Win the AI shopping cart
before the click ever happens.
ChatGPT Shopping, Perplexity, and Google AI Overviews now recommend the products consumers buy. GeoGenie makes sure the answer ends with your SKU - not your competitor's.
Used by DTC, marketplace, and global retail brands across beauty, fashion, electronics, and lifestyle.
E-commerce just lost
the search bar.
For 20 years ecommerce growth meant one thing: rank for the head keyword, win the click, drop the user into a PDP. That model is breaking in two places at once. Consumers are starting product research inside an AI chat - "what's the best moisturizer for sensitive skin under $30", "compare DJI Mini 4 Pro vs Mavic 3", "running shoes for flat feet" - and they're getting back a finished recommendation with three named products, not a list of ten blue links. ChatGPT Shopping and Perplexity also surface live pricing and inventory directly inside the answer.
The brands cited inside that answer get the consideration. Everyone else gets nothing - no impression, no click, no chance to retarget.
Ecommerce teams have two specific problems no generic AI search tool will solve. First, your catalog has thousands of SKUs and AI engines need a separate piece of crawlable context for each one. Second, models lean heavily on third-party comparison content, review platforms, and category guides to recommend - and most ecommerce sites have zero footprint in those sources.
GeoGenie was built around both problems.
How the 3-Pillar framework
applies to ecommerce.
Trust Layer - PDP and category page optimization
We audit every priority PDP, category page, and buyer's-guide template against the structured signals AI models actually use to assemble shopping recommendations: schema.org Product markup, FAQPage, comparison tables, sizing and fit data, ingredient lists, materials and care, return windows. Most catalogs have 30-60% of this missing at scale - and the fix is mechanical.
Scale Layer - one page per buyer question, not one per SKU
The pages that win ecommerce AI search are not your PDPs - they're your comparison and use case pages. "Best foundation for oily skin", "camera for solo travel under $1500", "running shoes for plantar fasciitis". We map every priority prompt to a page that should exist - either a new comparison page, a refreshed category page, or a buyer's guide - and prioritize the build queue by AI traffic potential. A category like skincare or consumer electronics typically produces a queue of 200-400 net-new high-intent pages in the first audit.
Signal Layer - the citation supply chain for shopping
AI shopping recommendations don't come from your site - they come from a small set of trusted off-site sources: vertical review sites, niche community forums, expert publications, and increasingly Reddit. We map the exact set models reference for your category, then run citation outreach to close the gap. For a DTC mid-market skincare brand that might mean 40 placements across dermatology blogs, beauty editor newsletters, and r/SkincareAddiction over a quarter.
The 8 steps, sized
to ecommerce velocity.
- 1
AI Visibility Health Check across catalog, category pages, and buyer's guides.
- 2
Topic Selection by margin contribution and category share, not just volume.
- 3
Prompt Identification mapped to your specific awareness, consideration, and conversion funnels.
- 4
Target Prompts and Pages Mapping - one page per query variation.
- 5
Citation Landscape Analysis of the third-party sources models actually trust in your category.
- 6
On-site Content and Technical Execution - PDP schema, comparison tables, buyer's guide briefs.
- 7
Off-site Content Strategies - review placements, niche outreach, community presence.
- 8
Measurement and Impact - AI citation frequency, AI-attributed sessions, AI-attributed revenue.
Measurable wins
ecommerce teams actually see.
Move from rank #7 to rank #1 in category-level prompts within 60-90 days for the brands that ship the on-site work consistently.
+30-50% lift in branded search after AI exposure - when an AI surfaces the brand, branded queries follow within days.
Detectable AI-attributed revenue - once UTMs and referrer analysis are set up correctly, attributable AI traffic typically converts at 1.5-2x the rate of cold organic.
Specific use cases
by sub-category.
Beauty and skincare: dedicated page per active ingredient, per concern, per skin type; ingredient knowledge graph in schema; expert and dermatologist citation outreach.
Fashion and apparel: size and fit data in structured markup; outfit and occasion buyer's guides; influencer and editorial review placements.
Consumer electronics: comparison page per model pairing ("X vs Y"); spec normalization in schema; tech review site placements.
Home and lifestyle: material, dimension, and care data in structured markup; project and room-based buyer's guides.
Marketplaces and multi-brand retailers: brand-level visibility tracking per private label, category-level share of voice, supplier citation mapping.
How GeoGenie works
for e-commerce brands.
Seven products. One goal: make AI search engines mention, cite, and recommend your products.
50%
of consumers already use AI-powered search today
McKinsey AI Discovery Survey, n=1,927
$750B
of consumer spend will flow through AI search by 2028
McKinsey
ContextGenie - map who's asking AI about your category
Our multi-agent research system maps the shopping personas, product categories, and discovery contexts where your brand should appear in AI recommendations. It identifies which competitor brands appear alongside you in AI answers, which buyer types are searching your product category, and what contexts trigger AI to recommend (or ignore) your brand. Every other GeoGenie product depends on ContextGenie's output - it's the foundation. The Content Guidelines you set here teach GeoGenie your tone, vocabulary and brand rules once, and shape everything it writes afterwards.
PromptsGenie - predict the exact queries shoppers use
See the prompts driving product discovery in your category - like "best running shoes for flat feet under $150" or "top sustainable skincare brands for sensitive skin." PromptsGenie predicts both broad Coverage prompts (your head-term category) and commercial Depth prompts (high-intent queries where AI gives a specific shortlist). Win the depth prompts, and you'll start winning the broader category recommendations too.
MonitoringGenie - track your AI visibility in real time
Monitor your brand's Visibility %, Share of Voice, and Citation Rate across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. See exactly when competitor brands get recommended instead of yours. Prompts are organized by product category so you can track performance at the category and individual query level, and every prompt carries Action Suggestions - the on-site, off-site and UGC/social sources behind that answer, each with a recommended next action.
CitationsGenie - understand why AI recommends them, not you
Analyze the citation supply chain for your product categories. See which domains AI engines pull from when answering product recommendation questions - whether that's review sites, editorial roundups, comparison pages, or retailer blogs. If competitors' product content is getting cited but yours isn't, CitationsGenie shows you whether the gap is about content structure, freshness, or where you're publishing. Cited domains that accept placements surface as publisher-network offers, so you can earn a citation on a domain the AI already trusts.
ActionsGenie - get content briefs that put your products on the list
Turn visibility insights into action. ActionsGenie generates GEO-optimized content briefs - and turns them into full article drafts - across three tiers: on-site (product pages, buying guides, comparison content), off-site (press coverage, affiliate roundups, review platform content), and social. Specialised agents cover Reddit engagement, earned-media articles, and YouTube metadata. GeoGenie's integrated publisher network gives you access to branded articles, third-party mentions, and publication placements at exclusive partner rates - turning briefs into published placements without sourcing publishers yourself.
SiteGenie - make your product catalog AI-ready
Audit your product pages and site architecture for AI crawlability. Get structured data and schema recommendations (Product schema, Review schema, FAQ schema) so generative engines can properly parse your catalog and surface your products in recommendations. If AI can't correctly read your product pages, it can't recommend them. SiteGenie also surfaces internal-linking opportunities and audits how clearly your site establishes your brand as an entity AI engines recognise.
BotsGenie - see when AI is actively recommending your products
GA4 can't see AI agent traffic - bots don't run JavaScript. BotsGenie reads your CDN logs to classify every AI bot visit: Citation (your product page is answering a live shopper's query right now), Indexing (AI is cataloging your catalog for future recommendations), or Training (AI is learning from your content). Overlaid with GA4, the Overview connects the whole chain: bots crawl, AI cites, those answers send shoppers back, and those sessions convert.
Three scenarios where
e-commerce brands use GeoGenie.
New product launch
You've launched a new product, but AI engines are still recommending established competitors. Use ContextGenie and PromptsGenie to identify the category queries your launch needs to win, then ActionsGenie to build the content that gets your new product into AI recommendations immediately.
Category dominance
You're the market leader, but AI keeps recommending niche competitors when shoppers ask about your category. MonitoringGenie shows you exactly which queries you're losing. CitationsGenie reveals why competitor content gets cited over yours. ActionsGenie builds the briefs to close the gap across your product catalog.
Competitive defense
A competitor is being recommended every time someone asks AI for the type of product you both sell. MonitoringGenie pinpoints every prompt where you've been displaced. CitationsGenie reveals the content strategy driving their AI visibility. ActionsGenie gives you a clear plan to get back on the list.
Why ecommerce teams
pick GeoGenie.
Built for catalogs with hundreds to hundreds of thousands of SKUs, not single-landing-page brands.
Schema and structured data depth that traditional SEO tools don't cover - we audit not just for Google but for the retrieval models behind ChatGPT, Perplexity, and Gemini.
Off-site placements through our Publisher Network - the part of ecommerce GEO no monitoring tool can do.
Revenue attribution baked in, not bolted on.
See exactly where your catalog stands in AI shopping today.
Submit your domain and category. We'll return a free audit showing how often AI engines recommend your top 25 SKUs vs. your three closest competitors - by engine, by prompt, by margin.