Your earned content and your FAQ pages are now linked. You need both to stand out

If your website content isn’t structured for retrieval, your PR activity is doing all the work and getting none of the credit.

What this article covers

• AI platforms cite content from the first 30% of a page in over half of all cases. For B2B brands, this means website content  (i.e. FAQ pages, resource hubs, product pages)  needs to be structured with the core answer first, not buried after context-setting.
• Earned media builds authority signals, but those signals only translate into citations when the owned content layer is structured for retrieval. 
• Restructuring existing pages to front-load answers, and treating FAQ sections as primary citation surfaces rather than SEO add-ons, are the two highest-impact actions most brands can take immediately.

Most PR teams have never had to think about FAQ pages. That’s always been someone else’s problem, whether that’s the SEO team, the web team, or the client’s internal marketing function. Messaging and media coverage sit firmly in comms territory. Page structure and website content don’t. That division made sense when search was about links and rankings.

It doesn’t anymore.

AI platforms, such as  ChatGPT, Perplexity, Google AI Overviews and  Copilot, are now the first stop for a growing share of B2B research queries. What determines whether any piece of content gets cited isn’t the channel it came from,  but whether it’s structured for retrieval. A resource page, an FAQ block, or a newswire release written with clear signals of relevance and authority: all of these can and do get cited. Most content, across all formats, isn’t written that way. And the owned content sitting on most client websites is where the biggest gap tends to be.

Where AI systems actually look

The marketing platform, Ahrefs, ran a structured analysis across 100 Google AI Overview citations, mapping exactly where on each source page the cited snippet appeared. The results were fairly unambiguous.

Over half (55%) of citations came from the first 30% of a page. The 10–20% zone alone outperformed every other segment. Only 21% of citations came from content in the bottom 40% of a page.

Kevin Indig, strategic Growth Advisor, creator of the Growth Memo newsletter and host of the Tech Bound podcast, found the same pattern in a separate analysis of 1.2 million search results for ChatGPT. In his data analysis 44% of citations came from the first third of a document, with a steep drop-off after that. He calls it the “ski ramp” effect – a sharp cliff after the first third of the page, then a long slow tail to nothing.

Two different AI systems, both showing the same structural bias toward early answers.

The implication for most B2B content is uncomfortable. A huge amount of it is written to build up to an answer – context first, insight later. Hooks, problem-agitate-solve, narrative arcs designed to hold a reader’s attention. All of that is optimised for humans. AI citation behaviour doesn’t care about the narrative arc. If the core answer is sitting at the 50% mark, AI systems are frequently not reaching it.

The exception that proves the rule

There is one content format that consistently beats this pattern: FAQ sections.

A meaningful share of bottom-of-page citations in the Ahrefs analysis came from FAQ blocks, even when those blocks appeared deep in the page. The reason is structural. Each question-answer pair is self-contained, with a clear answer in the first sentence. It functions like a mini page, with its own signal at the top. AI retrieval rewards exactly that.

In B2B specifically, this is more useful than it might sound. A well-written FAQ block can do both jobs at once: a crisp answer in the first sentence satisfies AI retrieval, while the expanded context that follows serves the mid-funnel reader who needs proof points and supporting rationale before they’re ready to act. The fix isn’t to strip out depth. It’s to restructure so the answer lands before the build-up, not after it.

Many companies treat FAQ sections as an SEO checkbox – something that gets added at the end of a page because someone read that it helps with rankings. Treated properly, they’re one of the highest-leverage citation surfaces on a website.

What this means for PR clients

The disconnect we see most often looks like this: a brand with an active PR programme, regular media coverage, and a well-managed newswire presence, but near-zero AI visibility. The coverage is real and the volume is there but the format isn’t scrapable, the sources carrying it don’t carry the credibility signals AI platforms weigh for citation, and the owned content on the website isn’t structured for retrieval.

Earned media and owned content have always been connected in theory, but rarely integrated in practice. In AI search, the connection is structural. AI platforms are essentially asking: who is talking about this brand, in what context, with what proof and is there owned content that confirms it? If the owned layer is weak or unstructured, the earned coverage doesn’t compound the way it should.

The strategic question most brands haven’t got to yet isn’t about message or channel – it’s whether the pages carrying your core messages are structured in a way that AI systems can find and use.

How we at Archetype can help

At Archetype, our VISTA framework is built around exactly this kind of joined-up thinking. VISTA maps the signals across earned media, owned content, executive voices, and community presence, the very places that AI platforms use to form their answers. One of the most common gaps we find in audits is earned media that doesn’t connect to owned content, and owned content that isn’t structured to reinforce what the brand is saying everywhere else.

Practically, there are a few ways we work with clients on this.

Content and page audits

We look specifically at where the primary answer to a target query appears on key pages. If it’s below the 30% mark, that’s the first optimisation target. We also look at how FAQ sections are written – whether they function as genuine answer units or as placeholder content – and identify where evergreen pages are structured for human readers but not for AI retrieval.

Content restructuring and creation

For clients where there are clear citation gaps, we work on restructuring existing pages and, where pages don’t exist, creating them. Resource hubs, FAQ pages, and product pages that carry the brand’s core messages with the structural clarity AI systems reward. In B2B, this means answer-first content that still carries the depth and proof points a buyer needs, along with executive summary logic applied to page structure.

AI visibility reporting

We track how clients appear across all leading AI platforms and map citation sources back to specific pages and content types. That gives us a clear picture of which owned content is being cited, which isn’t, and what’s driving the gap. Monthly reporting, quarterly reviews, and clear recommendations on what to address next.

If you  have a strong PR presence but haven’t looked at how your owned content is structured for AI retrieval, that’s a conversation worth having. The good news is that most of the content already exists. The work is in restructuring it, not starting from scratch.

Want to see how you show up in AI search? Get in touch.

Frequently Asked Questions (FAQ)

What is Generative Engine Optimisation (GEO)?

Generative Engine Optimisation is the practice of structuring content so it gets cited by AI platforms. This  includes ChatGPT, Claude, Perplexity, Google AI Overviews, and Copilot;  when they generate answers to search queries. Where traditional SEO focuses on ranking in search results, GEO focuses on being retrieved and cited within AI-generated responses. The two are connected but not the same: a page can rank on page one of Google and still receive zero AI citations if the content isn’t structured correctly.

Why does content structure affect AI citations?

AI systems retrieve and cite content based on how quickly and clearly they can identify a direct answer to a query. Research from Ahrefs and Kevin Indig shows that over half of all AI citations come from the first 30% of a page. Content written with narrative build-up  where the main point appears midway through  is frequently skipped. Placing the core answer in the first 150–200 words, and building the supporting detail beneath it, gives AI systems the clear signal they need to cite the page.

What is VISTA and how does it relate to AI visibility?

VISTA is Archetype’s strategic framework for AI visibility. It maps five pillars: Visibility (where a brand shows up across search and AI), Identification (which topics the brand can credibly own), Signals (the content, coverage, and conversations AI uses to form answers), Trust (the credibility proof that makes signals worth citing), and Attribution (tracking which activity is driving visibility). GEO and owned content optimisation sit primarily within the Signals and Trust pillars – they determine whether the content a brand produces gets picked up and cited, or ignored. 

Does earned media coverage improve AI visibility?

Earned media contributes to AI visibility, but it doesn’t replace owned content. AI platforms weight a combination of signals: the credibility of sources citing a brand, the consistency of messaging across channels, and the clarity of owned content on the brand’s own website. Press coverage from high-authority publications strengthens the Trust pillar of AI visibility. But if the owned content layer is weak or unstructured, earned media coverage doesn’t compound into citations the way it should. Both need to be working together.

How does Archetype audit and improve AI visibility for clients?

Archetype uses the VISTA framework alongside GEO-16 framework, which is a 16-point content readiness methodology  to audit how clients appear across AI platforms and identify where the gaps are. This covers traditional search performance, AI citation presence across leading AI platforms, owned content structure, and the credibility of sources currently citing the brand. From the audit, we produce a prioritised set of recommendations covering content restructuring, FAQ development, and earned media strategy. We also include monthly tracking to measure what’s shifting visibility over time.

image credit (photo): Aerps.com on Unsplash

Authors

• Mike Browne
  With over 25 years in editorial leadership, Mike specialises in bridging the gap between high-quality content and the technical logic of modern search, ensuring brands stay visible as search engines shift toward AI-driven answers. By aligning editorial strategy with the way AI models discover and cite information, Mike helps businesses move beyond traditional SEO to build authority that both humans and machines trust.
• Athena Nathalia
  Athena leads the strategy and delivery of the agency’s services through performance marketing and analytics. Her expertise spans media buying strategy, and data analytics, with a 10-year focus on developing effective strategies and optimising campaigns to meet clients’ objectives. She is Archetype’s VISTA Insights Lead and is integral to the integrated marketing, digital, and social strategies the agency provides.