Platform Fragmentation Index: Why ChatGPT, Claude, and Gemini Disagree

AI visibility is not portable. In 1,520 company reports with full ChatGPT/Claude/Gemini data analyzed by Loamly (Jan 9-21, 2026), ChatGPT and Claude show a moderate correlation (0.503). But ChatGPT vs Gemini drops to 0.175, and Claude vs Gemini is 0.168. That is not a rounding error. It is a structural split.

To quantify it, I built a simple Platform Fragmentation Index: the spread between the highest and lowest citation rate for each company across ChatGPT, Claude, and Gemini. The average spread is 0.296. 549 companies have a spread of 0.5+. Translation: many brands look strong on one engine and weak on another.

If you are optimizing for a single AI platform, you are probably leaving visibility on the table.

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The Correlation Gap (Why "One Strategy" Fails)

Here is the correlation matrix for platform citation rates:

Platform Pair	Correlation
ChatGPT vs Claude	0.503
ChatGPT vs Gemini	0.175
Claude vs Gemini	0.168

ChatGPT and Claude agree sometimes. Gemini is a different world. A correlation of 0.175 means that visibility on ChatGPT explains almost none of what happens on Gemini. The same applies for Claude.

This is why teams that "win" on one engine still feel invisible elsewhere. It is not bad execution. It is fragmentation. A single GEO checklist cannot cover three different retrieval and ranking behaviors. The right play is to measure platforms separately and build a strategy that accepts that reality.

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Platform Fragmentation Index (The Spread That Matters)

The Platform Fragmentation Index is the max minus min citation rate for each company across the three platforms. It captures how uneven your visibility is.

Overall spread stats:

Metric	Value
Average spread	0.296
Median spread	0.125
Spread >= 0.25	695 / 1520
Spread >= 0.5	549 / 1520

Spread buckets:

Spread range	Companies
0	639
0 to 0.25	186
0.25 to 0.5	146
0.5 to 0.75	485
0.75+	64

Nearly 1 in 3 companies sit above a 0.5 spread. That is a big gap. Even if you are "good" on one platform, the others may not recognize you.

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Average Absolute Divergence (Where the Gaps Are Largest)

Average absolute differences make the gaps more concrete:

Pair	Mean absolute difference
	ChatGPT - Claude
	ChatGPT - Gemini
	Claude - Gemini

Here is what that looks like in practice:

• Company X: ChatGPT 100%, Claude 93.75%, Gemini 0% - spread 1.00
• Company Y: ChatGPT 0%, Claude 33.3%, Gemini 100% - spread 1.00

The Gemini gap is the headline. It is about 3x larger than the ChatGPT vs Claude gap. That aligns with what most teams feel anecdotally: they can make progress on ChatGPT and Claude with the same playbook, but Gemini behaves differently.

This is not just a ranking issue. It changes what content gets cited, which sources matter, and how consistent your brand looks across engines. If you report only one platform, you are blind to a large chunk of your actual visibility surface.

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Who "Wins" by Platform

I looked at which platform gave each company its highest citation rate:

Outcome	Companies
Tie all three	639
Tie ChatGPT + Claude	408
Gemini wins	193
ChatGPT wins	186
Tie ChatGPT + Gemini	61
Claude wins	27
Tie Claude + Gemini	6

Two takeaways:

1. Ties are common. Most tie-all cases sit at the 0.6875 baseline (607 of 639), with smaller clusters at 1.0 (30) and 0.0 (2).
2. When there is a single winner, Gemini leads (193 companies), followed by ChatGPT (186). Claude is the most selective winner.

If you are growing on one platform but not the others, you are not alone. Fragmentation is normal. The mistake is pretending it does not exist.

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What This Means for Marketing Leaders

If you only have time for one change, do this: split your AI visibility reporting by platform. The aggregate average hides the gap.

Here is a practical order of operations:

1. Measure your platform spread. Use the max minus min citation rate across ChatGPT, Claude, and Gemini. Anything above 0.25 is a real gap.
2. Prioritize the weakest platform. If one engine is far below the others, focus there first. That is where the fastest lift lives.
3. Use authority signals as the base layer. The Princeton GEO study found that adding citations, quotes, and statistics increases visibility by 30-40% (KDD 2024). Those signals help on every platform.
4. Treat GEO as a multiplier, not the foundation. Structure and technical hygiene make content easier to extract, but they do not fix fragmentation by themselves.

If you want a baseline playbook, start with generative engine optimization and then track real changes with AI website traffic analytics.

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How to Reduce Fragmentation (Without Guesswork)

Fragmentation is not solved by guessing. It is solved by feedback loops.

Use this system:

• Run a platform check every month. Track citation rate per engine and the spread.
• Ship one platform-specific change per month. For example, publish a data-heavy reference page, then watch which platform moves.
• Double down on what actually moves. If a change lifts one platform but not the others, keep it as a platform-specific tactic, not a universal rule.

Loamly helps teams see those differences clearly in one report. If you want your current platform breakdown, start with the free AI visibility check.

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FAQ

Do I need separate GEO strategies for each platform?
Yes. The correlations show that success on one engine does not reliably translate to the others. The safest approach is a shared foundation plus targeted platform experiments.

What is a good fragmentation score?
Lower is better. A spread below 0.25 means your visibility is relatively stable across engines. Above 0.5 means your brand is highly uneven.

Which platform should I prioritize first?
Start with the platform where you are weakest. If two engines are similar and one is far behind, that gap is your highest ROI. The goal is balance, not just a single-platform win.

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Check Your Platform Split

Want your platform-level visibility? Get a free report and see your ChatGPT, Claude, and Gemini citation rates side by side.