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AI app

Lily AI

Enriches retail product catalogues with AI-generated attributes, copy and schema, then A/B tests the lift across Google Ads, Meta Ads, AI shopping assistants and onsite search.

  • Paid

Listing data refreshed Built from public product pages and documentation. SourcesClaim this listing

ecommerceguide summary

Lily AI runs Lily Max, an agentic engine that enriches retail product catalogues, generating attributes, descriptions, metadata and schema markup per SKU. Retailers start from their Google Merchant Center feed and extend the enriched data to Google Ads, Meta Ads, Amazon, onsite search and AI shopping assistants. Matched-spend A/B tests, holdout groups and difference-in-differences analysis report lift against a control. Pricing is quoted by catalogue size, use cases and markets, with a 30 day trial on 500 products.

Why it stands out

Enrichment layers onto existing feed managers and commerce stacks, with lift measured by matched-spend A/B tests against a control.

What Lily AI does

ecommerceguide editorial
  • Goal-based agents enrich, evaluate and republish the catalogue continuously
  • Six scoped use cases, from Google Shopping attributes to PDP copy
  • SEO and AEO metadata includes titles, alt text and schema markup
  • Works alongside existing feed managers with no replatforming required
  • Lift reported with confidence intervals from matched-spend A/B tests
  • Free 30 day trial on 500 products, plus a feed audit
  • Quoted pricing based on catalogue size, use cases and markets

How ecommerce teams could use it

ecommerceguide editorial

Illustrative scenarios written by ecommerceguide from the product's documented capabilities. They are not customer case studies.

  1. Apparel retailer running Google Shopping and Performance Max campaigns

    Merchant Center feed carries manufacturer titles with few shopping attributes

    Intended outcomeLily Max generates core shopping attributes per SKU and A/B tests the enriched feed against the existing one

  2. Beauty brand advertising through Meta Advantage+ catalogue ads

    Catalogue ad copy needs to be written and quality-checked across many SKUs

    Intended outcomeLily Max produces ad-ready catalogue copy for Meta placements and reports measured lift against a holdout group

  3. Multi-market retailer preparing products for AI shopping assistants

    Product pages lack structured, machine-readable data for answer engines and shopping agents

    Intended outcomeLily Max adds schema markup, metadata and conversational attributes so AI surfaces can read and match the products

Who it suits

ecommerceguide editorial

Best for

You run a large retail catalogue across Google Ads, Meta Ads, Amazon or onsite search and want enriched product data tested against a control before it ships.

Probably not for

You need published per-SKU pricing, a self-serve signup, or a site search engine itself rather than an enrichment layer feeding one.

Business size
EnterprisePricing is quoted per catalogue with no rate card, and the vendor lists enterprise and agency use cases.
Verticals
DTC apparel and fashion, DTC beauty and cosmetics, Home and furniture

Lily AI pricing

From the vendor

As published by the vendor. Prices change, so confirm on the vendor's site before buying.

Model
Paid
Starting price
$200

Often used alongside

ecommerceguide editorial

What the vendor and reviewers say

From the vendor

Customers named by Lily AI

  • LilyAI
  • Bloomingdales

Named on the vendor's own site (source (opens in a new tab)). Not confirmed with the customers.

Security and compliance claims

  • GDPR
  • CCPA

As stated by the vendor (source (opens in a new tab)). Ask the vendor for certificates before relying on them.

Categories and use cases

Sources

ecommerceguide profiles are built from public product information and written for ecommerce teams. We do not test products, and paying never changes where a listing ranks.

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