For years, search has been relatively predictable. SEO, we know what we're doing.
A customer would type:
"Dog food"
Or perhaps:
"Best dog food for sensitive stomachs"
Your job was to rank for those keywords, optimise your product pages, build backlinks and hope Google sent traffic your way.
But search behaviour is changing rapidly.
Today, customers are increasingly turning to ChatGPT, Gemini, Claude and AI-powered search experiences with questions that sound much more like conversations:
"I'm looking for a new dog food for my 6-year-old whippet who has historically had an upset tummy from grains. He really likes Beco chicken and vegetable kibble and tends to prefer kibble over wet food, but we're open to alternatives that may suit."
That's not a keyword.
That's a buying brief.
And it's changing everything.
The Difference Between Search Engines and AI Assistants
Traditional search engines return a list of websites and ask the customer to do the research.
AI assistants do the research for them.
Instead of presenting ten blue links, they analyse thousands of pieces of information and attempt to provide a direct recommendation.
In many cases, the customer may never visit a search results page at all.
The challenge for brands is simple:
If AI can't understand your products, expertise and trustworthiness, it can't recommend you.
Let's See How An AI Thinks
Take our whippet owner.
The AI isn't looking for a page that simply contains the phrase "dog food".
It's trying to understand:
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Dog age (6 years old)
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Breed (whippet)
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Digestive sensitivities
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Grain intolerance
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Existing food preference
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Kibble preference
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Chicken flavour preference
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Potential alternatives
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Brand comparisons
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Customer sentiment
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Nutritional suitability
An LLM effectively creates a profile of the dog and then looks for evidence across the web to determine suitable recommendations.
That means your website needs to provide far more context than simply:
"Premium Chicken Dog Food."
What Needs To Exist On Your Website?
1. Rich Product Information
Most product pages aren't detailed enough.
AI models need structured information such as:
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Suitable age ranges
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Breed suitability
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Grain-free status
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Protein source
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Digestive benefits
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Feeding recommendations
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Ingredient breakdown
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Allergens
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Texture (kibble, wet, mixed)
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Product comparisons
The more context you provide, the easier it becomes for AI to understand exactly when your product should be recommended.
2. Helpful Content, Not Just Product Content
Many brands still separate content and commerce.
AI doesn't.
A great dog food website should contain content such as:
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Best dog foods for sensitive stomachs
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Grain-free vs grain-inclusive diets
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Feeding advice for whippets
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Choosing food for older dogs
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Kibble vs wet food comparisons
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Common digestive issues in dogs
Every article creates additional context that helps AI understand where your brand is relevant.
The Importance Of Entity Building
AI models don't think in keywords.
They think in entities and relationships.
For example:
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Beco = Dog food brand
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Whippet = Dog breed
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Grain-free = Nutritional attribute
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Sensitive digestion = Health consideration
The stronger these relationships become across your website, the easier it becomes for AI to connect your products with relevant customer needs.
Product Schema Is No Longer Optional
Schema has always been useful, and Shopify handles 75% of this natively (cheers Shopify!) but there is more that can be done, and that's where we come in!
For AI search, it's essential.
Structured data helps machines understand:
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Product names
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Ingredients
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Ratings
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Reviews
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Pricing
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Availability
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Brand relationships
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FAQs
Proper implementation of:
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Product Schema
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Review Schema
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FAQ Schema
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Article Schema
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Organisation Schema
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Breadcrumb Schema
creates a cleaner, more understandable source of information for search engines and AI systems alike.
Trust Signals Matter More Than Ever
AI models don't just look at products.
They look for confidence.
Strong trust signals include:
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Verified customer reviews
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Expert endorsements
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Veterinary guidance
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Awards
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Certifications
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Transparent ingredient sourcing
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Clearly stated policies
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About Us content
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Author profiles
The more evidence of authority and trustworthiness available, the more likely your brand is to be surfaced.
Technical Foundations Still Matter - this is where we come in!
AI visibility starts with great content, but technical foundations are what allow systems to access and understand it.
This includes:
Clear Site Architecture
AI systems need logical relationships between content.
For example:
Dog Food → Grain-Free Dog Food → Sensitive Stomach Dog Food → Chicken Kibble
Internal Linking
Strong internal linking helps AI understand topical authority and relationships between pages.
Accessibility & ARIA Labels
Many AI systems rely on the same signals that improve accessibility.
Proper implementation of:
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Semantic HTML
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ARIA labels
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Accessible navigation
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Descriptive buttons
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Logical heading structures
helps machines interpret content more accurately.
Fast Performance
Slow websites create barriers for both users and crawlers.
Performance remains a critical ranking and discoverability factor.
The New Shopify Agentic Dashboard
Shopify clearly sees where search is heading.
Its new Agentic Commerce reporting provides insight into how AI agents and conversational commerce experiences are interacting with your store.
For the first time, merchants can begin to understand:
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AI-driven referrals
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Agent interactions
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Emerging discovery channels
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Product visibility within AI ecosystems
This data is still evolving, but it represents a major shift in how brands will measure visibility over the next few years.
The brands that start monitoring and improving these signals today will have a significant advantage over those waiting for AI search to become mainstream.
The Big Question
If a customer asks ChatGPT:
"What's the best grain-free kibble for a 6-year-old whippet with a sensitive stomach?"
Would your brand be recommended?
More importantly:
Would there be enough information available online for AI to understand why it should recommend you?
For many brands, the answer today is no.
Start Getting Your Agentic Ducks In A Row
The good news is that most businesses don't need a complete website rebuild.
They need a clear strategy.
The foundations typically include:
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Product data enrichment
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Structured content creation
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Schema implementation
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Technical SEO improvements
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Accessibility enhancements
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Entity building
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Trust signal optimisation
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AI visibility monitoring
The brands that invest now will be significantly better positioned as customer discovery shifts from traditional search engines to AI-powered recommendations.
At twotwentyseven, we're already helping brands prepare for this shift through AI visibility audits, technical reviews and practical roadmaps designed for Shopify merchants.
Because the question is no longer whether customers will use AI to discover products.
They're already doing it.
The question is whether they'll discover yours.
Get in touch with our team to have a quick chat, schedule an audit and get things updated!
