ChatGPT vs Claude vs Perplexity vs Gemini: how brand visibility differs
Brand visibility is not the same work across the four major AI engines. ChatGPT owns the traffic. Gemini owns the reach. Perplexity owns research queries. Claude owns the B2B technical audience. Each has a different user base, a different citation mechanism, and a different set of tactics that move the metric. Most brands cannot afford to optimize for all four. Prioritization is the whole game. This is the side-by-side we use internally to scope a new GEO engagement.
ChatGPT: the traffic leader
ChatGPT is the category king by a wide margin. As of February 2026, it has around 900 million weekly active users (TechCrunch), roughly 50 million paying subscribers, and 87.4 percent of all AI referral traffic per Passionfruit's 2025 ten-industry study (Passionfruit). If you only have resources to optimize for one engine, it is ChatGPT, and it is not close.
The citation mix: pre-training memorization plus Bing-driven real-time search (ChatGPT Search launched October 31, 2024, and OpenAI has confirmed Bing is an important input). GPT-4o's cutoff is October 2023; GPT-5.x reaches August 2025. Three levers in priority order: fix Bing visibility first (invisible in Bing means invisible in ChatGPT Search), seed the corpora that feed future training runs (Reddit, Wikipedia, YouTube, Stack Overflow, editorial press), and make sure GPTBot and OAI-SearchBot are allowed. Fixing the crawlability layer alone often unlocks 20 to 40 percent mention rate improvement in two to three weeks. Tactical detail is in how to get your brand mentioned in ChatGPT answers.
Claude: the B2B technical audience
Claude is smaller in raw users but dominates technical B2B buyers, senior engineers, and research-heavy users. Business of Apps reports roughly 7.38 million monthly app users end of 2025 (Business of Apps). Anthropic's revenue tells the real story: $14 billion annualized by February 2026, up from $1 billion at the start of 2025. That is hockey-stick expansion driven almost entirely by API-first technical customers.
Claude uses pre-training plus three dedicated crawlers: ClaudeBot for training, Claude-User for user-initiated fetches, and Claude-SearchBot for Anthropic's in-product search index. Claude's web search tool is available on Opus 4.6 and Sonnet 4.6. Make all three crawlers welcome, publish clean technical documentation with code examples, and seed your brand on the sources Claude's training pipeline weights highly: GitHub, Stack Overflow, developer subreddits, and technical editorial. Claude under-cites brands that exist almost entirely in consumer press. The step-by-step is in get cited by Claude for brand queries.
Perplexity: the research engine
Perplexity is the smallest of the four but has the most research-heavy user base. Business of Apps reports roughly 45 million active users and ~780 million monthly queries end of 2025 (Business of Apps). Users are analysts, due-diligence teams, and product managers gathering sources. Low tolerance for marketing content, high tolerance for dense technical material.
Perplexity runs a three-layer retrieval pipeline: initial retrieval, authority-and-credibility ranking, and an XGBoost reranker for entity queries. Source credibility rests on four signals: trustworthiness, authority, corroboration, and provenance. The company manually boosts GitHub, Amazon, LinkedIn, and Reddit as source domains. Build real presences on those four. Make your own site technically credible with author bylines, publication dates, and citations to primary sources, because Perplexity's credibility ranker reads those as signal. Brochure-style content ranks lower than content that reads like a primary source. The tactical guide is in rank in Perplexity answers.
Gemini and Google AI Overviews: the reach leader
Gemini powers Google's flagship app plus AI Overviews and AI Mode inside Search. The numbers are enormous. The Gemini app alone reached 750 million monthly active users as of February 2026 (TechCrunch). AI Overviews has roughly 2 billion monthly users worldwide. AI Mode adds another 100 million in the US and India. Sistrix tracking shows AIO now triggers on roughly 20 percent of German-language and 18 percent of UK-language keywords (Sistrix).
Seer Interactive's 2025 study of 25 million organic impressions found that when an AIO is present, organic CTR drops 61 percent and paid CTR drops 68 percent. When you are cited inside the AIO, you get 35 percent more organic clicks and 91 percent more paid clicks than non-cited results on the same query (Seer). AI Overviews pulls sources from Google's existing index, weighted by E-E-A-T. Google's own documentation says there is no special schema required. Rank well in classical Google, improve E-E-A-T, get author bylines and publication dates on every article. Visibility inside AIO is downstream of traditional search equity. Walkthrough: how to appear in Google AI Overviews.
Side-by-side comparison
| Engine | Scale | Citation mechanism | Best fit audience | Biggest blocker |
|---|---|---|---|---|
| ChatGPT | 900M weekly active users | Bing index plus training data | Consumer and B2B breadth | Not indexed by Bing |
| Claude | ~7.38M monthly app users | 3 crawlers plus live web search tool | Developers, researchers, enterprise | ClaudeBot blocked by robots.txt |
| Perplexity | ~45M active users, 780M queries/month | 3-layer retrieval, XGBoost reranker | Technical researchers, power users | Low authority domain score |
| Google AI Overviews | 2B monthly users | Google index weighted by E-E-A-T | Mass consumer and informational queries | Not ranking organically for the query |
Additional quick reference points across the four engines.
- Primary citation mechanism: ChatGPT = pre-training plus Bing; Claude = pre-training plus three internal crawlers; Perplexity = real-time retrieval with authority ranking; Gemini/AIO = Google's existing index plus E-E-A-T.
- Fastest intervention: ChatGPT = Bing SEO plus Reddit; Claude = robots.txt hygiene plus GitHub; Perplexity = Reddit, GitHub, LinkedIn, Amazon; Gemini = classical Google SEO plus E-E-A-T.
- Share of AI referral traffic: ChatGPT 87.4 percent of all AI referrals; the other three split the remaining 12.6 percent.
- Hardest engine to optimize cold: Perplexity, because the authority signals take months to build; easiest is Gemini/AIO if you already rank in Google.
Who should prioritize which engine
Three rules of thumb that hold across most of the engagements we run.
B2B technical brands should prioritize Claude and Perplexity. Your buyers are researchers, engineers, and product managers reaching for the tool that gives them dense technical answers with citations. A B2B SaaS brand invisible on Perplexity is invisible to the exact audience it wants to reach, even if ChatGPT rankings look fine.
Consumer brands with broad reach goals should prioritize ChatGPT and Google AI Overviews. That is where the volume lives. A DTC brand or media company ignoring AIO is watching classical Google traffic erode without replacement.
Mid-market brands usually need ChatGPT plus one of the other three based on audience. If you serve engineers, add Claude. If you serve researchers, add Perplexity. If you serve consumers, add Gemini. Optimizing equally across all four spreads the budget too thin to move any single metric. For the pillar framework, see the 2026 guide to Generative Engine Optimization. For the technical layer, how LLMs decide what to cite.
The B2B vs consumer divide
B2B brands over-index on ChatGPT because it is the biggest name, then wonder why Perplexity share-of-voice is terrible. Their buyers are not asking ChatGPT for due diligence. They are asking Perplexity, Claude, and Gemini's Deep Research. ChatGPT dominates consumer volume, but a senior buyer doing vendor research is as likely to be inside Perplexity as inside ChatGPT, and Claude's share of that audience is growing.
Consumer brands make the inverse mistake. They over-index on Claude or Perplexity because the names sound modern, then miss that their actual buyers never open either product. If your end user is not a researcher, your GEO budget belongs in ChatGPT and AIO first.
Conclusion
Prioritization is the whole game. The four major engines are not interchangeable. They have different audiences, different citation mechanisms, and different intervention costs. Spreading a budget equally across all four is the fastest way to make no measurable progress on any of them. Pick the one or two engines your actual buyers use, go deep, and measure weekly. The rest can come later.
How Soar saves you time and money
Every engagement starts with a weighted prioritization based on the client's actual audience. We do not default to "optimize for all four." We look at who the buyer is, which engines that buyer uses, and how much it would cost to move each metric. For a B2B SaaS client that means Claude and Perplexity first with ChatGPT as a secondary layer. For a DTC brand it means ChatGPT and Gemini first, with the others running as monitoring. For a mid-market hybrid, we split the work 70/30.
The savings come from not wasting months on the wrong engine. We have watched brands spend a quarter optimizing for Claude when their buyers were in Gemini, or chasing Perplexity when 87 percent of their AI referral traffic was already coming from ChatGPT. Each of those mis-prioritizations costs $30,000 to $80,000 in wasted program budget. Soar's prioritization framework catches it in the first kickoff meeting.
For a prioritization audit before committing to a full program, request a proposal. We will run your top 20 prompts through Parse across all four engines and hand you a weighted recommendation for where your first 90 days of GEO spend should actually go.