Lily AI

Lily AI is a product data enrichment platform that helps retailers improve their catalog so products show up and convert better on Google Shopping, Meta ads, onsite search and AI shopping assistants. Founded in 2015, it started with product attribute tagging for fashion and retail, and now positions its Lily Max agents around agentic commerce, where AI assistants need clean, structured product data to recommend items. It pairs enrichment with controlled tests, so teams can see whether better data actually moves performance.

What is Lily AI used for?

Ecommerce and merchandising teams use Lily AI to fill gaps in product feeds and pages at scale, especially across catalogs with tens of thousands of SKUs.

• Generating core Google Shopping attributes per SKU to improve feed approval and match quality
• Writing Meta catalog ad copy that is quality checked before it ships
• Creating SEO and answer-engine metadata such as titles, descriptions, alt text and schema markup
• Adding conversational attributes that power chat and voice shopping assistants
• Classifying new items and populating structured fields during item setup
• Running A/B tests and gap analysis on high-demand search terms to measure lift

Who Lily AI is best for

Lily AI is built for mid-size and enterprise retailers, marketplaces and the agencies that manage their ads, particularly in apparel, home and beauty where attributes like fit, style and occasion matter. It suits teams with large catalogs and meaningful ad spend. A small shop with a few dozen products will get more value from a self-serve product description writer.

Lily AI pricing

Lily AI does not publish a rate card. As of October 2026, its pricing page says cost depends on catalog size, which use cases you choose and how many markets you sell in, and that cost per SKU generally falls as volume grows. You build a quote request on the site or book a demo, and Lily returns a line-itemized quote. A free feed audit is offered to new prospects.

Limitations to keep in mind

• Pricing is custom, so you cannot estimate cost before talking to sales
• It enriches data you already have; poor source data still limits results
• The focus is retail catalogs, not general marketing content
• Results depend on pushing the enriched data back into your feeds and site

Lily AI vs alternatives

Describely is the closest alternative for teams that mainly want product titles, descriptions and SEO metadata generated across a catalog, with a more self-serve approach. Shopify Sidekick can write product copy for small Shopify stores inside the admin. Copy.ai and Jasper suit marketing teams that need broader content, not structured feed attributes. Lily AI wins for large retailers that want attribute-level enrichment tied to measured lift in shopping ads and AI discovery.

Tips for getting started with Lily AI

Start with the free feed audit to see where your attributes are missing or inconsistent. Pick one channel and one category, such as Google Shopping for a top category, for the first test so the lift is easy to measure. Agree on success metrics like impression share or conversion rate before enrichment begins. Plan who on your team will push enriched data back into your feed tools.

Lily AI FAQ

Is Lily AI free?

No. Lily AI offers a free feed audit, but the platform itself is priced through custom quotes based on catalog size, use cases and markets.

What is Lily AI used for?

Lily AI is used to enrich retail product catalogs with attributes, metadata and copy that improve performance in shopping ads, site search and AI assistants.

Does Lily AI work for small stores?

Lily AI is designed for retailers with large catalogs, so small stores are usually better served by self-serve product description tools.

What is the best alternative to Lily AI?

Describely is a close alternative for catalog-wide product copy and metadata, with a more self-serve setup than Lily AI.