Lily AI
Agentic product intelligence engine that enriches e-commerce catalogs for AI-powered commerce.
Lily Max takes a data-driven approach to feed enrichment, and the reported lifts are impressive. However, the tailored quote model means you won't know the cost until you talk to sales. It's a strong fit for brands with substantial ad spend looking to prove ROI, but smaller teams may find the opaque pricing and enterprise focus a hurdle.
Verified 6d ago · liveness 75/100 · cite: rightaichoice.com/tools/lily-ai
- Performance marketing teams at retail brands optimizing Google Shopping and Meta ads
- Enterprise retailers with large product catalogs needing AI-ready product data
- Agencies managing multi-channel e-commerce campaigns for multiple clients
- Brands preparing for AI-driven shopping surfaces like ChatGPT and Gemini
- Small businesses with very limited product catalogs (under 500 products)
- Teams without existing product feed infrastructure or catalog system
- Use cases requiring real-time personalization beyond product enrichment
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Skip Lily Max if you have a small catalog (under 500 products), need transparent upfront pricing, or expect the tool to manage your ad campaigns—it only enriches product data and doesn't run ads.
Going past 500 products in the free trial requires a tailored quote, and costs scale with catalog size and monthly ad spend, so expect to pay more as you grow.
Lily Max's pricing is tailored to your catalog size and ad spend, making it a good fit for mid-to-large retailers with substantial budgets. It's costlier than self-serve feed tools like DataFeedWatch (which has published per-feed pricing), but the matched-spend testing and revenue-lift measurement can justify the investment for performance marketers.
In short
Lily AI — Agentic product intelligence engine that enriches e-commerce catalogs for AI-powered commerce. Best for Performance marketing teams at retail brands optimizing Google Shopping and Meta ads, Enterprise retailers with large product catalogs needing AI-ready product data, Agencies managing multi-channel e-commerce campaigns for multiple clients. Contact Sales pricing.
What's new in Lily AI
Checked 6 days agoAcross the latest 5 updates: 5 news mentions.
A buying standard for AI commerce
Lily AI proposes four questions to evaluate AI marketing tools, emphasizing surviabilty under finance review.
The most expensive thing in retail right now
CEO previews CommerceNext session, arguing retailers overlook revenue-generating surfaces for unproven AI futures.
Google says conversational attributes are optional. History says otherwise.
Lily AI argues Google's new AI-shopping feed fields will become mandatory, like mobile-friendly and page speed did.
Google may have just created a billion-dollar optimization market
Google's new AI Performance Insights make AI visibility measurable, likely unlocking budgets for feed optimization.
$80M in incremental revenue last month, one optimization: the feed
Case study showing four Google Ads tests where revenue lifts were driven entirely by Google Merchant Center feed optimization.
What people actually say about Lily AI — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
15 mentions across 1 source (Lemmy) · researched Jul 3, 2026.
- +AI-driven feed enrichment for Google Shopping and Meta Advantage+ compatibility.
- +Controlled A/B testing lets teams validate feed changes before rolling out.
- +AI Performance Insights tie enrichment directly to revenue lift metrics.
- +Goal-based AI agents automate product data optimization across paid channels.
- +Conversational attribute extraction prepares products for LLM-powered shopping assistants.
- −Virtually no real user reviews or community discussions to validate claims.
- −Pricing is not transparent — contact-only model raises cost concerns.
- −Listed integrations as N/A, limiting plug-and-play with existing tools.
- −No free tier or trial mentioned, risking buyer's remorse.
- −Performance claims are vendor-supplied, not independently verified.
- • No public pricing — may require annual contracts or setup fees
- • Possible overage charges for high-volume catalogs
Viability Score
How well maintained and how widely used is Lily AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: August 2026
How we score →Key Features
- Goal-based AI agents for continuous enrichment
- AI-generated product attribute enrichment
- Google Merchant Center feed optimization
- Meta Advantage+ product feed integration
- AI Performance Insights for search term gap analysis
- Controlled matched-spend A/B testing with holdout groups
- Agent-ready payload generation for LLM shopping agents
- Onsite search revenue lift via enriched attributes
- Enrichment scoring and gap analysis
- Schema-validated product payload generation
- Multi-surface support (Google, Meta, AI discovery, onsite)
- Human approval before shipping changes to feeds
About Lily AI
Lily Max is an agentic product intelligence engine that enriches your e-commerce catalog with structured, machine-readable attributes, making your products legible to AI shopping surfaces like Google Shopping, Meta Advantage+, ChatGPT, and Gemini. It's built for performance marketing teams at brands, agencies, and enterprise retailers who need to improve product visibility, conversion, and ROAS across both traditional and AI-mediated channels. Lily Max works by ingesting your existing product feed, scoring data gaps, and using AI agents to continuously enrich attributes, titles, descriptions, and schema markup. It then runs controlled matched-spend A/B tests with holdout groups to measure the actual revenue lift from enrichment—so you can prove impact before scaling. Reported results include +28% revenue lift on Google Shopping, +21.4% ROAS lift on Meta, and +28.3% onsite revenue lift. Lily Max integrates with your existing feed managers and ad tools, so there's no replatforming. Pricing is tailored to catalog size, channels, and monthly ad spend, with a free 30-day trial for 500 products. The platform emphasizes agentic commerce readiness, ensuring your catalog can be understood and recommended by LLM-based shopping assistants. It's not a full ad management platform; it focuses solely on product data enrichment and measurement, with human approval before changes go live.
Behind the Verdict
Lily Max is a specialized tool for performance marketers who live and die by product feed quality. Its core value proposition is turning messy, unstructured product data into structured, AI-readable attributes that power better visibility on Google, Meta, and emerging LLM-based shopping surfaces. The platform’s key differentiator is its measurement rigor: it runs matched-spend A/B tests with holdout groups, so you can see the actual revenue lift before scaling changes. This is a rare discipline in the feed-enrichment space, and it makes Lily Max appealing for brands that need to justify spend to skeptical finance teams.\n\nThe reported results—+28% revenue lift on Google Shopping, +21.4% ROAS lift on Meta, and +28.3% onsite revenue lift—are eye-catching, but they are from customer case studies, not independent benchmarks. You should treat these as directional, not guarantees. On the positive side, Lily Max integrates with your existing feed managers and ad tools, so there’s no replatforming; you keep your current stack and just improve the data flowing through it. The AI-agent-driven enrichment is continuous, and the platform scores gaps, prioritizes high-impact attributes, and generates schema-validated payloads that AI surfaces can parse.\n\nWhere Lily Max falls short is pricing transparency. There’s no public price card; you must book a demo to get a quote. This makes it hard to compare with competitors like Feedonomics or DataFeedWatch, which have published pricing. For small businesses with under 500 products, the 30-day free trial is a nice entry point, but the tailored-quote model may feel like a barrier. Additionally, Lily Max is not an ad management platform—it doesn’t run campaigns, bid, or allocate budget. It only optimizes product data. If you need end-to-end ad management, this is not the tool.\n\nOverall, Lily Max is a strong fit for performance marketing teams at mid-to-large retailers with substantial ad spend and a need to prove ROI. It’s less suitable for small businesses with limited catalog size or those who want transparent, predictable pricing. If you value measurement and are willing to engage with sales, Lily Max is worth a demo.
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Real-world workflow fit
Concrete scenarios for the personas Lily AI actually fits — and what changes day-one when you adopt it.
You're running Google Shopping campaigns but seeing stagnant ROAS. You connect Lily Max to your existing Google Merchant Center feed, run a 30-day trial on 500 products, and Lily scores your data gaps and enriches high-impact attributes. You launch a matched-spend A/B test, and within weeks you see a measurable revenue lift on the enriched feed.
Outcome: You prove a +28% revenue lift on Google Shopping, get finance on board, and expand Lily Max to your full catalog.
You manage Meta Advantage+ campaigns for several retail clients. You use Lily Max to enrich product feeds for each client, run cross-channel tests, and report the ROAS lift to each client with holdout-group validation.
Outcome: You demonstrate clear ROI to clients, strengthen retention, and scale your managed ad spend.
You're seeing ChatGPT and Gemini start to recommend products, but your catalog lacks structured data for these surfaces. You deploy Lily Max's Enterprise plan, which generates agent-ready payloads and ensures your products are AI-readable. You track visibility in LLM-based shopping experiences and see your brand appear as a top recommendation.
Outcome: Your brand is ranked #1 in AI shopping experiences for your category, giving you a competitive edge in emerging channels.
Use Cases
- Enrich product titles and descriptions with high-demand search terms to improve Google Shopping performance
- Run controlled A/B tests to measure the revenue lift from feed changes before full rollout
- Generate agent-ready product payloads for LLM-based shopping assistants like ChatGPT and Gemini
- Optimize Meta Advantage+ campaigns by enriching product attributes for better ad matching
- Audit existing product data for AI readability gaps and automatically fill missing attributes
- Improve onsite search conversion rates by adding granular, schema-validated product attributes
- Prepare product catalog for AI-powered shopping surfaces and agentic commerce
Models Under the Hood
as of 2026-08-21
Limitations
- Pricing is not publicly listed and requires a tailored quote or booking a demo.
- The platform focuses on product feed enrichment and does not handle ad management or campaign execution directly.
- It requires a product catalog or feed to begin, and advanced features like agentic commerce readiness may be gated to enterprise plans.
as of 2026-08-16
Verification history
We have re-verified Lily AI 4 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Lily AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Starter
Contact for tailored quote
Ideal for
Growing brands getting started with AI retail media on a single primary channel, wanting to prove lift before expanding.
What this tier adds
Starting tier: includes catalog ingestion, product-data scoring, enrichment on highest-impact gaps, and matched-spend testing.
Growth
Contact for tailored quote
Ideal for
Multi-channel brands scaling spend across Google Ads, Meta Ads, and onsite, needing continuous optimization and cross-channel testing.
What this tier adds
Adds multi-channel support, continuous optimization loops, broader catalog coverage, cross-channel testing cadence, and human approval before feed changes.
Enterprise
Custom
Ideal for
Large retailers and marketplaces with complex catalogs and governance needs, requiring dedicated support and custom SLAs.
What this tier adds
Adds dedicated support, custom SLAs, security and compliance review, and readiness for emerging AI-discovery and agentic-commerce surfaces.
Where the pricing makes sense
The company stage and team size where Lily AI's pricing actually pencils out — and where peers do it cheaper.
Lily Max's pricing is tailored to your catalog size and ad spend, making it a good fit for mid-to-large retailers with substantial budgets. It's costlier than self-serve feed tools like DataFeedWatch (which has published per-feed pricing), but the matched-spend testing and revenue-lift measurement can justify the investment for performance marketers.
Setup time & first value
How long it actually takes to get something useful out of Lily AI — broken out by persona, not the marketing-page minute.
Most teams get set up in under a week. You'll need to provide access to your product feed (e.g., Google Merchant Center), and Lily Max will score your gaps and start enrichment. The 30-day free trial on 500 products lets you see initial results within days.
Switching to or from Lily AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual feed optimization: Replace time-consuming manual keyword research and attribute cleanup with Lily Max's automated enrichment, while keeping your existing feed manager.
- →From a competitor like Feedonomics: Upload your existing feed and Lily Max will score gaps and prioritize enrichment based on your current channels—no replatforming needed.
- →From using Google's own attributes: Import your GMC feed and let Lily Max enhance it with deeper attributes and continuous optimization.
- ↗To a self-serve feed tool like DataFeedWatch: Export your enriched feed and continue using it with your existing ad platforms.
- ↗To an in-house data team: Download your enriched product data and integrate it into your own systems, though you'll lose Lily Max's continuous optimization and testing.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Lily AI
Common stack mates teams adopt alongside Lily AI, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Lily Ai vs Weglot
Lily AI and Weglot serve entirely different e-commerce pain points: Lily Max optimizes product feeds for ad platforms and AI shopping surfaces (with recent news emphasizing feed criticality), while Weglot handles multilingual website translation. If your goal is to boost Google Shopping and Meta ad performance via enriched product data, choose Lily AI. If you need to rapidly translate your e-commerce site into multiple languages with brand consistency and SEO, choose Weglot.
Lily Ai vs Screenplayiq
Lily AI and ScreenplayIQ serve entirely different audiences — one optimizes e-commerce feeds for measurable ad lift, the other predicts screenplay box office returns. If you're a retail marketer seeking to boost Google Shopping or Meta ad performance with AI enrichment, Lily AI is your tool. If you're a screenwriter or producer needing data-driven script feedback and financial forecasts, ScreenplayIQ fits better. The choice is purely domain-based.
Lily Ai vs Chili Piper
Lily AI and Chili Piper serve completely different missions: Lily AI optimizes e-commerce product feeds for ad platforms and AI shopping surfaces, while Chili Piper automates B2B lead conversion from website traffic. Your choice depends on whether your priority is improving product visibility on Google/Meta (Lily AI) or accelerating sales meetings from inbound visitors (Chili Piper). There is no overlap, so choose based on your GTM challenge.
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