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Mentionator

AI Shopping Visibility for Shopify Brands

Get your products recommended by AI shoppers.

Mentionator audits how AI shopping assistants understand your products, then improves your catalog data, product pages, schema, collections, and feeds so ChatGPT, Google AI Mode, Gemini, and Perplexity can recommend your store more accurately.

Join the Shopify pilotSee how it works
  • No fake reviews
  • No hidden content
  • No guaranteed placement

Where shoppers ask

  • ChatGPT
  • Google AI Mode
  • Gemini
  • Perplexity

Why now

Shopping is moving into AI conversations.

Shoppers are asking AI assistants what to buy, not just typing keywords into search bars. The winning stores will be the ones AI systems can understand, match, and trust.

  • Shopify product data is integrated into ChatGPT through Shopify Catalog.

    Source: OpenAI

  • Google AI Mode shopping is powered by a Shopping Graph with more than 50 billion product listings, billions updated hourly.

    Source: Google

  • Product pages, structured data, feeds, reviews, price, availability, shipping, and returns are becoming AI shopping infrastructure.

    Source: Google Search Central

The gap

Your products can be great and still invisible to AI.

AI shoppers describe needs, constraints, and use cases. If your product data does not clearly explain material, fit, dimensions, compatibility, care, price, availability, reviews, shipping, and returns, AI shopping assistants may recommend a competitor with clearer evidence.

  • Product data is too thin

    Descriptions stop at brand and style. AI needs material, fit, dimensions, compatibility, and use case.

  • Product pages are not answer-ready

    Buyers ask in natural language. Pages reply in keywords and category jargon.

  • Feeds and pages disagree

    Merchant Center says one thing, the PDP says another, and AI cannot resolve the conflict.

  • Generic AI dashboards do not fix SKUs

    Mention trackers report what AI said. They do not change product data.

The fix

Mentionator finds the products AI should recommend — then fixes why they do not.

Connect Shopify, choose priority categories, and Mentionator starts testing real AI shopping prompts. It identifies which products are missing, why competitors are being recommended instead, and what changes are needed. Then it improves product data, product pages, schema, collections, and feed fields automatically or through approval.

  1. 1Test natural-language AI shopping prompts.
  2. 2Measure product recommendation rate and AI shelf share.
  3. 3Diagnose missing attributes and weak pages.
  4. 4Improve product titles, descriptions, metafields, schema, collections, and feeds.
  5. 5Retest prompts.

The flow

How Mentionator works

  1. Step 1

    Connect your store

    Connect your store. Mentionator builds a product knowledge graph from your catalog, variants, collections, pages, and optional Merchant Center / Search Console data.

    You see
    Connect Shopify and optional Google Merchant Center / Search Console.
    Mentionator does
    Imports catalog, variants, collections, product metadata, inventory, price, reviews if available, and store structure.
  2. Step 2

    Test AI shopping prompts

    Test AI shopping prompts. We test the questions shoppers actually ask: best non-toxic play mat for a small apartment, comfortable black work shoes for nurses, or gift for a new runner.

    You see
    Prompt clusters and competitor recommendations.
    Mentionator does
    Generates buyer prompts by category, price, intent, use case, persona, and constraint; tests across supported AI surfaces.
  3. Step 3

    Fix product data and pages

    Fix the gaps. Mentionator turns missing attributes, weak product pages, schema errors, and feed inconsistencies into shipped improvements.

    You see
    Action plan or autopilot updates.
    Mentionator does
    Identifies missing attributes and updates product content, metafields, schema, pages, collections, and feeds.
  4. Step 4

    Retest AI shelf share

    Retest AI shelf share. We run the same prompt clusters again to measure product recommendation rate, citation rate, accuracy, and competitor displacement.

    You see
    AI shelf-share and before/after score.
    Mentionator does
    Reruns baseline prompts and measures recommendation rate, citation rate, accuracy, and competitor displacement.

What we touch

Built for the data surfaces that matter in AI shopping.

Mentionator improves product titles, descriptions, metafields, variant labels, collection pages, FAQ blocks, Product schema, Merchant Center feed fields, review themes, shipping details, returns language, and internal links.

  • Product titles

    Clarify type, primary attribute, use case, and constraint without keyword stuffing.

  • Descriptions

    Add buyer-relevant attributes, scenarios, materials, compatibility, care, and product proof.

  • Metafields and attributes

    Fill category-specific attributes such as fabric, skin type, dimensions, age range, materials, compatibility, warranty, and care.

  • Product schema

    Add or repair Product, Offer, AggregateRating, shipping, return, and variant-related structured data where appropriate and visible.

  • Collection pages

    Create AI-readable category context and buyer guidance.

  • FAQ blocks

    Answer the natural-language shopper questions buyers actually ask.

  • Merchant feeds

    Identify feed gaps and inconsistencies where Merchant Center is integrated.

  • Shipping and returns

    Make policy details clearer and easier for AI to surface accurately.

  • Review signals

    Surface legitimate, visible review themes only — never fabricated proof.

  • Prioritization

    Optimize high-margin, in-stock, high-converting products first.

From thin to evidence-rich

From product listing to AI-ready product evidence.

A thin product listing tells AI very little. Mentionator adds the structured, visible, shopper-relevant evidence needed to match natural-language buying intent to the right product.

Before

Luna Mat — Sage

Soft, stylish baby mat for your home.

No structured attributes. AI cannot match a natural-language need (“non-toxic, small apartment, 6×4 ft”) to this product.
After · with Mentionator

Luna Non-Toxic Baby Play Mat — Sage, 6 ft x 4 ft

A cushioned, wipe-clean baby play mat for tummy time, crawling, and everyday play. Designed for infants and toddlers, with a non-toxic foam surface, waterproof finish, and neutral sage color for nurseries, living rooms, and small apartments.

Age range
infant to toddler
Use cases
tummy time, crawling, nursery, playroom, small apartments
Material
non-toxic foam
Care
wipe clean
Dimensions
6 ft x 4 ft
Surface
waterproof
Color
sage

Mentionator does not stuff keywords. It adds the missing product evidence AI assistants need to match a shopper’s natural-language request to the right item.

Measurement

Measure AI shelf share, not just traffic.

Track whether your products are recommended, cited, described accurately, and selected over competitors across high-intent AI shopping prompts.

  • Product recommendation rate

    Percentage of tested prompts where your products appear at all.

  • AI shelf share

    Your share of product recommendations versus competitors.

  • Prompt-to-product match rate

    How often the correct product is matched to the shopper’s need.

  • Citation rate

    How often your PDP, collection page, or merchant data is cited or linked.

  • Accuracy score

    Whether AI describes price, availability, material, fit, and shipping correctly.

  • Competitor displacement

    Prompt clusters where your product moves above or replaces a competitor.

  • Revenue signal

    AI/chat referrer traffic, assisted conversions, and high-intent product views where trackable.

Real prompts

Use cases by ecommerce category

  • BeautyPrompt 01

    Best fragrance-free moisturizer for sensitive skin under $40

    Likely missing

    Skin type, ingredient flags, fragrance-free, texture, finish, proof.

    Mentionator fixes

    Product attributes, ingredient summary, FAQ, collection copy, schema.

  • ApparelPrompt 02

    Comfortable black work pants for petite women

    Likely missing

    Fit, inseam, fabric stretch, body type, occasion, care.

    Mentionator fixes

    Metafields, variant labels, sizing FAQ, collection content.

  • PetPrompt 03

    Best calming dog bed for a large anxious dog

    Likely missing

    Dog weight range, bed size, washable cover, support type, anxiety positioning.

    Mentionator fixes

    Title and description rewrite, product attributes, FAQ, schema.

  • HomePrompt 04

    Small-space dining table for four people

    Likely missing

    Dimensions, seating capacity, room type, assembly, material, style.

    Mentionator fixes

    Attribute enrichment, collection copy, buying guide block.

  • Baby & KidsPrompt 05

    Non-toxic baby play mat for crawling in small apartments

    Likely missing

    Age range, safety and material, dimensions, care, use case.

    Mentionator fixes

    PDP rewrite, safety facts, schema, FAQ, collection guide.

Connections

Connect the systems that power your product discovery.

Mentionator starts with Shopify and expands into the data sources that shape AI shopping visibility.

  • Shopify

    Live

    Products, variants, collections, metafields, inventory, pricing, images, store structure.

  • Google Merchant Center

    Planned

    Feed quality, product data requirements, product status, issue context.

  • Google Search Console

    Planned

    Product page performance, indexing signals, merchant listing visibility, query data.

  • Review platforms

    Planned

    Review themes and rating data — only legitimate, visible, authorized.

  • Analytics

    Planned

    AI / chat referrers, product views, add-to-cart, checkout, revenue attribution.

  • Theme & CMS

    Live

    Structured data, FAQ blocks, collection content, PDP insertion.

Trust by design

AI visibility without spam or fake signals.

Mentionator does not create fake reviews, hide content from users, cloak pages, spam communities, or promise guaranteed AI placement. It improves the product evidence that your store controls.

  • No fake reviews or fabricated ratings.
  • No hidden AI-only content.
  • No cloaking.
  • No guaranteed rankings or recommendations.
  • No claims unsupported by product data or visible page content.
  • Approval workflows for regulated or sensitive categories.

Apply

Join the Shopify pilot.

We are onboarding a small group of Shopify brands that want to understand and improve how their products appear in AI shopping recommendations.

Tell us where your store is today. We will prioritize brands where product data improvements can create measurable visibility upside.

  • Real prompts, your category

    We test the natural-language buying intents that drive your traffic — not generic questions.

  • Per-SKU diagnosis

    Missing attributes, weak pages, schema gaps, feed inconsistencies — all surfaced at the SKU level.

  • Approval-first by default

    Nothing ships to your storefront without your sign-off unless you opt into autopilot for low-risk fixes.

Manage ecommerce clients? Tick the agency box below — we route those separately.

https:// added automatically if missing

Optional — helps us prioritize

Pick one or more

Optional

We use this only to qualify your pilot application. See our privacy policy.

Questions

Frequently asked questions

  • Can you guarantee my products will be recommended by ChatGPT or Google AI Mode?

    No. No vendor can control independent AI answer engines. Mentionator improves the product data, pages, structured data, and feeds that help AI shopping systems understand and match your products.

  • How is this different from SEO?

    Traditional SEO optimizes pages for search results. Mentionator optimizes product evidence for AI shopping recommendations: prompts, product attributes, schema, collections, feeds, and prompt-to-product matching.

  • How is this different from a product description generator?

    A description generator rewrites copy. Mentionator tests AI shopping prompts, diagnoses SKU-level gaps, updates product data and pages, and retests visibility.

  • How is this different from a feed optimization tool?

    Feed tools focus on feed completeness and ad/listing requirements. Mentionator combines prompt testing, product-page optimization, schema, collections, feed gap analysis, and AI shelf-share measurement.

  • Do I need to be on Shopify?

    The pilot is Shopify-first because Shopify gives us the fastest path to catalog automation. Other platforms can join the waitlist.

  • What data do you need?

    At minimum: store URL, Shopify catalog access, product pages, collections, and category priorities. Optional: Merchant Center, Search Console, reviews, and analytics for deeper optimization.

  • Will this change my live store automatically?

    The default pilot mode is approval-first or guarded autopilot. Brands can choose draft-only, approval-required, or auto-publish for low-risk changes.

  • How long does it take to see results?

    Catalog and page improvements can be shipped quickly, but AI and search systems may take time to crawl, refresh, and change recommendations. The dashboard shows shipped actions immediately and visibility changes over time.

  • Do you create fake reviews or ratings?

    No. Mentionator only uses legitimate, visible, authorized review data and never fabricates social proof.

  • Can agencies use this for clients?

    Yes. Agency access is available for ecommerce SEO, growth, and Shopify agencies managing multiple stores. Tick the agency box in the pilot application and we will route accordingly.

Still have a question? Drop us a line — hello@mentionator.com

Apply for the pilot
Pilot · Open

Ready to get your products recommended by AI shoppers?

Connect Shopify, choose priority categories, and Mentionator gets to work on your AI shopping visibility — measured, fixed, retested.

Apply for the pilot

No credit card · Approval-first by default