Ask ChatGPT to recommend a clean lip oil. Or a long-wear foundation. Or an affordable home fragrance brand.

Your brand probably won’t come up. Even if you’ve spent decades building SEO dominance, even if you own shelf space at every major retailer, even if your site converts at 4%+.

In edition 10, we explored how beauty brands show up in AI search, and the findings were hard to ignore. 

When shoppers ask AI for advice, they rarely mention these brands. AI doesn’t care about any of that.

And right now, thousands of shoppers are asking AI for recommendations instead of Googling. They’re skipping your paid search, your SEO stack, and your retargeting pixels entirely. They’re getting answers from models that may have never even crawled your site properly.

The hierarchy of discovery has been rewritten. And most brands don’t realize they’ve already lost.

TL;DR:

• AI search is the new Google for product discovery, and most legacy brands don’t show up
• We ran tests across major AI models and found that big brands like Revlon disappear in early discovery, even with strong SEO
• What matters most now is structured data, review clarity, creator mentions, Reddit threads. Backlinks or domain authority no longer rule
• Digital-first brands win because AI learns from signal, not size
• The next era of growth depends on being seen and trusted by AI, now

Revlon Has a Century of Equity. ChatGPT Doesn’t Care.

We analyzed Revlon through our new AI visibility framework. Here’s what we found:

Overall Discoverability Score: 50.7 / 100

But that number hides the real problem:

• Discovery (early funnel): 38.4 / 100
• Evaluation (comparison): 73.7 / 100
• Purchase (decision): 97.7 / 100

Revlon performs well once you already know the brand. Its product pages are clean. Its policies are clear. If you’re comparing “Revlon ColorStay vs Maybelline Fit Me,” it shows up strong.

But ask an open-ended question like “best long-wear lipstick” or “clean beauty brands to try”? Revlon disappears.

It doesn’t even get introduced. It’s skipped.

The model can’t parse Revlon’s site well. Missing schema. Weak structured data. No loyalty signals. Incomplete review metadata. And off-site, almost zero creator mentions or Reddit threads, the exact signals AI models weight heavily in discovery.

Revlon still owns the shelf. But it lost the search.

And if this is happening to a 100-year-old global brand with massive distribution, it’s probably happening to you too.

Why AI Search Breaks Everything You Know

AI models don’t rank like Google. They synthesize.

Every time someone asks “what’s a good moisturizer for dry skin,” the model pulls signals from across the web, weighs trust and tone and structure, then writes a new answer from scratch.

It doesn’t reward:

• Backlinks
• Domain authority
• Ad spend
• Brand legacy

It rewards:

• Structured data clarity
• Review sentiment and distribution
• Creator mentions and Reddit threads
• Simple, emotionally resonant language

A 3-year-old DTC skincare brand that explains its ingredients clearly will outrank a heritage company simply because the model understands it better.

The playing field just reset. And the brands moving fastest right now will define how they’re remembered for the next decade.

We’ve Been Mapping What AI Actually Sees

Here’s a First look Inside the System.

For months, we’ve been running thousands of real shopping-style prompts through the major AI models and mapping what they surface, what they skip, and the signals they trust the most.

And the patterns are… eye-opening.

We’re not announcing anything today.
But we are going to show:

• How often your brand appears when shoppers ask AI open-ended questions
• What AI highlights when comparing you with competitors
• Whether your site and policies are even understood correctly

Think of this as a sneak peek, a bit of data, and the clearest picture yet of how AI interprets your brand.

This is how the next era of visibility begins.

The Shift You Haven’t Noticed Yet

We’ve been analyzing the results. Brand by brand, category by category. Looking at who’s being recommended, who’s left out, and what those patterns tell us about how these systems rank trust and relevance.

Legacy brands with strong SEO often vanish in early discovery. Digital-first brands dominate despite smaller budgets. The signals that matter most aren’t what anyone expected.

Over the next few weeks, we’ll share what we’re learning:

• Actual brand breakdowns (like Revlon above)
• Patterns we’re seeing across categories
• The specific signals that seem to move the needle

This is a behind-the-scenes look at how AI visibility actually works and what it means for your brand.

Over time, we may open access to this internal tool, starting with those who read CommerceGPT.

For now, we’re just mapping new territory and sharing what we find as we go.

The bottom line

The next wave of growth won’t just be about ranking higher. It’ll be about being understood and trusted faster.

Let’s make sure your brand is part of the next answer, not the last result.

— Tomer