Yes. According to okara.ai's 230-query study published in November 2026, ChatGPT cites product and service pages for more than half its sources, while Claude, Gemini, and Perplexity draw mainly from third-party "best X" lists and comparison articles.
That single finding changes how you should allocate content budget. One strategy no longer covers four retrieval systems.
What the Study Actually Found
Okara.ai wrote 70 questions a real buyer of marketing software would ask, covering category queries, comparison prompts, problem-first questions, and industry-specific searches. They ran those questions through ChatGPT (with web search on), Claude Sonnet 5.5, Gemini 3.5 Flash, and Perplexity Sonar Pro, producing 230 total answers. For each answer they logged every cited URL and, where available, the background searches each model ran.
Two findings stand out.
First, the engines agreed on which brands to recommend about 41% of the time for the same question. So brand visibility is partly portable across engines.
Second, the overlap in cited domains between any two engines was just 6%. ChatGPT and Claude shared only 3% of cited domains for the same question. The engines are recommending similar companies through almost entirely different source material.
That 6% figure is the number to hold onto. It means being cited in ChatGPT offers almost no guarantee of citation in Perplexity, and vice versa.
Why the Engines Pull Different Sources
Each engine retrieves differently, and Tengence's breakdown of citation behavior sketches the logic clearly:
- ChatGPT uses retrieval-augmented generation with a browser tool, and its citations favor authoritative media and documents. The okara.ai study also found ChatGPT appends the current year to most of its background searches, which pulls it toward recently updated, indexed pages like product and pricing pages.
- Perplexity is built around "answers with citations" as its core product. Nearly every sentence is traceable. It draws from news, papers, and official sites.
- Gemini is tied deeply to the Google index, weights high-authority pages, and responds strongly to structured data. It tends to cite Google-owned services and high-authority pages.
- Claude leans on third-party editorial sources rather than vendor-owned pages, favoring "best X" lists and comparison articles.
None of this is surprising once you think about it. ChatGPT's browsing tool fetches pages that directly answer a commercial query. A well-structured product page is a direct answer. Perplexity and Gemini, by contrast, are rewarding content that already consolidates authority from many sources.
Making Product Pages Citation-Ready for ChatGPT
If ChatGPT is pulling product and service pages, those pages need to be readable as self-contained answers. Loxvo's guide on AI citations makes the crawl requirement explicit: OAI-SearchBot must be allowed in robots.txt and in any firewall or bot-protection layer. Blocking it means your site will not be shown in ChatGPT search answers, though you can still appear as a navigational link.
Beyond access, the content itself needs to work in isolation. Open each key page with a direct two-to-three sentence answer. Put pricing, specs, and use-case descriptions near the top. Use question-style headings. Name the facts that a model can quote: who the product is for, what problem it solves, what it costs.
Structured data helps too, particularly for Gemini and AI Overviews, and it also makes pages easier for ChatGPT to parse and attribute. Tengence's analysis highlights FAQ, HowTo, and Article schema as especially critical for Gemini and AI Overviews, with benefits extending to ChatGPT and Perplexity as well.
Tools like Writesonic GEO and Vaylis AI can help you audit and optimize page-level signals at scale before you run your own prompt tests.
Targeting Third-Party Placements for Claude, Gemini, and Perplexity
For the other three engines, the game is different. You need to appear in the articles they already cite, which means identifying the specific comparison and listicle domains that consistently surface for your category, then earning placement there.
High Links documented this pattern directly: republished articles can appear as AI citations, sometimes through the republisher's domain rather than the original.
The practical moves are:
- Run your category queries in Perplexity and Gemini, log every cited domain, and build a target list of publications that appear repeatedly.
- Prioritize outreach to those domains over general PR. A mention in a "best project management software" roundup on a site Perplexity already trusts is worth more than a press release on a domain neither engine indexes.
- Transparent authorship and verifiable sources raise citation odds across all three engines, as Tengence's analysis notes.
For tracking which third-party mentions actually translate into AI citations, OmniSEO and Peec are worth looking at.
A Two-Track Content Calendar
The practical split looks like this:
| Engine | Primary citation source | Your content priority |
|---|---|---|
| ChatGPT | Product and service pages | First-party page optimization, crawler access, structured data |
| Perplexity | News, papers, aggregators | Third-party editorial placement, timely facts |
| Gemini | Google-ranked, high-authority pages | SEO-backed comparison content, E-E-A-T signals |
| Claude | Third-party editorial | Comparison articles, "best X" lists |
For commercial queries where someone is close to buying, ChatGPT citations from your own pages carry the most direct value. For informational and research queries, Perplexity and Gemini dominate, so third-party presence matters more. Brand awareness across all stages requires both tracks running in parallel.
Caveats Worth Keeping in Mind
The okara.ai study covered 230 answers to marketing software buying questions, run in November 2026. The vertical skew is real: results for SaaS tools may not transfer cleanly to e-commerce, healthcare, or local services. Asking the same question twice produced noticeably different answers, so individual data points are noisy.
Before reallocating budget based on this study, run your own prompt audit. Take 20 to 30 questions your buyers actually ask, run them through each engine with web search on, and log every cited domain. What okara.ai found for marketing software may hold, or your category may show a different pattern entirely. Tools like PromptWatch and Otterly make it easier to run that kind of ongoing audit without building the logging infrastructure yourself.
The underlying point stands regardless of vertical: four engines, four retrieval habits, one content strategy is no longer enough.