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Why E-Commerce is Broken, and How Agentic Commerce Fixes It

The essentials
Where the model breaks : brands accept a 2-3% conversion rate while relying on ads built for clicks, product pages overloaded with information and filters that miss context.
Why shoppers leave : the burden of research sits entirely with them, so when they cannot find what they want they bounce, or increasingly ask an AI assistant instead.
What replaces it : agents that anticipate intent, personalize results and guide the shopper like a trusted advisor, which turns browsing into buying.
What it produces : at Mon Lit Cabane, post-conversation conversion reached 8%, average order value rose 30%, and more than €1M in incremental revenue came in over three months.

 

The traditional e-commerce flow hasn’t fundamentally changed in nearly two decades. Brands are stuck accepting a measly 2-3% conversion rate. Agentic commerce stands to replace this broken e-commerce model to drive better results for shoppers and retailers. Here we’ll break down why traditional e-commerce storefronts are failing and why agentic commerce is rising up to take its place.

Most E-Commerce Brands Still Struggle to Drive Conversions and Deliver Great UX

Even top brands suffer from high bounce rates, low conversions, and an underwhelming user experience. Why? They tend to rely on:

  • Ads optimized for clicks, not experience
  • Static PDPs overloaded with information
  • FAQ sections that go unread
  • Search bars and filters that miss context
  • Passive chatbots that wait for engagement
  • Analytics and A/B testing tools only give incremental improvements

Retailers overwhelm shoppers with choices, but fail to guide them to the right decision and drive the sale—despite having access to more customer insights than ever. The burden ultimately rests on every shopper to research and find what they want. When they can’t, they bounce… or increasingly, they use AI.

Agentic Commerce: New E-commerce Shopping Behaviors and Expectations

Fed up with poor online shopping experiences, consumers are turning to genAI assistants like ChatGPT, Gemini, and Perplexity to help them shop, bypassing traditional search and endless browsing across PDPs altogether. Adobe reported a 1200% increase in generative AI-driven traffic to retail sites just since July of 2024. 

Traditional Search vs. Agentic Commerce Search


The shift makes sense, consumers want instant, curated results with less effort.

Traditional storefronts can’t deliver that. But ahead-of-the-curve retailers implementing agentic commerce tactics can, and they’re already starting to.

Agentic Commerce Drives Bigger, Faster Wins for Retailers

USMonLitCabane_Convstarter-ezgif.com-optimizeAI shopping agents anticipate intent, personalize results, and guide the shopper like a trusted advisor. Agentic commerce succeeds where traditional e-commerce fails: turning browsing into buying. 

Children’s furniture brand Mon Lit Cabane rolled out an
AI shopping assistant on product pages to help proactively
guide parents to the right piece of furniture. The impact?  

  • Engagement on PDPs skyrocketed
  • Post-conversation conversions hit 8%
  • Average order value rose 30%
  • More than €1M in incremental revenue was generated
    in just three months

…and this is just one of many examples. 

When retailers stop making shoppers do all the work, and instead guide them with AI-backed confidence, the shopping experience becomes a win-win.

Three Takeaways for E-Commerce Leaders

1. Stop relying on the browse-and-hope model.

PDPs need to be proactive decision engines, not static brochures. Reframe your highest-intent pages as guided experiences that anticipate and curate to go from doubt to purchase more seamlessly.

2. Get your data ready for agentic commerce.

To be discoverable by AI agents, retailers must structure product data, enable secure APIs, and implement “agentic SEO” so their catalog can be indexed and surfaced in conversational queries. Forward-looking brands are already making LLM optimizations today to prepare for agent-driven transactions.

3. Launch fast, learn faster.

Retailers don’t need to rebuild from scratch: they can launch an AI storefront with iAdvize, run an agentic readiness assessment, quickly launch an AI shopping assistant, and learn from early results to scale fast. 

 

AI Storefronts as the Next Frontier of E-Commerce

The next era of commerce won’t start with a search bar but with an AI agent. And if your brand isn’t visible to agents, it won’t be visible to customers.

Agentic commerce isn’t a trend. It’s a structural shift redefining how products are discovered, evaluated, and purchased. As PayPal’s CEO predicted, 25% of e-commerce spend could be agent-driven by 2030, and the retailers that move first won’t just capture higher conversions and new revenue streams, they’ll set the standards everyone else will follow.

The good news is you don’t need to rebuild from scratch. Getting started is fast. An agentic commerce readiness assessment can help you benchmark where you stand today and map the fastest path to launch your AI storefront.

 

Key takeaways
More choice without guidance loses the sale : retailers overwhelm shoppers with options while holding more customer insight than ever, and still fail to lead them to a decision.
Turn your highest-intent pages into decision engines : product pages should anticipate and curate rather than sit there as static brochures waiting to be read.
If agents cannot read your catalog, you are invisible : structured product data, secure APIs and agentic SEO are what get a catalog surfaced in conversational queries.
Launch fast, learn faster : you do not need to rebuild from scratch, and early results from a limited launch are what justify scaling it.

 

Frequently Asked Questions about agentic commerce

The questions teams ask most often about what changes compared with traditional e-commerce.

  • Traditional e-commerce puts the work on the shopper: ads optimized for clicks, static product pages overloaded with information, unread FAQ sections, search and filters that miss context, and passive tools that wait to be asked. Agentic commerce reverses that: AI agents anticipate intent, personalize results and guide the shopper the way a trusted advisor would.

  • Children's furniture brand Mon Lit Cabane rolled out an AI shopping assistant on product pages to guide parents toward the right piece. Engagement on those pages rose sharply, post-conversation conversion reached 8%, average order value rose 30%, and more than €1M in incremental revenue was generated in three months.

  • Three moves: reframe your highest-intent pages as guided experiences instead of static brochures, structure product data and enable secure APIs so agents can index and surface your catalog in conversational queries, and launch something limited quickly so early results can fund the next step rather than rebuilding everything first.

 

[1] “A 1200% increase in generative AI-driven traffic to retail sites since July 2024” — Adobe.
[2] “25% of e-commerce spend could be agent-driven by 2030” — PayPal CEO.
[3] “8% post-conversation conversion, average order value up 30%, more than €1M incremental revenue in three months” — Mon Lit Cabane, iAdvize customer story.
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