Using BrightEdge AI Catalyst, we analyzed eCommerce prompts across Google AI Overviews and ChatGPT throughout the holiday shopping season. We've already shared WHO each platform cites — now we're examining HOW CONCENTRATED those citations are. The patterns reveal very different distribution curves that marketers should understand when measuring AI visibility.

Data Collected

We analyzed citation sources across both AI platforms to understand:

• Which domains each AI returns to repeatedly across many queries

• How concentrated citations are among top sources

• How often the same URL gets reused across different prompts

• Whether the same content surfaces differently on each platform

Key Finding

AI Overviews concentrates citations among a smaller set of trusted sources — its top 10 domains capture 39% of all shopping citations. ChatGPT distributes citations across a much wider pool — its top 10 domains capture just 22%. One retailer homepage appears in roughly 1 of every 4 AI Overview shopping responses. The same optimization wins on both platforms, but understanding the distribution curves helps you measure success accurately.

The Concentration Gap

AI Overviews: Deep Trust in Fewer Sources

AI Overviews returns to the same sources repeatedly. The top 10 domains capture 39% of all eCommerce citations, and a single retailer homepage appears in approximately 26% of all shopping queries.

This concentration pattern means that when AI Overviews trusts a source, it cites that source across many different queries. Winning visibility on AI Overviews means joining a concentrated set of repeatedly-cited sources.

The Strategic Interpretation

This isn't about one platform being better than the other. It reflects different approaches to sourcing information for shoppers.

AI Overviews builds on established, trusted sources — going deep with content it returns to across many related queries.

ChatGPT casts a wider net — pulling from a broader universe of sources and going wide to find query-specific content.

URL Reuse Patterns: The Starkest Contrast

How Often Does the Same URL Get Cited?

The URL reuse data reveals just how different these platforms behave.

AI Overviews' most-reused single URL appears in approximately 26% of all shopping queries. When AI Overviews finds a source it trusts for a category, it returns to that source repeatedly.

ChatGPT's most-reused single URL appears in approximately 1% of queries. Even ChatGPT's "favorite" sources are only cited in a small fraction of responses.

What This Looks Like in Practice

For AI Overviews, a Consumer Reports buying guide might get cited in 27 different shopping queries — from coffee makers to mattresses to microwaves. The same trusted source serves many different user needs.

For ChatGPT, a detailed RTINGS TV review might get cited in 48 queries — but those are almost all TV-specific queries. ChatGPT finds the deep expert source for each specific topic rather than reusing general buying guides across categories.

Same Content, Different Visibility Curves

The Measurement Implication

Your content can win on both platforms — but where and how often it appears will differ.

On AI Overviews, a winning piece of content may surface repeatedly across many related queries. If you're cited, you may be cited often.

On ChatGPT, a winning piece of content may surface for specific queries where it's the best match. You may be cited less frequently, but with more precision.

This isn't a strategy problem — it's a measurement reality. Tracking visibility on both platforms gives you the complete picture of how your content performs in AI search.

Platform Favorites: Different Sources for Different Platforms

Each Platform Has Go-To Sources

When we looked at specific URLs, clear patterns emerged. Each platform has sources it returns to repeatedly — and they're often different sources.

One TV review site's "best TVs" page was cited in 48 queries by ChatGPT but 0 by AI Overviews.

One trusted buying guide index page was cited in 27 queries by AI Overviews but 0 by ChatGPT.

Both are high-quality sources. Both provide genuine value to shoppers. But each platform has developed its own preferences for which sources to trust and return to.

The "Optimize Once" Reality

This doesn't mean you need different content strategies for each platform. Quality content that serves user needs can surface on both. The difference is in how each platform distributes that visibility.

AI Overviews may cite you frequently across many queries once you're in its trusted set.

ChatGPT may cite you precisely for the specific queries where you're the best source.

Both are wins. Understanding the pattern helps you interpret your visibility data correctly.

What This Means for Brands

Track Both Scoreboards

The concentration difference means raw citation counts will look different across platforms — and that's expected.

A source cited 20 times by AI Overviews and 5 times by ChatGPT isn't necessarily "losing" on ChatGPT. It may simply reflect the different distribution curves. ChatGPT's 5 citations might represent 5 highly specific queries where your content was the best match.

Conversely, being cited 0 times by AI Overviews but 15 times by ChatGPT doesn't mean AI Overviews is ignoring you — your content may simply serve queries that ChatGPT handles differently than AI Overviews.

Understand Your Category

The concentration patterns may vary by category. Buying guides and category-level content may see more reuse on AI Overviews. Deep product-specific reviews may see more precise matching on ChatGPT.

This aligns with what we found earlier: AI Overviews leans on editorial and UGC content (YouTube, Reddit, review sites) while ChatGPT leans on retailer and product sources. The concentration data adds another layer — AI Overviews not only favors different source types, it returns to those sources more repeatedly.

One Strategy, Two Visibility Patterns

The actionable insight isn't "build two strategies." It's "measure two outcomes."

Same content optimization. Same focus on quality, relevance, and user value. But when you check your AI visibility metrics, expect to see different patterns:

AI Overviews: Fewer total queries, but higher citation frequency per query when you do appear.

ChatGPT: More total queries in your addressable universe, but lower citation frequency as visibility spreads across more sources.

Both patterns represent success. Understanding them helps you set appropriate benchmarks and interpret your data correctly.

Technical Methodology

Data Source: BrightEdge AI Catalyst

Analysis Approach:

• eCommerce prompts analyzed across Google AI Overviews and ChatGPT

• Citation sources extracted and categorized by domain and URL

• Domain concentration calculated (share of citations held by top domains)

• URL reuse patterns measured (how many prompts cite the same URL)

• Cross-platform comparison for shared vs. platform-exclusive sources

Key Metrics:

• Top 10 domain concentration (% of total citations)

• Single URL maximum reuse (% of queries citing one URL)

• URL uniqueness rate (% of URLs cited only once)

• Domain overlap analysis across platforms

Measurement Period: Holiday Shopping Season 2025

Key Takeaways

The Concentration Gap: AI Overviews' top 10 domains capture 39% of citations. ChatGPT's top 10 capture just 22%. AI Overviews goes deep with trusted sources. ChatGPT goes wide across more.

The Reuse Pattern: AI Overviews' most-cited single URL appears in ~26% of shopping queries. ChatGPT's most-cited URL appears in ~1%. AI Overviews returns to favorites. ChatGPT pulls fresh sources.

The Uniqueness Rate: 61% of URLs cited by ChatGPT appear in only one query. ChatGPT finds specific sources for specific queries rather than reusing general pages.

The Platform Favorites: Each platform has sources it trusts and returns to repeatedly — and they're often different sources. The same quality content can win on both, but visibility patterns will differ.

The Measurement Reality: Same optimization strategy works for both platforms. But understanding the different distribution curves helps you interpret visibility data and set appropriate benchmarks.