How a luxury home brand boosted sales from Shopify site search and Google search](https://www.lily.ai/case-studies/luxury-home-brand-shopify-and-google): A top luxury home furnishing brand enriched its Shopify product content and GMC feed with Lily AI, lifting on-site revenue per visit, Google impressions, and ad clicks, with a ROAS boost two weeks after going live.
- [Tapestry boosts traffic and sales from Google Search with Lily AI](https://www.lily.ai/case-studies/tapestry-google-search-discovery): At CommerceNext 2024, Tapestry (parent of Coach) and Lily AI showed how enriching product attributes with customer-centric language drove high-single and double-digit lifts across SEM, SEO, and Site Search.
- [From experimentation to full AI vibes at Rue Gilt Groupe](https://www.lily.ai/case-studies/rue-gilt-groupe-full-ai-vibes): A CommerceNext 2025 conversation on putting AI to work across the Rue Gilt Groupe portfolio.
- [From SEM to GEO: how Merrell connects with Gen Z and millennials](https://www.lily.ai/case-studies/merrell-sem-to-geo): How Merrell is evolving from search-engine to generative-engine optimization.
- [How Bloomingdale's makes site search convert with enriched product data](https://www.lily.ai/case-studies/bloomingdales-site-search-convert): Bloomingdale's on lifting on-site search conversion with richer product attributes.
- [“AI is here, now what?” with Tapestry and Lily AI](https://www.lily.ai/case-studies/tapestry-ai-is-here-now-what): Tapestry and Lily AI on turning AI ambition into measurable retail results.
- [How J.Crew uses AI to delight customers and power sales growth](https://www.lily.ai/case-studies/jcrew-ai-delight-customers): J.Crew on using product intelligence to improve discovery and growth.

## FAQs
- [All FAQs](https://www.lily.ai/faqs): Answers about Lily's products, pricing, coverage, implementation, security, and the outcomes customers report.

## Optional
- [A buying standard for AI commerce](https://www.lily.ai/blog/a-buying-standard-for-ai-commerce): Four questions to ask before you fund any AI marketing tool. Every retail budget now carries an AI line item, and almost nothing on it arrives with a way to know whether it worked. Here's the standard, and the one shortcut to remember it: would it survive a finance review?
- [The most expensive thing in retail right now](https://www.lily.ai/blog/the-most-expensive-thing-in-retail-right-now): Brands are pouring attention into a future that isn't generating revenue yet, while the surfaces actually producing revenue today get treated like settled infrastructure. A preview of my CommerceNext session with Ken Pilot and Noam Paransky.
- [You don't have an agency problem. You have an input problem.](https://www.lily.ai/blog/you-dont-have-an-agency-problem): A CMO fired three paid agencies in two years and decided you can't find a good one anymore. The real problem was upstream: the old agency edge has been commoditized, and the leverage has moved to the inputs only the brand controls.
- [Google says conversational attributes are optional. History says otherwise.](https://www.lily.ai/blog/conversational-attributes-optional-history-says-otherwise): Mobile-friendly, page speed, structured data: Google introduced each as optional, and each became the price of entry. Conversational attributes, its new AI-shopping feed fields, look like the next one.
- [It always turns out to be a feed](https://www.lily.ai/blog/it-always-turns-out-to-be-a-feed): OpenAI spent a year pitching conversational shopping, then quietly rebuilt something that looks a lot like Google Merchant Center. Every platform that monetizes shopping ends up needing the same thing first: a feed.
- [Google may have just created a billion-dollar optimization market](https://www.lily.ai/blog/google-created-a-billion-dollar-optimization-market): AI visibility struggled to attract serious budget for a simple reason: nobody funds what they can't measure. With Google's new AI Performance Insights, it's measurable now. So the money moves.
- [Automation commoditized everything except your feed](https://www.lily.ai/blog/automation-commoditized-everything-except-your-feed): Google spent five years making paid search dramatically easier to run, which is exactly why it keeps getting more expensive to win. A classic Jevons paradox: automation standardized the edge brands used to build by hand. The one input it can't commoditize is your product feed.
- [Google just told the market AI content isn't the moat. Structured product data is.](https://www.lily.ai/blog/google-ai-content-isnt-the-moat-structured-data-is): Google's official guide on optimizing for AI search quietly dismissed the llms.txt-and-content-variants playbook a whole vendor category was built on. For retailers, the moat isn't AI-optimized content. It's structured, machine-readable product data.
- [$80M in incremental revenue last month, one optimization: the feed](https://www.lily.ai/blog/80m-incremental-revenue-one-optimization-the-feed): Four 28-day Google Ads tests across a luxury house, a US department store, a global home retailer, and an athletic-wear brand. Every lift came from one place: the Google Merchant Center feed.
- [Stripe is building the rails. Your product data decides who wins on them.](https://www.lily.ai/blog/stripe-rails-product-data-decides-who-wins): A day at Stripe Sessions made one thing unmistakable: agentic commerce has moved from interesting future to build now. Stripe is building the payment rails. The brands that win on them will already have their product data structured for agents.
- [Brands are paying for bad product data twice now](https://www.lily.ai/blog/brands-pay-for-bad-product-data-twice): Adobe says 34% of retail product pages can't be properly read by AI, even as the AI channel converts 42% better. The cost of thin product data used to be invisible. Answer engines just made it impossible to ignore.
- [NRF 2026 Takeaways: Retail Is Being Rewired Around AI Discovery](https://www.lily.ai/blog/nrf-2026-takeaways-retail-is-being-rewired-around-ai-discovery): NRF 2026 made clear that AI is no longer a nebulous concept: it is already reshaping how retail teams approach discovery, personalization, and growth. Here is what stood out and why it matters.
- [From Experimentation to Expectation: How AI Shopping Normalized Faster Than Retail Prepared](https://www.lily.ai/blog/from-experimentation-to-expectation-how-ai-shopping-normalized-faster-than-retail-prepared): Over the course of 2025, AI-powered shopping moved from cautious experimentation to everyday utility, shifting how consumers search, discover, and decide what to buy.
- [6 Things Every Retailer Needs to Know About Agentic Shopping Right Now](https://www.lily.ai/blog/6-things-every-retailer-needs-to-know-about-agentic-shopping-right-now): Consumers no longer type short keywords; they express intent in full sentences and AI agents reason through them. Six takeaways on the shift from ranking to reasoning.
- [The Agentic Wake-Up Call for Retail: Why CMOs and CDOs Must Prioritize Product Data Now](https://www.lily.ai/blog/the-agentic-wake-up-call-for-retail-why-cmos-and-cdos-must-prioritize-product-data-now): Andrej Karpathy called this the “decade of agents.” For retail CMOs and CDOs it is a runway, not a buffer: agents only perform atop rock-solid, machine-readable product data.
- [The Agentic Commerce Era Has Officially Begun](https://www.lily.ai/blog/the-agentic-commerce-era-has-officially-begun): Walmart has announced a partnership with OpenAI that lets shoppers discover and buy directly through ChatGPT. Product content optimization is no longer operational; it is existential.
- [Every Discovery Is AI Discovery](https://www.lily.ai/blog/every-discovery-is-ai-discovery): The way you search on Instagram isn’t the way you search on Amazon. Each query describes the same goal in a different language—every platform speaks its own dialect of intent.
- [In the Instant Checkout Era, Product Content Is Everything](https://www.lily.ai/blog/in-the-instant-checkout-era-product-content-is-everything): Everyone’s buzzing about OpenAI’s Instant Checkout, but the real winners won’t be the ones with the flashiest tech stack. They’ll be the brands that finally fix their product content.
- [7 Hot Takes on AI from Female Execs & Founders at Cannes Lions](https://www.lily.ai/blog/7-hot-takes-on-ai-female-executives-and-founders-at-cannes-lions): At Cannes Lions this year, Lily AI CEO Purva Gupta joined a panel of women founders to discuss the AI ecosystem in advertising and media. Here are 7 hot takes from the session.
- [Q2 2025 Retail Trends: 3 Opportunities for Google, Meta, SEO, AIO, AEO & GEO](https://www.lily.ai/blog/q2-2025-retail-trends-3-opportunities-for-google-meta-seo-aio-aeo-geo): Q2 2025 retail data across digital advertising and organic search was marked by both ups and downs. Synthesizing the quarter reveals three golden opportunities for marketers right now.
- [AI Slop vs Creme-of-the-Crop: Optimizing Product Content Generation with AI](https://www.lily.ai/blog/ai-slop-vs-creme-of-the-crop-optimizing-product-content-generation-with-ai): AI slop is low-quality, filler-heavy content generated with AI, and it is flooding the digital landscape. Why it matters for retail, and how to reach the creme of the crop instead.
- [5 Times Google and Meta Disrupted Organic Traffic & SEO, and What’s Next for Retail](https://www.lily.ai/blog/5-times-big-tech-disrupted-organic-traffic-seo-and-whats-next-for-retail): Brands are seeing 30% drops in organic traffic as AI Overviews fuel zero-click search. A look back at five times big tech disrupted SEO, and three predictions for retail.
- [3 Ways GEO vs SEO Tactics Converge, and the Role of Product Content Optimization for Retailers](https://www.lily.ai/blog/3-ways-geo-vs-seo-tactics-converge-and-the-role-of-product-content-optimization-for-retailers): Retail executives keep asking how different GEO and AEO really are from traditional SEO. The answer is complicated, but content is where the two converge most tightly.
- [Lily AI Launches Product Content Optimization for SEO, AEO & GEO](https://www.lily.ai/blog/lily-ai-launches-product-content-optimization-for-seo-aeo-geo): Lily AI has launched a new solution built for the realities of SEO and GEO in 2025, automatically enriching, standardizing, and optimizing product content across ecommerce websites.
- [Retailers, Is Your Product Content Ready for GEO?](https://www.lily.ai/blog/retailers-is-your-product-content-ready-for-geo-heres-why-it-needs-to-be): Generative search is rewriting the rules of SEO right before our eyes. Winning now means being included in the answer itself, with accurate, on-brand, consumer-relevant information.
- [What Do Retailers Need to Know About Google AI Mode’s Query Fan-Out Technique and Thematic Search?](https://www.lily.ai/blog/what-do-retailers-need-to-know-about-google-ai-modes-query-fan-out-technique-and-thematic-search): Google's AI Mode and its thematic search patent threaten keyword-based SEO, but they also open a pivotal opportunity for retailers who invest in richer, consumer-centric product data.
- [What Do Marketers Need to Know About Google’s “AI Mode”?](https://www.lily.ai/blog/what-marketers-need-to-know-about-googles-ai-mode-released-at-i-o-2025): At Google I/O 2025, Google unveiled “AI Mode,” a conversational search experience now live for all U.S. users. Is it revolution or evolution, and what does it mean for SEO and SEM?
- [People Still Matter: Why Humanity Must Remain at the Heart of Retail’s AI Revolution](https://www.lily.ai/blog/people-still-matter-why-humanity-must-remain-at-the-heart-of-retails-ai-revolution): Technology should not be a shortcut to workforce reduction. It should be a catalyst to reimagine and elevate the work that only humans can do in retail.
- [Details Matter: How Product Discovery In the Age of AI and GEO is Evolving for Home Decor Retailers](https://www.lily.ai/blog/details-matter-how-product-discovery-in-the-age-of-ai-aeo-and-geo-is-evolving-for-home-decor-retailers): Finding home decor online shouldn’t feel like a chore. A survey of 2,081 U.S. consumers reveals what today’s buyers want and how the right details get a product found first, then sold.
- [What Are the New SEO Strategies for the AI Era of GEO, AEO, and Agentic Search and Shopping?](https://www.lily.ai/blog/winning-seo-strategies-for-the-ai-era-of-geo-aeo-and-agentic-ai): Bain estimates companies are seeing a 15% to 25% reduction in organic web traffic across industries. Where did the traffic go, and what does winning search look like now?
- [Advertising’s Blind Spot: The Role of Product in Audience Targeting and Personalization](https://www.lily.ai/blog/advertisings-blind-spot-the-role-of-product-in-audience-targeting-and-personalization): For all the advertising industry's focus on the consumer and personalization, there is a glaring blind spot: the personalization equation is equal parts consumer and product.
- [AI Training Data: Why It’s GIGO When Building Next Generation Frontier Firms](https://www.lily.ai/blog/ai-training-data-why-its-gigo-when-building-next-generation-frontier-firms): Microsoft’s research introduces “Frontier Firms” — organizations restructured around humans and AI agents working side by side. But garbage in still means garbage out.
- [From Vibe Coding to Vibe Marketing and Content Optimizing](https://www.lily.ai/blog/from-vibe-coding-to-vibe-marketing-and-content-optimizing): Anthropic expects AI to write 90% of its code and Shopify wants proof AI can’t do a job first. Vibe coding captures a cultural shift now reaching retail product content.
- [The Search for Smarter Shopping Continues: New Consumer Shopping Research Unveils Product Content Gaps](https://www.lily.ai/blog/the-search-for-smarter-shopping-continues-new-consumer-shopping-research-unveils-product-content-gaps): After the 2024 holiday season, Lily AI surveyed over 2,000 U.S. shoppers to answer one question: has AI made shopping better? Here are the highlights, plus the full infographic.
- [Lily AI’s Winter 2025 Release Is Here](https://www.lily.ai/blog/see-whats-new-lily-ais-winter-2025-release): Lily AI’s Winter 2025 release brings a suite of advanced features that transform how retailers optimize product catalogs for discoverability and conversion across every channel.
- [Tapestry Exec: Saying No to AI is Like Saying ‘No, We Don’t Like Money’](https://www.lily.ai/blog/tapestry-exec-saying-no-to-ai-is-like-saying-no-we-dont-like-money): At the SJ Fall Summit, Tapestry's SVP of Global Digital Product & Omnichannel Innovation opened with a mic-drop moment: saying no to AI is like saying “No, we don't like money.”
- [AI Improving Search, Naturally, and Other Takeaways from Legends of Commerce Hosted by Coresight Research](https://www.lily.ai/blog/ai-improving-search-naturally-and-other-takeaways-from-legends-of-commerce-hosted-by-coresight-research): On December 3rd, 2024, retail leaders gathered during the peak of Cyber Week at Legends of Commerce to discuss the hottest topics in retail today. Was AI on the agenda? AI-bsolutely!
- [How AI Can (really) Deliver Hyper-Relevant Experiences: AI in Retail Leaders Podcast](https://www.lily.ai/blog/how-ai-can-really-deliver-hyper-relevant-experiences-ai-in-retail-leaders-podcast): Lily AI president Ahmed Naiem joined AiR host Matthew Smith for a discussion on how artificial intelligence is reshaping the retail industry.
- [Vibe Shift: Elevating Shopping Ads with AI-Powered Natural Language Search](https://www.lily.ai/blog/vibe-shift-elevating-shopping-ads-with-ai-powered-natural-language-search): In this Live Demo recorded at SMX Next, Lily AI demoed our product attributes platform and no-code GMC integration that enriches product catalogs to boost shopping ad performance.
- [The AI-Fueled Vibe Shift Happening in Product Search](https://www.lily.ai/blog/the-ai-fueled-vibe-shift-happening-in-product-search): In our SMX Next demo session we explored how retailers can navigate an evolving product search landscape where consumers are no longer confined to traditional search engines.
- [Lily AI Unveils Its No-Code Product Attributes Platform](https://www.lily.ai/blog/lily-ai-unveils-its-no-code-product-attributes-platform): The next generation of the Lily AI product attribute platform is now available. With the Lily app, retailers and brands get end-to-end control over attribute management and workflows.
- [Start Harnessing Natural Language Search to Optimize Google Ad Performance](https://www.lily.ai/blog/start-harnessing-natural-language-search-to-optimize-google-ad-performance): Google Shopping Ads are perhaps a retail marketer's most powerful weapon, and optimizing them with AI makes ads even more powerful. Here's how to operationalize natural consumer language.
- [AI Index Deep Dive: Top 10 Fashion Brands](https://www.lily.ai/blog/retail-ai-top-10-fashion-brands): A peek at the top 10 fashion brands in the 2024 Retail AI Index, and the innovative ways they use AI to serve customers, boost personalization, and enhance internal processes.
- [Partner Spotlight: Algolia](https://www.lily.ai/blog/partner-spotlight-algolia): Algolia is the leader in search, and horizontal AI search solutions like Algolia work best when integrated with vertical AI search solutions like Lily AI. It's 1+1=5.
- [From Y3K to Indie Sleaze: Brat Summer’s 4 Key Fashion Trends](https://www.lily.ai/blog/brat-summer-fashion-trends-indie-sleaze-y3k): Charli XCX’s brat is a critical and commercial hit, and social media has run with it. Several of today’s hottest fashion trends now fall squarely into the brat summer aesthetic.
- [How to Harness the Natural Language of the Customer to Dominate The Present and Future of Search: Part 3](https://www.lily.ai/blog/natural-language-dominate-search): AI is changing the way people search and shop. Part 3 of our series on why rich product attributes in the language of the customer are critical to surviving and thriving.
- [Why Product Attributes Are Key to Dominating Search on Google, and Beyond: Part 2](https://www.lily.ai/blog/why-product-attributes-are-key-to-dominating-search-on-google-and-beyond-part-2): Search is changing thanks to AI, and almost all eyes are on Google. A look at the shifting search landscape and the evolving search and shopping habits behind it.
- [Why Product Attributes Are Key to Dominating Google Shopping Ads: Part 1](https://www.lily.ai/blog/product-attributes-google-product-listing-ads): The ways people speak and shop evolve every day, and brands must keep up. How to nail customer-centric product attributes to connect with shoppers via Google Shopping Ads.
- [Partner Spotlight: Bloomreach](https://www.lily.ai/blog/lily-ai-partner-bloomreach): Both Bloomreach and Lily AI are leaders in connecting consumers to products, so it's no wonder we have partnered to enhance ecommerce product discoverability.
- [Hot 2024 Summer Trends: Athleisure & Americana-Inspired Fashion Product Attributes](https://www.lily.ai/blog/athleisure-fashion-product-attributes): Retailers who sell athleisure can optimize product listings with athleisure-inspired attributes ahead of the 2024 Summer Games. A look at the season's hottest athletic-inspired trends.
- [Partner Spotlight: Microsoft](https://www.lily.ai/blog/microsoft-azure-marketplace-ai): For two years Lily AI has been part of the Microsoft Partner Network. Now its AI-powered product attribution is available to retailers through the Microsoft Azure Consumption Commitment program.
- [Purva Gupta Honored as Ad Age Leading Women & Rising Star Awards](https://www.lily.ai/blog/purva-gupta-ad-age-leading-women): Lily AI Co-Founder and CEO Purva Gupta is among the 2024 Ad Age Leading Women honorees, celebrated for creating opportunity and driving transformation in marketing and advertising.
- [Purva Gupta, Lily AI Co-Founder and CEO, on Bloomberg Markets: The Close](https://www.lily.ai/blog/lily-ai-ceo-on-uniting-merchants-consumers-using-ai): Purva Gupta discusses the progress of AI technology accuracy in the retail space with Romaine Bostick on “Bloomberg Markets: The Close” on November 10th, 2023.
- [The Ultimate Guide to Integrating Product Attributes, From Google Search to PIM](https://www.lily.ai/blog/product-attributes-implementation): Once you have customer-centric product attribution, you can apply that enriched detail across the retail value chain. Here are three ways our clients approach implementation.
- [How AI Is Fueling a Customer-Centricity Renaissance in Retail](https://www.lily.ai/blog/ai-customer-centricity-retail): Everyone’s been talking about customer-centricity for some time, but putting it into practice is incredibly difficult. AI is ushering in the customer-centricity Renaissance retailers need.
- [3 Big Takeaways From Report On Gen AI Transforming Brand Experiences](https://www.lily.ai/blog/gen-ai-transforms-brand-experiences): An executive summary of Retail TouchPoints’ Tech Guide on how generative AI is transforming brand experiences at three stages of the buying journey: discovery, recommendation, and conversion.
- [The Dirty Truth About Clean Retail Data](https://www.lily.ai/blog/the-dirty-truth-about-clean-retail-data): Data is the lifeblood of AI, data science, and analysis, yet product data is rarely as clean as it needs to be. Missing, messy, and dirty data means garbage in, garbage out.
- [Lily AI Expands International Footprint, Starting in London](https://www.lily.ai/blog/lily-ai-uk-london-office): Lily AI is expanding its international presence further with a new London office, bringing its customer-centric product attribution platform to European markets.
- [Retail AI Experts On What Differentiates Lily AI’s Training Data and Why It Matters](https://www.lily.ai/blog/retail-ai-experts-training-data): Horizontal AI models trained on data scraped from the web miss retail-specific information and consumer behavior. A deeper look at Lily AI’s training data and why it matters.
- [Shoptalk Recap: Shoptalk or AI-talk?](https://www.lily.ai/blog/shoptalk-recap-shoptalk-or-ai-talk): Shoptalk or AI-talk? Vegas was a-buzz with everything retail-focused, and the biggest focus of retailers seemed to be artificial intelligence. Key takeaways from Shoptalk 2024.
- [Maximize Google Search Performance With New Lily AI Release](https://www.lily.ai/blog/maximize-google-search-performance): Search isn’t dead, but it is evolving. Lily AI has launched its most comprehensive SEO and SEM product attribution capabilities to maximize Google Search performance.
- [Trustworthy AI: What Makes—and Breaks—Consumer Confidence?](https://www.lily.ai/blog/trustworthy-ai-consumer-confidence): Consumers are wary of AI even as trust in the tech industry runs high. Here’s how to build consumer trust in AI, and how the right AI makes shoppers more confident in your brand.
- [eTail West Brings AI-Fueled, People-Focused Retail to the Forefront](https://www.lily.ai/blog/etail-west-brings-ai-fueled-people-focused-retail-to-the-forefront): eTail West is in full swing, and the Lily AI team was excited to see that its mission of bringing humanity to shopping was at the forefront of the event.
- [Lily AI + Shopify Integration: 3 Things You Can Do With Your Saved Time](https://www.lily.ai/blog/lily-ai-shopify-integration): With our new Shopify integration, brands and retailers can automatically export their product catalogs to Lily AI and receive their industry-leading product attributes in return.
- [AI Product Description Generator: 1 Dress, Described 3 Ways](https://www.lily.ai/blog/ai-product-description-generator): Lily AI's product description generator crafts copy custom-tailored to each retailer's voice. See how one white halter dress is described three very different ways.
- [How Can AI Boost Profitability for Retailers in Economic Uncertainty?](https://www.lily.ai/blog/ai-profitability-economic-uncertainty): Consumers are bracing for continued economic uncertainty, and tightening pursestrings hit retailers directly. Here is where AI’s retail promise lies.
- [AI for Retailers: Its Impact on Merchandising Teams](https://www.lily.ai/blog/ai-for-retailers-merchandising): Merchandisers are hyper-focused on product sales and inventory productivity. AI-assisted product attribution makes that forecasting work more accurate and efficient than ever.
- [2024 Trends: Macro vs. Micro](https://www.lily.ai/blog/2024-trends-macro-vs-micro): Today’s trend cycles come and go faster than ever. We examine three hot micro-trends and their macro-trend counterparts across fashion, beauty, and home.
- [AI-Generated Product Descriptions:Customer-Centric Content Generation for Retailers](https://www.lily.ai/blog/lily-ai-generated-product-descriptions): Product and marketing copy often leaves much to be desired: for brands and retailers the process is too manual and lacks data-driven precision.
- [Head of Digital: How to Work With AI in 2024](https://www.lily.ai/blog/work-with-ai-retail-cto-cio-teams): AI boomed in 2023 and is on pace to become essential in retail. Here is how it will change work across the teams that report to the Head of Digital.
- [3 Research-Backed Ways AI Enhances Omnichannel Shopping](https://www.lily.ai/blog/retail-ai-omnichannel-shopping): In 2024, shopping must be personalized and seamless, weaving together online and offline. Three of retail’s biggest trends and how brands can harness AI to address them.
- [Key Takeaways from This Week’s Business of Fashion VOICES Conference and State of Fashion Report](https://www.lily.ai/blog/business-of-fashion-lily-ai): The Business of Fashion VOICES conference and the BoF and McKinsey State of Fashion 2024 report sent one clear message: AI is already well-integrated into the fashion industry.
- [Capitalizing on the Mobile Shopping Experience with AI](https://www.lily.ai/blog/capitalizing-on-the-mobile-shopping-experience-with-ai-a-game-changer-for-retailers): As more and more online shopping happens via mobile, retailers have a unique opportunity to leverage AI to capitalize on the mobile shopping experience.
- [Lily AI & Bloomberg On AI and Bringing Humanity to Shopping](https://www.lily.ai/blog/lily-ai-bloomberg-shopping-retail-ai): Co-Founder and CEO Purva Gupta was featured on Bloomberg’s The Close. Three key takeaways on how Lily AI helps retailers think like their customers and drives 9-figure revenue lifts.
- [The Estée Lauder Companies Name Lily AI The Winner of Its Open Innovation Challenge](https://www.lily.ai/blog/the-estee-lauder-companies-name-lily-ai-the-winner-of-its-open-innovation-challenge): Lily AI is the winner of The Estée Lauder Companies 2023 Open Innovation Challenge for Optimizing Product Discovery Experience.
- [AI for the Holidays Webinar: 6 Key Takeaways](https://www.lily.ai/blog/ai-for-the-holidays-webinar-6-key-takeaways): Many retailers believe the window to test new technology closes by mid-October. Purva Gupta says it’s never too late, especially with AI. Six takeaways from our holiday webinar.
- [Putting ChatGPT to the Synonym Test](https://www.lily.ai/blog/putting-chatgpt-to-the-synonym-test): Large language models have earned admiration for their ability to generate human-like text, but they are not standalone solutions. We put ChatGPT to the test on product synonyms.
- [The Retailer’s Dilemma: Build Vs. Buy AI](https://www.lily.ai/blog/the-retailers-dilemma-build-vs-buy-ai): Retail CIOs and CTOs can build AI in-house, buy off-the-shelf software, or partner with vertical AI specialists. Here is the case for augmenting your existing technology investments.
- [Infographic: Customer-Speak, Engineered for Scale](https://www.lily.ai/blog/customer-speak-engineered-for-scale): The New York Times published a feature on Lily AI’s impact on retail. Here we demystify “consumer-speak,” our 20,000-word product taxonomy, and the scale we’ve reached to date.
- [How Vertical AI Transforms the Retail Value Chain](https://www.lily.ai/blog/how-vertical-ai-transforms-the-retail-value-chain): Vertical AI, purpose-built for retail, is revolutionizing every aspect of the retail value chain. See how the language of the consumer transforms make, market, and sell.
- [Don’t Let Q3 Code Freeze Hurt Your Chances for a Strong Q4 Holiday](https://www.lily.ai/blog/dont-let-q3-code-freeze-hurt-your-chances-for-a-strong-q4-holiday): The Q4 holiday rush is coming. Purpose-built vertical AI platforms let retailers still make Q3 investments that lift customer experience and operational efficiency.
- [How Vertical AI is Fueling the Next Wave of Retail Growth and Innovation](https://www.lily.ai/blog/why-purpose-built-ai-is-playing-a-pivotal-role-in-reshaping-the-future-of-retail-like-never-before): AI is driving a revolutionary transformation in retail marketing, merchandising, and operations — and purpose-built vertical AI is playing a pivotal role in reshaping the industry’s future.
- [How AI Is Revolutionizing Retail](https://www.lily.ai/blog/how-ai-is-revolutionizing-retail): Retail has an unquenchable thirst for innovation, and AI leads the pack. Why the next wave will come from vertical AI purpose-built for retail rather than horizontal AI.
- [Macro Trend: Comfort](https://www.lily.ai/blog/macro-trend-comfort): Since 2000, few retail macro trends have been as pivotal as athleisure. Its seeds have blossomed into a whole new fashionably acceptable aesthetic: embracing comfort.
- [Quiet Luxury Part Deux](https://www.lily.ai/blog/quiet-luxury-part-deux): Quiet luxury, or “stealth wealth,” means understated design, subtle branding, and a focus on quality. A look at aspirational versus achievable quiet luxury.
- [The Rise of Quiet Luxury](https://www.lily.ai/blog/quiet-luxury): The fashion industry has witnessed a trend toward quiet luxury: the discreet yet luxurious clothing of high-end brands, which exudes understated sophistication and refinement.
- [Lily AI’s Fashion Product Taxonomy: What is Dark Academia?](https://www.lily.ai/blog/lily-ais-fashion-product-taxonomy-what-is-dark-academia): Dark Academia, the popular TikTok aesthetic, is one of the darkest trends in fashion: classic, minimalist, and edgy. What defines the look, and the product attributes that capture it.
- [Capturing Synonyms with Product Data Enrichment](https://www.lily.ai/blog/capturing-synonyms-with-product-data-enrichment): Shoppers search uniquely. Capturing synonyms through product data enrichment helps retailers ensure every customer finds what they want, no matter how they describe it.
- [Lily AI’s Fashion Product Taxonomy: What is Barbiecore?](https://www.lily.ai/blog/lily-ais-fashion-product-taxonomy-what-is-barbiecore): With pops of bright pink and bold fuchsia, Barbiecore is one of the hottest trends in fashion. Inspired by the upcoming live-action Barbie movie, it's time to think (hot) pink.
- [5 Ways AI Supercharges Site Search](https://www.lily.ai/blog/5-ways-lily-ai-will-supercharge-your-ecommerce-site-search-engine): Search bar shoppers are 2-3x more likely to make a purchase than shoppers who don't use it. Here are five ways AI supercharges your e-commerce site search engine.
- [Looking for More Zero-Party Data? You Probably Already Have It](https://www.lily.ai/blog/looking-for-more-zero-party-data-you-probably-already-have-it): Zero-party data, what a customer intentionally and proactively shares with a brand, has emerged as strategically important. Your site search queries are already a rich source of it.
- [Trend Identification and the Top Fall & Winter 2022 Trends](https://www.lily.ai/blog/trend-identification-and-the-top-fall-winter-2022-trends): Trend identification is a key part of every fashion, beauty, and home retailer’s journey. A look at how the trend cycle works, plus the top fall and winter 2022 trends.
- [A Q&A on Home Product Attribution with Lily AI’s Amy Chong](https://www.lily.ai/blog/a-qa-on-home-product-attribution-with-lily-ais-amy-chong): Lily AI Senior Styling Manager Amy Chong on how home products are attributed, how that differs from fashion, and the home decor trends circulating right now.
- [Boost Your Holiday AOS and RPV with Customer-Centered Product Attributes](https://www.lily.ai/blog/boost-your-holiday-aos-and-rpv-with-customer-centered-product-attributes): The holiday shopping rush is upon us, and there is still time to boost AOS, RPV, and your e-commerce strategy by adding customer-centered product attributes to your wish list.
- [The Power of Actionable Search Insights at Your Fingertips](https://www.lily.ai/blog/the-power-of-actionable-search-insights-at-your-fingertips): Out-of-the-box site search analytics are slow-moving and generic. Lily AI’s Search Analytics Dashboard helps retailers act on search trends through the lens of the consumer.
- [The Top Home Decor Styles](https://www.lily.ai/blog/the-top-home-decor-styles): Shopping for a home is a personal act, and one shoppers take very seriously. There are plenty of home decor styles to choose from, so let's look at some of the top ones.
- [How to Capitalize on Shoppers’ Search Diversity](https://www.lily.ai/blog/how-to-capitalize-on-shoppers-search-diversity): Every consumer has their own long-tail way to describe what they are looking for, yet this search diversity is barely acknowledged on a high percentage of e-commerce retail sites.
- [Build a Better Brand Initiative with Lily AI’s Taxonomy](https://www.lily.ai/blog/build-a-better-brand-initiative-with-lily-ais-taxonomy): Getting the right items out at the right time is a tricky art to master in retail. Lily AI's customizable taxonomy evolves to align with your brand initiatives, right on schedule.
- [Product Discovery in the Influencer Age: How to Capitalize on Social Media Fads](https://www.lily.ai/blog/product-discovery-in-the-influencer-age-how-to-capitalize-on-social-media-fads): Influencer culture puts a heavy focus on Gen Z, whose buying power tops $140 billion. To capitalize on fast-moving social media fads, retailers must strengthen product discovery.
- [The Connection Between Fashion Merchandising and Product Attribution Data](https://www.lily.ai/blog/the-connection-between-fashion-merchandising-and-product-attribution-data): From the start of the runway to the finale on the shelf or search bar, fashion merchandising is a complex, interwoven system. Better item set-up with customer-centric AI helps.
- [The Importance of Empathy in Fashion Product Attribution](https://www.lily.ai/blog/the-importance-of-empathy-in-fashion-product-attribution): Shopping for a new outfit has not always been an experience that drives empathy. Finding an item that actually makes a shopper feel good can make all the difference.
- [Effective Product Attribution Q&A with Lily AI’s Sean Gouldson](https://www.lily.ai/blog/effective-product-attribution-qa-with-lily-ais-sean-gouldson): Lily AI Head of Presales Sean Gouldson on the nuts and bolts of product attribution: how it is applied at item set-up, what data retailers need to provide, and how tags evolve.
- [Revolutionizing Retail with AI and Product Attribution Data](https://www.lily.ai/blog/revolutionizing-retail-with-ai-and-product-attribution-data): Retail’s transformation to digital is a revolution worth talking about. Here is how the industry has changed, particularly with the help of AI and product attribution data.
- [Afternoon Tea with SMEs: Moving at the Speed of AI to Win in Google Search](https://www.lily.ai/blog/retail-ai-google-search): Our experts James Beauchamp and Abhijit Shome discuss how retailers and brands should navigate the next eras of product discovery, Google Search and beyond.
- [Fashion Product Attribution and the Top 3 Style Trends for Summer 2022](https://www.lily.ai/blog/fashion-product-attribution-and-the-top-3-style-trends-for-summer-2022): New season, new style trends. Lily AI's in-house team of domain experts share their takeaways on three core women's apparel style trends for summer 2022.
- [Bringing AI Science to the Art of Merchandising with Product Attribution Data](https://www.lily.ai/blog/bringing-ai-science-to-the-art-of-merchandising-with-product-attribution-data): Merchandising is both an art and a science, and there’s nothing to fear from the fusion of the two: together they help retailers boost revenue and move inventory faster.
- [How to Connect Shoppers to What They Want and Need with Customer-Centric Product Recommendations](https://www.lily.ai/blog/how-to-connect-shoppers-to-what-they-want-and-need-with-customer-centric-product-attributes): The right, relevant product recommendations are evergreen. Connecting shoppers to what they actually want and need, this month and every month after, is worth the extra effort.
- [Boost Your Beauty Product Attribution: Part 1](https://www.lily.ai/blog/boost-your-beauty-product-attribution-part-one): Today’s beauty consumer knows exactly what they want. Part one of two on how Lily AI boosts site search, personalization potential, and SEO/SEM for beauty brands.
- [It’s Not Product Attribution Data OR Search – It’s Both](https://www.lily.ai/blog/its-not-product-attribution-data-or-search-its-both): Search is central to e-commerce, but swapping search vendors solves only half the problem. Without a robust product attribution taxonomy, it’s a costly cart with no horse.
- [The Cascading Challenge of Legacy, Out-of-the-Box Product Attributes](https://www.lily.ai/blog/the-cascading-challenge-of-legacy-out-of-the-box-product-attributes): “It’s the way we’ve always done it” is commerce’s most common excuse. Legacy, out-of-the-box product attributes start a cascading series of problems at item set-up.
- [Trend Identification: How Does it Build Customer Confidence?](https://www.lily.ai/blog/what-is-trend-identification-how-does-it-build-confidence-in-customer-relationships): Lily AI's domain experts understand trend cycles and where to find the latest directions in fashion, home, and beauty. Here's what trend identification is and the role it plays.
- [High-Conversion Shoppers Deserve a Seamless Search Experience](https://www.lily.ai/blog/high-conversion-shoppers-deserve-a-seamless-search-experience): Type a typical, specific search term into your favorite fashion site's search bar and you are met with a surprising amount of resistance. High-conversion shoppers deserve better.
- [Customer Success at its Best: A Q&A with Lily AI’s Catherine O’Keefe](https://www.lily.ai/blog/customer-success-at-its-best-a-qa-with-lily-ais-catherine-okeefe): A Q&A with Senior Customer Success Manager Catherine O’Keefe on how Lily AI nurtures client relationships through the full lifecycle of its platform and services.
- [Product Attribution for Beauty Brands: A Q&A with Lily AI’s Joyce Lay](https://www.lily.ai/blog/customer-intent-for-beauty-brands-a-qa-with-lily-ais-joyce-lay): Joyce Lay, Lead Merchandise Analyst at Lily AI, on how beauty products differ from apparel and the challenges beauty brands face turning shopper intent into purchases.
- [Human-Powered Product Taxonomies: An Interview with Lily AI’s Kathy Lee](https://www.lily.ai/blog/human-powered-product-taxonomies-an-interview-with-lily-ais-kathy-lee): Lily AI’s Kathy Lee on why product discovery became retail’s battleground, how our in-house styling team builds category taxonomies, and how stylists work with automation.
- [How Customer-Centric Product Attributes Help Mitigate the Supply Chain Crunch](https://www.lily.ai/blog/how-granular-product-attributes-help-mitigate-the-supply-chain-crunch): The pandemic and the associated supply chain crunch exposed how many retailers still use historical data to forecast demand. So, can better product attribution data save the day?
- [3 Reasons Why E-Commerce Product Recommendations & Personalization Have Never Been More Pressing](https://www.lily.ai/blog/ecommerce-product-recommendations): Two years into the pandemic, we've learned why e-commerce success is tied to strong product recommendations, online personalization, and rock-solid demand forecasting.
- [7 to Stay, 1 to Go: Retail Trends in E-Commerce That Will Outlast the Pandemic](https://www.lily.ai/blog/7-to-stay-1-to-go-retail-trends-in-ecommerce-that-will-outlast-the-pandemic): Multiple pandemic-driven changes in retail trends are here to stay, though not every trend has staying power. A look at eight e-commerce trends, and which ones will last.
- [Lily AI is Now Available on Microsoft Azure](https://www.lily.ai/blog/lily-ai-now-available-on-microsoft-azure-to-re-define-retail-ecommerce-with-ai-powered-customer-intent-platform): Lily AI's product attributes platform is now hosted on Microsoft Azure and available through the Azure Marketplace and Microsoft AppSource.
- [Why Product Data is Key to Your Search Engine Marketing and Optimization](https://www.lily.ai/blog/why-product-data-is-key-to-your-search-engine-marketing-solution): More product data, and more granular product data, is simply better. Five ways customer-centric product attributes can inform your search engine marketing solution.
- [Purva Gupta named an EY Entrepreneur Of The Year 2024 Bay Area finalist](https://www.lily.ai/press/ey-entrepreneur-of-the-year-2024-finalist): Lily AI Co-Founder and CEO Purva Gupta was named a finalist for the EY Entrepreneur Of The Year 2024 Bay Area award.
- [Lily AI closes $25M Series B to bring the language of the customer across the retail value chain](https://www.lily.ai/press/series-b-announcement): Lily AI announced the close of its Series B financing round, with participation from Canaan Partners, Conductive Ventures, Sorenson Ventures and NEA, to bring the language of the customer across the entire retail value chain.
- [Retail tech start-up Lily AI secures $25 million Series B financing](https://www.lily.ai/press/series-b-funding-wwd): WWD reports on Lily AI's $25 million Series B round and its plans to expand across mid-market retail, home and beauty, and into the U.K. and Europe.
- [What is Lily AI?](https://www.lily.ai/faqs/what-is-lily-ai)
- [What is agentic product intelligence?](https://www.lily.ai/faqs/what-is-agentic-product-intelligence)
- [How does Lily Max work?](https://www.lily.ai/faqs/how-does-lily-max-work)
- [Who is Lily Max for?](https://www.lily.ai/faqs/who-is-lily-max-for)
- [Which channels and surfaces does Lily Max support?](https://www.lily.ai/faqs/which-channels-and-surfaces-does-lily-max-support)
- [What does Lily do?](https://www.lily.ai/faqs/what-does-lily-do)
- [Which channels does Lily support?](https://www.lily.ai/faqs/which-channels-does-lily-support)
- [Is Lily a content generator or a feed manager?](https://www.lily.ai/faqs/is-lily-a-content-generator-or-a-feed-manager)
- [How much does Lily Max cost?](https://www.lily.ai/faqs/how-much-does-lily-max-cost)
- [How is Lily priced?](https://www.lily.ai/faqs/how-is-lily-priced)
- [Is there a free trial?](https://www.lily.ai/faqs/is-there-a-free-trial)
- [How is Lily different from a feed management tool or an agency?](https://www.lily.ai/faqs/how-is-lily-different-from-a-feed-manager-or-agency)
- [How is Lily different from AI visibility tools?](https://www.lily.ai/faqs/how-is-lily-different-from-ai-visibility-tools)
- [How is Lily different from agentic-commerce-only (ACO) tools?](https://www.lily.ai/faqs/how-is-lily-different-from-agentic-commerce-only-aco-tools)
- [What data does Lily need to get started?](https://www.lily.ai/faqs/what-data-does-lily-need-to-get-started)
- [How does Lily keep product intelligence accurate?](https://www.lily.ai/faqs/how-does-lily-keep-product-intelligence-accurate)
- [Do I keep control of my ad accounts and data?](https://www.lily.ai/faqs/do-i-keep-control-of-my-ad-accounts-and-data)
- [How does Lily prove the results are real?](https://www.lily.ai/faqs/how-does-lily-prove-the-results-are-real)
- [Can Lily guarantee my products will appear in ChatGPT, AI Overviews, or other AI assistants?](https://www.lily.ai/faqs/can-lily-guarantee-my-products-appear-in-ai-answers)
- [Can I measure revenue from AI-driven discovery?](https://www.lily.ai/faqs/can-i-measure-revenue-from-ai-driven-discovery)
- [Why does Lily say "the score is not the outcome"?](https://www.lily.ai/faqs/why-does-lily-say-the-score-is-not-the-outcome)
- [What kind of results do customers see?](https://www.lily.ai/faqs/what-kind-of-results-do-customers-see)
- [How long until I see impact?](https://www.lily.ai/faqs/how-long-until-i-see-impact)
- [Does Lily Max replace my existing tools or PIM?](https://www.lily.ai/faqs/does-lily-max-replace-my-existing-tools-or-pim)
- [How do I get started, and how soon will I see results?](https://www.lily.ai/faqs/how-do-i-get-started-and-how-soon-will-i-see-results)
- [How long does onboarding take?](https://www.lily.ai/faqs/how-long-does-onboarding-take)
- [How does Lily protect my data?](https://www.lily.ai/faqs/how-does-lily-protect-my-data)
- [Is my catalog or ad data ever shared or sold?](https://www.lily.ai/faqs/is-my-catalog-or-ad-data-ever-shared-or-sold)
- [Does Lily work for agencies managing multiple brands?](https://www.lily.ai/faqs/does-lily-work-for-agencies-managing-multiple-brands)
- [How do I partner with Lily as an agency?](https://www.lily.ai/faqs/how-do-i-partner-with-lily-as-an-agency)
- [Privacy](https://www.lily.ai/privacy)
- [Terms](https://www.lily.ai/terms)
- [Security](https://www.lily.ai/security)