Retail Unbundling

OpenAI, Gemini, Perplexity, and Grok are not just changing how people search — they’re reshaping how people shop. The era where your homepage acted as the main entrance to your retail world is fading. Now, answers and product links are increasingly delivered straight from AI-powered assistants built on LLMs (Large Language Models). In my research, I’ve found that traffic coming from LLMs is 9 times more valuable than traditional search traffic. Once these LLMs have access to your credit card details, they’ll begin shopping for you. The future belongs to agentic e-commerce.

For traditional retailers, this means the customer journey to your product no longer passes through your digital storefront. Consider DayDream, a startup that recently launched a personal shopping agent. When AI becomes the curator, advisor, and shopping guide—what happens to the digital mall? It’s headed for extinction. I see three major strategies to survive the unbundling of e-commerce.

What Retail Can Learn from Media’s Unbundling

In times of transformation, history often provides insight. When was the last time technology caused a market to fragment? The media industry during the rise of social internet offers a clear example. What happened ten years ago?

As HTML and social media reshaped media consumption, the homepage lost its dominance. Readers no longer started at whatevernews.com; instead, they landed directly on a specific article discovered via Facebook, Twitter, or Google. The article became the fundamental unit of value. Media brands faded into the background. Many downsized, with only top-tier outlets like The New York Times or The Economist managing to adapt and build new business models.

Retail is now undergoing a similar disruption, and we will again witness the decline of the homepage, the rise of creators/producers, and the dominance of aggregators.

The End Of Amazon, BestBuy, Walmart As We Know Them

Amazon, BestBuy, Walmart — these giants have long been the “homepages” of shopping. Customers typed in the URL, searched for products, and navigated their platforms. But as AI becomes the new interface, those direct entry points are weakening, much like the media homepage did.

Why would someone visit bestbuy when they can simply ask an AI: “What’s the best washing machine for a small apartment with eco features?” The LLM won’t show a homepage — it will return the best answer, wherever that information resides.

This shift makes traditional e-commerce retailers vulnerable. Unless they adapt, Amazon, BestBuy, Walmart, and others risk becoming irrelevant.

The Three Strategies For E-Commerce Retailer

Just as media companies had to reinvent themselves, so too must online retailers. Here are a few potential paths forward:

Price Leadership - The Walmart Model

Price remains a key factor. LLMs will query retailers — likely using protocols like MCP (Model Context Protocol) — about pricing. If competitive pricing wins, then companies like Walmart with strong purchasing leverage will come out ahead. Being the cheapest comes with razor-thin margins, but works at scale.

Distribution Network Leadership - The Amazon Edge

Delivery still matters. Speed and reliability remain crucial. While Amazon's homepage may fade, its logistics network, speed, and convenience give it a major edge. They’ve built the most efficient delivery system in the world.

Content And Advisory Leadership

This third strategy is just beginning to take shape. Similar to how content drove clicks in media, content will also drive engagement in retail. Retailers that offer expert advice will thrive.

Forget Best Buy — think Tom’s Guide, which delivers trusted tech insights. Forget Walmart — think REI, the leader in outdoor gear. Offer genuine advice, curated selections, and personalized shopping experiences. This is where AI opens opportunities.

In my work, I see many retailers wanting to be part of the LLM conversation. I’ve written about Answer Engine Optimization (AEO) and what brands need to know in this Forbes article. The core idea: LLMs will learn from authentic and original content. Sometimes called Generative Engine Optimization (GEO) or LLMO (LLM-Optimization), this approach rewards brands that provide unique perspectives on real questions. Those who do will stay relevant to LLMs.

This is the future for new brands. Just as the media world saw the rise of niche bloggers like Ben Thompson — who sells specialized knowledge — we’ll see retail brands focusing on areas general LLMs don’t yet cover. Best advice for vitamins beyond the usual suspects? Deep expertise in hardware installation? Leading voices in fashion? That’s where the opportunity lies.

If big brands want to seize this moment, they’ll need to become multi-brand platforms. Launching niche micro-brands, each tailored to a specific audience and powered by AI-driven personalization.

The Future Will Be More Targeted And More Personalized

Envision the new landscape of e-commerce.

• A landing page that adjusts to your taste in home decor.
• Product recommendations generated dynamically based on lifestyle, not just clicks.
• Influencer-curated collections surfaced through LLMs.
• Site-search that feels like a chat-GPT experience.

This is retail reimagined — not for a homepage, but for a world where every page is a landing page.

Expert Knowledge - The Winner Of Retail Unbundling

Just as the media world now thrives on niche creators, so too will e-commerce. Big changes are coming. Two and a half years ago — when LLM excitement first began — I predicted on my podcast that the future would be “indie.” That’s exactly what we’re seeing unfold in retail today.

The winners will be those who embrace specialization, personalization, and advisory strength. Not everyone needs to be Amazon, Walmart, or Best Buy. But everyone needs a plan for the age of AI discovery.

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