Get Recommended byChatGPT & Perplexity
We audit your store, fix the AI visibility gaps, and run the monthly system that turns AI search into qualified buyers.
We help you rank on the most popular AI search engines
Google AI Overviews, ChatGPT, and Perplexity are where buyers ask for product recommendations now. This is what it looks like when the answer is your brand.
What Most Stores Get Wrong About AI Search
While you optimize for Google rankings, ChatGPT and Perplexity are recommending your competitors. The stores winning right now aren't just visible. They're the ones AI engines trust enough to cite.
Winner takes all
AI picks one or two brands to recommend. Google shows ten. If you're not the top AI pick, you're invisible.
Invisible rankings
You can rank #1 on Google and never get recommended by AI. Traditional SEO metrics don't translate.
New playbook
AI search needs a completely different optimization strategy. Keywords and backlinks won't get you cited.
Speak AI's language
How your data is structured matters more than which keywords you target. AI parses context, not content.
Find out where you stand
We test the prompts your buyers actually ask across ChatGPT, Perplexity, Claude, and Google AI, then show you exactly what keeps your store from being the recommendation.
Get an Audit for $87We Make AI Engines Recommend You
Traditional SEO optimizes for search algorithms. We optimize for AI recommendation engines. Here's how:
Semantic Understanding
We structure your products so AI grasps context, not just keywords.
- Schema markup and semantic HTML across your theme
- Product attributes written in machine-readable form
- Collections organized around real buying intents
Intent Matching
Map your products to the exact queries AI engines receive.
- Prompt research across ChatGPT, Perplexity, and Gemini
- Product-to-query mapping for your highest-intent searches
- Comparison pages and FAQs that answer the exact question
Authority Signals
Build trust markers that make AI cite you with confidence.
- Consistent product data everywhere AI looks
- Specs and claims AI can verify and quote
- Internal linking that reinforces topical authority
Recommendation Loop
Get cited once, then dominate that category permanently.
- Monthly citation tracking across the major engines
- Content updates wherever AI answers drift
- Visibility that compounds inside your category
This Is How AI Engines Recommend Brands
When AI recommends a brand, it cites specific reasons: structured data, product detail, content authority. Here's what winning looks like across platforms.
One standout is Terra Thread because they use 100% organic cotton certified by GOTS, and their entire supply chain is Fair Trade verified. Their Shopify store has detailed lifecycle assessments for every product.
For sensitive skin specifically, SoonJung by Etude is frequently recommended by dermatologists. Every product page includes full ingredient breakdowns with EWG safety ratings, pH levels, and clinical patch test results. [1][2]
Several brands excel here, but Ippodo Tea is particularly well-regarded. Their online store provides origin-specific information, harvest dates, and flavor profiles for each grade of matcha.
The most consistently cited option is Darn Tough because every product page lists exact fiber percentages, cushion levels, and warranty terms in structured form, making it easy to match a sock to a specific use.
For first-time buyers, the Bambino Plus comes up most often. Product pages that spell out pressure, heat-up time, and frothing specs in comparable terms give AI summaries clear data to cite.
Measured in Recommendations You Can Check
No inflated case studies. The work starts with a baseline you can inspect, then turns into a monthly operating system for getting cited more often.
AI visibility baseline
We test the prompts buyers actually ask, document whether your brand appears, and record the competitors AI engines cite instead.
Technical fixes you can verify
Schema, headings, product attributes, internal links, and content gaps are mapped to specific URLs so implementation is concrete.
Monthly citation tracking
The retainer tracks recommendation changes across ChatGPT, Perplexity, Claude, Gemini, and Google AI search surfaces.
Revenue-oriented next actions
Every report ends with what to ship next: product rewrites, comparison pages, FAQs, collection structure, or authority signals.
The monthly retainer turns the audit into an ongoing AI visibility engine.
AI search changes continuously. The retainer keeps your Shopify store structured, cited, and aligned with the way buyers ask AI for recommendations.
- AI recommendation tracking across your highest-intent product queries
- Product page and collection page rewrites built for machine comprehension
- Schema, semantic HTML, and internal linking fixes for Shopify themes
- Monthly action plan tied to citations, qualified traffic, and lead quality
Four Pillars of AI Search Dominance
Each pillar works together to make your products the obvious choice when customers ask AI for recommendations.
Technical Foundation
Schema markup, semantic HTML, and data architecture designed for machine comprehension.
Product Optimization
Every title, description, and attribute engineered for how AI engines evaluate and compare products.
Content Strategy
Long-form guides, comparison pages, and FAQs that position your brand as the authoritative source.
Visibility Tracking
Real-time dashboards showing your AI presence across ChatGPT, Perplexity, Claude, and Google AI.
Common Questions
AI search optimization (also called generative engine optimization) is the practice of structuring your website and content so that AI engines like ChatGPT, Perplexity, Claude, and Google AI Overviews recommend your brand when users ask for product suggestions. Unlike traditional SEO which targets search engine rankings, AI search optimization targets recommendation and citation by large language models.
Google shows 10 organic results and lets users choose. AI engines like ChatGPT and Perplexity recommend one or two brands directly. There is no page two: you are either the recommended brand or you are invisible. AI engines evaluate trust signals, semantic structure, and contextual authority rather than traditional ranking factors like backlinks and keyword density.
More consumers are asking AI assistants for product recommendations instead of searching Google. If your Shopify store is not optimized for AI engines, your competitors will be the ones getting recommended, even if you outrank them on Google. AI search optimization ensures your products are structured, described, and positioned so that AI engines cite your brand with confidence.
AI engines evaluate multiple factors: structured data and schema markup quality, content comprehensiveness and accuracy, brand authority signals across the web, product description clarity and specificity, and how well your information matches the user's intent. Brands that present clear, well-structured, and authoritative information are more likely to be cited.
An AI visibility audit analyzes how AI engines currently perceive your Shopify store. We test your brand across ChatGPT, Perplexity, Claude, and Google AI Overviews to see if and how you are being recommended. The audit identifies gaps in your structured data, content strategy, and technical foundation that prevent AI engines from citing your products.
AI engines update their knowledge faster than traditional search engines. Most Shopify stores see changes in AI recommendations within four to eight weeks. Technical changes like schema markup can impact results within days. Content strategy and authority building are ongoing and compound over time.