E-retail
The new commerce divide: Shopping GPT, when machines shop for humans
Henri de Bouteiller
Co-founder & CEO
5
min read
Why 54% of customers now shop through AI instead of your website
Picture this: Your best-performing customer segment isn't scrolling your homepage anymore. They're not even opening your app. In fact, 54% of purchase decisions now begin with a conversation—but neither on your website, nor in your store. They're talking to ChatGPT, Claude, or Perplexity, asking: "Find me the best noise-canceling headphones under $300 with at least 20 hours of battery life and fast delivery."
Welcome to 2025, where your most valuable customer is a machine that never gets tired, never gets emotional, and always compares your product against every competitor in milliseconds.
This isn't a trend. This is the tipping point where traditional e-commerce crashes into obsolescence. The question isn't whether you'll need to adapt—it's whether you'll recognize you're already invisible to half your potential customers.
How AI killed the traditional marketing funnel
Remember when we obsessed over awareness → consideration → conversion? That was last year's playbook. Today's reality looks dramatically different:
Traditional funnel: Customer sees ad → visits homepage → compares products → adds to cart → checks out
AI agent funnel: Customer states need → Agent evaluates options → Direct purchase
The numbers are staggering. OpenAI's partnership with Shopify isn't just another integration—it's potentially 1 billion customers who will never see your carefully crafted homepage, your seasonal banners, or your persuasive product descriptions. They'll bypass everything you've invested in and go straight to the agent's recommended selection.
Think about your marketing budget. How much are you spending to reach customers who will never see your content because their AI assistant has already made the decision?
How competitors outsell you with better product data structure
Last month, I worked with a premium European fashion brand—€200M annual revenue, 15 years of market leadership, #1 on Google for their top keywords. They were bleeding traffic from AI-powered shopping assistants.
The culprit? A competitor with worse SEO, lower brand recognition, but superior structured data. Their products showed up in AI recommendations. My client's didn't.
Within 48 hours of ChatGPT launching its shopping agent, their organic search referrals from AI platforms dropped 40%. The competitor's rose 200%.
The harsh truth: 73% of products are invisible to shopping agents due to poor data structure. Your beautifully designed product pages might as well not exist if AI can't parse them.
In a nutshell, you need to have well structured, rich, detailed product data.
Google's SEO no longer guarantees AI visibility. You can be #1 on Google and #nowhere on GPT.
Product data: why is it your new brand identity and best asset for AI Agents
Here's what should keep you up at night: Your brand's identity is shifting from perception-based to data-driven. AI agents don't care about your heritage story or your brand values—they care about specs, availability, and delivery terms.
This is the new brand identity stack:
Structured product specifications: The agent's first impression
Real-time inventory feeds: Your reliability score
Shipping data: Your competitiveness factor
Return policies in machine-readable format: Your trustworthiness metric
Beyond the traditional PDP, you need machine-readable brand narratives. What problems does your product solve? What use cases does it excel at? What's the context of its value? If an AI can't understand this, your product becomes a commodity.
The most sophisticated brands understand that product data isn't static—it's a living, evolving narrative. Asia is already leading the way : recently, I was on the phone with the SMCP team in Asia and they were explaining me how they dynamically updated their product descriptions for different moments:
For Mother's Day, their black handbags were recontextualized as "the perfect gift for showing appreciation."
The same bag for Valentine's Day became "an elegant companion for romantic evenings."
Even for Lady Gaga's concert tour, they adjusted descriptions to emphasize "the dress that Lady Gaga could wear."
This contextual evolution is what AI agents now expect. They're looking for products that match not just specifications, but situations, emotions, and cultural moments. Your product data needs to pulse with the rhythm of real life.
Think FAQ-style structured data: proven for SEO today, essential for tomorrow's AI search landscape.
Trust isn't earned through marketing anymore—it's calculated through consistency, delivery reliability, and data accuracy.
How to optimize your products for AI shopping algorithms
Understanding machine decision-making is fundamentally different from understanding human psychology. AI agents evaluate:
Exact specification matching to user requirements
Price-to-value ratios across the entire market
Delivery speed and certainty
Return policy flexibility
Verified review consistency
Building product feeds isn't just technical SEO—it's storytelling for machines. Your product descriptions need to answer:
What specific problems does this solve?
In what situations is this the optimal choice?
What are the measurable benefits versus alternatives?
What are the concrete use cases and life moments where this excels?
Ask yourself: If an AI agent had to choose between your product and a competitor's based purely on data, what makes yours the obvious choice?
Your API integration strategy determines your market presence. Be where AI agents shop:
Marketplace integrations
Comparison engines
Shopping aggregators
Product databases
The cross-border pricing revolution means you're no longer competing locally. When AI agents can instantly compare prices across borders, your pricing strategy needs global awareness.
To finish, you must AB test. You need to test dozens of different format and data structure to find the one that works best for your industry/product/clients.
Building human experiences in an AI-shopping world
Paradoxically, as machines take over initial product discovery, the human experience becomes more critical—but different.
Your website transforms from a conversion funnel to a task completion hub. People arrive with specific needs:
Complex purchase questions the AI couldn't answer
Brand experience they can't get from an agent
Post-purchase support
Product discovery that requires human touch
Create post-purchase experiences that earn AI recommendations. If an agent sees high customer satisfaction scores, fast shipping, and easy returns, your product becomes its preferred choice.
Building brand loyalty when customers never see your brand requires rethinking everything. You need to create value that AI agents recognize and communicate to their users.
Strategic priorities for AI-driven ecommerce success
Your organization needs to evolve. New critical roles emerge:
Product data strategist: Translates brand story into machine-readable formats
AI partner manager: Maintains relationships with AI platforms
API distribution lead: Ensures product visibility across agent-accessible channels
The investment priority shifts dramatically. Traditional marketing budget needs reallocation toward data infrastructure. The ROI of perfect product data now exceeds the ROI of marketing automation.
Here's your 12-month roadmap:
Months 1-3: Audit and structure your product data
Months 4-6: Implement API integrations across major platforms
Months 7-9: Optimize for AI agent requirements
Months 10-12: Build feedback loops to improve agent recommendations
The bridge to machine-human commerce
This isn't about replacing marketing—it's about expanding it to a new audience. Your challenge is serving both machines and humans through unified product intelligence.
Here's the paradox that will define successful brands in 2025: While AI agents do the shopping, humans retain veto power. That final "confirm purchase" button remains firmly in human hands, and this is where brand significance reaches its apex.
The most powerful position in this new ecosystem? Being in the customer's preferred brand list. Imagine hearing customers say to their AI assistant: "Find the best deals on TVs, but only show me Samsung, LG, or Sony." This explicit brand preference becomes your ultimate moat.
AI shopping agents will become the most sophisticated customer knowledge engines ever created. They'll understand purchase patterns better than any CRM:
Which brands each user consistently chooses over alternatives
Which features matter most in their decision-making
Their price sensitivity thresholds
Their seasonal shopping behaviors
Perplexity and ShoppingGPT aren't just shopping assistants—they're becoming the world's deepest repositories of actual customer preference data. They know not just what users say they want, but what they actually buy.
The convergence point is product content that serves both:
Technical specifications that AI agents understand
Stories and context that humans connect with
Data that drives decisions
Emotions that drive loyalty
The future belongs to brands that recognize this truth: AI agents research, but humans ultimately choose. Build your brand so strongly that customers include you in their AI instructions. Create experiences so remarkable that AI agents observe your repeat purchase patterns and recommend you automatically.
The brands that master this transition won't just survive the AI shopping revolution—they'll define it. Are you ready to speak fluent AI while keeping your human heart?
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At Newtone, we understand this fundamental shift. Our AI copywriter doesn't just create content—it builds the bridge between human brand stories and machine understanding. We translate your brand's unique voice into the structured data that AI agents need while preserving the emotional resonance that connects with human customers. Because in this new era, the most powerful brands are those that speak both languages fluently.
