AI Search Optimisation: How Australian Businesses Can Get Cited in ChatGPT, Perplexity, and Google AI Overviews in 2026

Over 40% of Google searches now trigger an AI Overview. ChatGPT Search is growing at roughly 30% month-on-month. Perplexity processes more than 100 million queries every month and is adding users faster than any search product since early Google. If your business does not appear in the answers these platforms generate, you are not simply missing clicks. You are being edited out of your buyers' decision-making process before they ever reach your website.

This is not a future problem. Australian business owners and marketing managers are already watching their branded and non-branded organic traffic behave differently than it did 18 months ago. AI Overviews are absorbing clicks that used to flow to position-one results. Buyers are asking ChatGPT which mortgage broker to use, which recruitment firm specialises in their sector, which professional services firm understands their specific problem. The businesses that get cited in those answers are capturing qualified attention. The businesses that are absent are paying more for paid media to compensate for visibility they have silently lost.

This guide covers exactly how each major AI search platform selects its sources, what signals matter most for each one, how to restructure your content and technical setup to earn citations, and how to measure whether it is working. I will also share two real examples from our client base that illustrate what happens when you get this right, and what it cost when businesses delayed. This is not surface-level advice about "being helpful". This is a practical, platform-by-platform optimisation playbook built for the Australian market in 2026.

Key Takeaways

• AI search engines use citation logic, not ranking logic. The signals that earn a citation in ChatGPT or Perplexity are meaningfully different from the signals that earn a first-page ranking in traditional Google.

• Each platform has distinct selection criteria. Google AI Overviews prioritise corroboration and structured data. ChatGPT Search prioritises Bing-indexed authority and conversational formatting. Perplexity prioritises recency and direct answers.

• Entity authority and source reliability now outweigh raw backlink volume for AI visibility. Topical depth, consistent factual accuracy, and structured markup matter more than domain authority scores alone.

• Australian businesses have a local-context advantage that most global competitors cannot replicate. Localised data, ABS-referenced statistics, and Australia-specific regulatory context (ACCC, ASIC, APRA) signal genuine local expertise to AI systems.

• Content formatting must change. Concise answer blocks, FAQ schema, and clearly labelled entity information are now the baseline for AI citation eligibility.

• Measurement is possible today. You do not need to wait for platform-native analytics. Manual auditing, third-party tools, and structured citation tracking can give you a clear picture of your AI search visibility right now.

AI Search Versus Traditional Search: A Quick-Reference Comparison

Why AI Search Is Fundamentally Different from Traditional Search

Traditional search engines rank pages. AI search engines synthesise answers and then attribute sources. That distinction sounds simple but it changes almost everything about how you need to approach visibility.

When Google's traditional algorithm evaluates your page, it is asking: "Is this page more relevant and authoritative than the competing pages for this query?" The output is a ranked list. The user then decides which result to click.

When an AI search system evaluates your content, it is asking a different set of questions: "Is this source accurate? Is it specific? Does it directly answer the question being asked? Is it consistent with what other credible sources say? Is it current?" The output is a synthesised answer with attributed sources. The user reads the answer first and may or may not click through.

This shifts the fundamental value exchange. In traditional SEO, the goal is to win the click. In AI search optimisation, the goal is to be cited, because the citation itself delivers brand visibility and trust signals even when the user does not click through. Over time, repeated citation builds what I would call AI-era brand authority: the association between your business and a given topic or question in the minds of AI systems that are continuously re-indexing the web.

The second major difference is the role of corroboration. AI systems, particularly large language models with retrieval capabilities, are designed to triangulate claims across multiple sources before surfacing them. A single page making a strong claim is less likely to be cited than a claim that appears consistently across multiple credible sources. This is why entity-building strategies, getting your business cited accurately across directories, media, industry associations, and partner websites, have become directly relevant to AI search visibility rather than just being a traditional local SEO tactic.

Third, AI search changes the intent-to-format match. A user typing a query into ChatGPT or Perplexity is typically expecting a direct, structured answer. They are not browsing. They want a recommendation, an explanation, or a comparison. Content that buries its main point under three paragraphs of preamble is less likely to be pulled into an AI answer than content that leads with the direct answer and then supports it.

For Australian businesses, this creates a specific opportunity. Most local competitors have not adjusted their content strategy for AI citation. They are still optimising for the traditional ranking model. Businesses that move now, restructuring content, adding structured data, building entity presence, and creating concise answer blocks, can establish AI search visibility before the space becomes as competitive as traditional SEO.

How Google AI Overviews Selects Sources

Google AI Overviews, powered by Gemini, draws on the existing Google index but uses a different selection layer than traditional PageRank. Understanding that selection layer is the starting point for optimisation.

Corroboration Across Multiple Sources

Google AI Overviews has a strong preference for claims that are corroborated by multiple indexed sources. If your page is the only place on the web making a particular claim, it is less likely to be surfaced in an AI Overview than a claim that appears consistently across several credible pages. This means your content strategy needs to consider not just what you publish, but whether the claims you make are reflected and referenced by other credible sources in your industry.

For Australian professional services firms, this is particularly actionable. If your business publishes a statistic sourced from the Australian Bureau of Statistics (ABS), and other credible Australian sources reference that same ABS data point, your page is participating in a corroboration network that Google's AI systems treat as a quality signal.

Structured Data and Schema Markup

Google's systems can parse structured content far more reliably than unstructured prose. Pages with correctly implemented schema markup, including FAQ schema, HowTo schema, Article schema, and LocalBusiness schema, give Google's AI a cleaner signal about the nature and purpose of the content. In our experience working across our SEO service engagements, sites with well-implemented structured data are measurably more likely to appear in AI Overviews for their target queries than comparable sites without it.

For Australian businesses, LocalBusiness schema with accurate Australian address data, ABN reference where relevant, and correct service area specification is a baseline requirement for local AI Overview visibility.

Freshness and Content Currency

Google AI Overviews show a strong bias toward recent content for time-sensitive queries. "Best mortgage broker in Brisbane 2026" is not going to pull a page last updated in 2023 into an AI Overview, regardless of that page's traditional ranking strength. Content needs to be actively maintained, with publication and modification dates marked up correctly in schema, to remain eligible for AI Overview citations on time-sensitive topics.

E-E-A-T Signals at the Entity Level

Google's AI systems evaluate Experience, Expertise, Authoritativeness, and Trustworthiness not just at the page level but at the entity level. This means the author of the content, the publishing organisation, and the topic cluster all contribute to AI Overview eligibility. Businesses that have a clear, consistent entity presence, with named authors who have their own Google-indexed profiles, published bylines, and verifiable credentials, are better positioned for AI Overview citations than anonymous or entity-ambiguous content.

How ChatGPT Search Determines Citations

ChatGPT Search, OpenAI's retrieval-augmented search product, primarily draws on the Bing index. This is the single most important fact for Australian businesses trying to earn ChatGPT citations: if your site is not well-indexed by Bing, you are not a candidate for ChatGPT Search citations regardless of your Google rankings.

Bing Indexation and Bing Webmaster Tools

The first action item for any Australian business serious about ChatGPT Search visibility is to verify and actively manage their Bing Webmaster Tools account. Submit your sitemap, check crawl errors, and ensure that your key pages are indexed. Many Australian businesses have never touched Bing Webmaster Tools because Bing's share of the traditional search market in Australia is relatively small. That logic no longer holds when Bing is the index feeding the fastest-growing search product in the world.

Authority Signals in the Bing Index

Bing's ranking algorithm places somewhat higher weight on domain authority signals, including the quality and diversity of inbound links, than Google's more nuanced systems. For ChatGPT Search citation purposes, this means traditional authority-building tactics, earning mentions and links from credible Australian publications, industry associations, and government-adjacent sources, remain directly relevant. If your business is mentioned in an ABC News article, an ACCC release, or a credible Australian industry publication, that mention is likely indexed by Bing and therefore visible to ChatGPT Search.

Conversational Formatting and Direct Answer Structure

ChatGPT Search users are asking questions in natural language. They expect conversational, direct answers. Content that is formatted as a Q&A, that uses clear headings matching common question formats, and that leads with a direct answer before elaborating is structurally better aligned with how ChatGPT Search retrieves and attributes content. This does not mean writing in an informal or unprofessional register. It means structuring content so that the answer to the implied question is immediately identifiable.

Recency for Volatile Topics

For topics where the correct answer changes regularly, such as interest rate commentary for mortgage brokers, employment market trends for recruitment firms, or regulatory updates for professional services, ChatGPT Search strongly favours recently published content. A page published in the last 90 days on a fast-moving topic will typically outperform an older, more thoroughly optimised page in ChatGPT Search citation.

How Perplexity Ranks Sources

Perplexity operates differently from both Google AI Overviews and ChatGPT Search. It is a dedicated AI answer engine that does its own real-time web crawling, weighted heavily toward recency and source credibility as assessed by its own systems.

Recency as a Primary Signal

Perplexity's architecture places significant weight on content published or updated recently. For Australian businesses, this means a consistent publishing cadence is more important for Perplexity visibility than it is for traditional Google SEO. Businesses that publish high-quality, topically relevant content on a weekly or fortnightly basis are structurally advantaged in Perplexity's citation selection compared with businesses that publish infrequently regardless of quality.

Direct Answer Density

Perplexity's users have explicitly opted for an answer-first experience. They are asking questions and expecting immediate, specific answers. Content that scores well for Perplexity tends to have a high density of direct, factual statements that directly address common questions in the relevant topic area. Vague, hedge-everything content performs poorly. Specific, accurate, clearly stated content performs well.

This aligns directly with the approach I take across our content marketing work. The clients who see the fastest compound returns from content are consistently the ones who commit to publishing genuinely useful, specific content rather than generic industry overviews that say nothing a competitor would not also say.

Source Credibility Heuristics

Perplexity applies its own source credibility heuristics when selecting citations. Known credible domains, consistent factual accuracy, clear authorship, and a history of being cited by other credible sources all contribute. For Australian businesses, appearing in credible local media, being listed and active on established Australian directories and industry association sites, and maintaining an accurate and consistent entity presence across the web are the primary levers for improving Perplexity source credibility signals.

Platform-by-Platform Optimisation Checklist

Google AI Overviews

• Implement FAQ schema on all content pages targeting informational queries

• Add Article schema with accurate author entity information on all blog content

• Implement LocalBusiness schema with full Australian address, service areas, and business category

• Ensure all factual claims are corroborated by links to credible external sources (ABS, ACCC, APRA, peer-reviewed research, industry associations)

• Maintain a content freshness programme: review and update evergreen pages at minimum every six months

• Structure every page so the direct answer to the target query appears within the first 100 words

• Build topical authority clusters: for every core service, publish at minimum 5-8 supporting content pieces that establish depth across the topic

ChatGPT Search

• Verify and actively manage Bing Webmaster Tools: submit sitemap, monitor crawl coverage, fix crawl errors

• Earn mentions and links from credible Australian publications indexed by Bing

• Format key service and resource pages as direct Q&A: use heading structures that mirror common question formats

• Prioritise content freshness for time-sensitive topics: establish a process for updating pages when the underlying topic changes

• Ensure all pages have clear, named authorship with verifiable credentials

• Check Bing's cache of your key pages and resolve any indexation gaps

Perplexity

• Establish a consistent publishing cadence: minimum fortnightly for competitive topic areas

• Prioritise direct-answer formatting: every section should open with the clearest possible statement of the answer before elaborating

• Build Australian-specific credibility signals: citations from Australian media, government, and industry bodies carry disproportionate weight for Australian-context queries

• Monitor Perplexity citations manually: run your target queries monthly and record whether your domain appears in citations

• Submit your domain to Perplexity's publisher programme if eligible (available as of early 2026)

Content Formatting Changes Required for AI Citation

AI search optimisation is not just a technical exercise. It requires meaningful changes to how content is written and structured. Here is what needs to change.

Lead with the Direct Answer

Every piece of content targeting an informational query should open with a direct, concise answer to that query. This is sometimes called an "answer block" or "position zero content". It is a 2-4 sentence summary that gives the AI system a clean, attributable answer to pull. What follows that answer block can be as detailed and nuanced as the topic requires, but the direct answer must come first.

Use Structured Headings That Match Question Formats

Headings formatted as questions ("What is the best way to...", "How do Australian businesses...", "What does [regulation] mean for...") perform better for AI citation than generic topical headings. They signal to AI systems exactly what question the following section answers.

Implement FAQ Schema on Every Relevant Page

FAQ schema is the single highest-impact structured data change for AI search visibility. It gives AI systems a machine-readable, clearly structured set of questions and answers that can be pulled directly into AI-generated answers with clear attribution. Every service page, every blog post targeting informational queries, and every resource page should have FAQ schema implemented.

Build Entity Consistency Across the Web

Entity consistency means that the name, address, phone number, category, and description of your business are identical across every platform where you appear: your Google Business Profile, your website, your Bing Places listing, your LinkedIn company page, relevant industry directories (such as the Law Society directory for legal firms, or MFAA for mortgage brokers), and any media mentions. AI systems that encounter consistent, corroborated entity information across multiple credible sources assign higher confidence to that entity's authority on related topics.

Use Tables, Lists, and Clear Comparative Structures

Tabulated information, numbered lists, and clearly structured comparisons are significantly more likely to be pulled into AI-generated answers than equivalent information buried in prose paragraphs. Where your content contains comparative information, present it in a table. Where it contains a process, use a numbered list. Where it contains a ranking or recommendation, state it explicitly rather than implying it.

Real-World Results: What AI Search Visibility Changes in Practice

Case Study 1: Queensland Mortgage Broker

About 18 months ago, I was working with a Queensland mortgage broker who was stuck on page three for their primary keyword. They had no consistent pipeline from digital channels and were surviving on referrals alone. We executed the full 3P Framework sequence, starting with a proper Profile phase to define their ideal client, building a Plan around high-intent local keywords, and then Performing against a structured content and technical SEO roadmap.

Within six months, they reached position one for their primary keyword and were generating 40-plus qualified leads per month from organic search, a 312% increase in organic traffic. But what happened with AI search visibility was the more interesting development. Once the site had structured data in place, a consistent content programme running, and genuine entity authority built across local directories and industry sites, the broker started appearing in Google AI Overviews for queries like "how to choose a mortgage broker in [suburb]" and "first home buyer process Queensland". These AI Overview appearances were generating brand impressions and citation-driven clicks that had not existed before. The broker told me that clients were arriving on calls having already seen the business cited in AI answers as a credible source, which changed the nature of the sales conversation entirely.

Case Study 2: National Recruitment Firm

A national recruitment firm I worked with was spending heavily on job boards and generating inconsistent, expensive leads. We replaced that dependency with an SEO and content strategy focused on both candidate attraction and client acquisition, rebuilding their content architecture around the specific questions their target audience was asking.

The outcome was 574 additional leads with a 63.5% reduction in cost per lead. The content strategy that drove those results, built on specific, question-matched content published on a consistent cadence, also created strong Perplexity and ChatGPT Search visibility. When I ran searches in Perplexity for queries like "how to find specialist [sector] recruiters in Australia", the firm's content was appearing in citations within three months of the new content going live. The recency signal combined with the direct-answer formatting was enough to break into Perplexity citations ahead of competitors with far larger traditional SEO footprints.

This is exactly the dynamic I want Australian businesses to understand. Traditional SEO authority takes years to build. AI search visibility, particularly on Perplexity, can be established in a matter of months if your content is structured correctly and published consistently. The firms that move now are not just optimising for today's traffic. They are building a compounding asset that becomes harder to displace over time, which is precisely how marketing that compounds over time is supposed to work.

Measuring AI Search Visibility

One of the most common objections I hear from marketing managers is that AI search visibility cannot be measured. This is not accurate. It is less measurable than traditional SEO right now, but there are clear, actionable methods available.

Manual Citation Auditing

The most direct method is manual: run your target queries in ChatGPT Search, Perplexity, and Google (triggering AI Overviews) and record whether your domain appears in citations. Do this monthly for your 10-20 most commercially important queries. Track it in a simple spreadsheet with date, query, platform, citation yes/no, and citation position. Over time this gives you a clear trend line.

Google Search Console for AI Overview Impressions

As of 2026, Google Search Console reports are increasingly capturing data on AI Overview appearances. Queries that trigger AI Overviews and in which your site appears as a cited source will show in impressions data even when click-through rates are lower than traditional results. Monitor your impressions-to-clicks ratio for informational queries: a rising impression count with a falling CTR is a strong indicator of AI Overview appearances.

Third-Party AI Visibility Tools

Several third-party tools now provide AI search visibility tracking, including products from established SEO platforms that have added AI Overview monitoring modules. Tools in this category track which domains are being cited across AI platforms for given query sets. While Australian market coverage varies across tools, the major platforms are improving their local coverage through 2026.

Referral Traffic from AI Platforms

Direct referral traffic from Perplexity, ChatGPT, and similar platforms is trackable in Google Analytics 4 and other analytics platforms via referral source. While not all AI-driven visits will be attributed to these sources correctly (some will be masked as direct traffic), establishing a referral traffic baseline from AI platforms and tracking its growth is a meaningful visibility metric.

Brand Query Volume

An indirect but important signal: businesses that earn consistent AI search citations typically see an increase in branded search volume as users who encounter the business name in AI answers then search for it directly. Monitor branded query volume in Google Search Console as a downstream indicator of AI search visibility growth.

The Australian Local Advantage in AI Search

I mentioned in the Key Takeaways that Australian businesses have a local-context advantage in AI search that most global competitors cannot replicate. This deserves more detail.

AI search systems, particularly Google AI Overviews, place significant value on content that is genuinely authoritative for a specific geographic and regulatory context. A piece of content about home loan requirements in Australia that correctly references APRA's lending standards, cites current ABS housing affordability data, and uses suburb-level specificity is structurally more credible for Australian-context queries than a generic global piece on home loans.

For Australian businesses, this means: cite ABS data where relevant. Reference Australian regulators (ACCC, ASIC, APRA, AHPRA, relevant state-level bodies) accurately. Use suburb and state names specifically rather than generic geographic language. Structure service pages around the Australian legal and regulatory context for your industry.

This is not just a content strategy. It is an entity-building strategy. AI systems that encounter a business consistently producing accurate, Australia-specific, regulatory-aware content on a given topic will assign that entity genuine topical authority for Australian-context queries. Global competitors who do not have this local knowledge cannot easily replicate it.

This is also why the AI solutions work we do at 3P Digital consistently emphasises building genuine local authority rather than chasing global topical breadth. For most Australian SMEs and mid-market businesses, owning AI search visibility for their specific Australian market context is both more achievable and more commercially valuable than competing for global visibility.

What Most Businesses Get Wrong About AI Search Optimisation

I want to be direct about the mistakes I see repeatedly, because they are costing Australian businesses real leads right now.

The first mistake is treating AI search optimisation as a separate workstream from traditional SEO. It is not. The foundations are shared: technical health, content quality, entity authority, structured data. Businesses that have strong traditional SEO fundamentals are significantly better positioned for AI search visibility than businesses starting from scratch. The SEO work we do is designed to build these shared foundations, which is why clients see returns across both traditional and AI search channels simultaneously.

The second mistake is producing activity without accountability. I see businesses publishing content at volume, adding schema tags without auditing their accuracy, and submitting sitemaps to Bing as a one-time exercise. None of that is a strategy. AI search optimisation requires a measurement framework, a content programme with clear criteria for what gets published, and a feedback loop between what is being cited and what is being created. Activity disguised as progress does not move the needle on AI search any more than it moves it on traditional SEO.

The third mistake is ignoring the content formatting requirements. Businesses assume that because their pages rank well in traditional Google, they are well-formatted for AI citation. They are often not. A 3,000-word page that buries every answer in dense paragraphs, with no structured headings, no FAQ schema, and no answer blocks, is a poor AI citation candidate regardless of its traditional ranking performance. Restructuring existing high-performing content for AI citation is often the fastest path to measurable AI search visibility improvement.

If you are unsure where your business currently sits across these dimensions, the starting point is an honest audit. Our contact page is the right place to begin that conversation. The businesses that move from chasing leads to having them come to you are consistently the ones that treat AI search visibility as a strategic asset, not a technical afterthought.

FAQs

What is AI search optimisation and why does it matter for Australian businesses?

AI search optimisation is the practice of structuring your online content and entity presence so that AI-powered search systems, including Google AI Overviews, ChatGPT Search, and Perplexity, select your business as a cited source when generating answers to relevant queries. It matters because these platforms now handle hundreds of millions of queries monthly and the businesses that are cited in AI answers capture buyer attention before competitors do. For Australian businesses, being invisible in AI search means losing qualified leads to competitors who have adapted their content strategy.

How is AI search different from traditional SEO?

Traditional SEO aims to rank a page in a list of links. AI search optimisation aims to earn a citation in a synthesised answer. The key differences are: AI systems prioritise corroborated, structured, and recent content over pure backlink authority; the output is an answer with attributed sources rather than a ranked list; and the user interaction model means a citation delivers brand value even without a click-through. The technical foundations overlap significantly, but content formatting and entity-building requirements are distinct.

Which AI search platforms should Australian businesses focus on first?

Prioritise in this order: Google AI Overviews first, because Google still processes the majority of Australian search volume and AI Overview visibility sits on top of existing SEO foundations. ChatGPT Search second, because its growth rate is the highest of any search product and Bing indexation improvements are achievable quickly. Perplexity third, because its recency weighting means consistent, well-formatted publishing can generate citations relatively fast for businesses starting from a low base.

Does traditional SEO still matter if AI search is growing?

Yes, significantly. Traditional SEO and AI search optimisation share most of their foundational requirements: technical site health, content quality, entity authority, and structured data. A business with strong traditional SEO fundamentals is in a much better position to build AI search visibility than a business starting from scratch. The two disciplines should be treated as complementary, with AI search requirements incorporated into an existing SEO programme rather than managed as a separate workstream.

How long does it take to see results from AI search optimisation?

Timelines vary by platform. Perplexity citations can appear within weeks of publishing well-formatted, topically relevant content, because recency is a primary signal. Google AI Overview appearances typically take 2-4 months of consistent structured data implementation and content freshness work. ChatGPT Search citations depend on Bing indexation, which can take 1-3 months to fully reflect site improvements. Across all platforms, businesses with existing SEO authority see faster results than those building from scratch.

What structured data types are most important for AI search visibility?

FAQ schema is the highest-priority implementation for most Australian businesses, as it provides machine-readable Q&A pairs that AI systems can pull directly into answers. After FAQ schema, prioritise: Article schema with author entity information for all blog and news content, LocalBusiness schema with accurate Australian address and service area data, and HowTo schema for any process-oriented content. All schema should be validated against Google's Rich Results Test before deployment.

How do I check whether my business is currently being cited in AI search results?

The most direct method is manual: run your 10-20 most commercially important queries in ChatGPT Search, Perplexity, and Google (triggering AI Overviews) and record whether your domain is cited. Do this monthly and track results in a spreadsheet. Supplement this with Google Search Console impression data for informational queries, referral traffic from AI platforms in Google Analytics 4, and third-party AI visibility tracking tools where Australian market coverage is adequate.

Can small Australian businesses compete with large brands in AI search?

Yes, and in some respects the competitive dynamics are more favourable for small businesses in AI search than in traditional SEO. AI systems prioritise specific, accurate, locally relevant answers over broad, high-domain-authority pages. A small mortgage brokerage publishing genuinely useful, Australia-specific content with correct structured data can earn Google AI Overview citations ahead of a large national bank whose content is less specifically targeted. The advantage goes to whoever answers the specific question most directly and credibly, not necessarily to whoever has the largest budget.

References

1. Google Search Central Documentation on Structured Data, Google's official developer documentation covering FAQ schema, Article schema, and LocalBusiness schema implementation requirements. Describes how structured data is used by Google systems to understand page content and eligibility for enhanced search features including AI Overviews.

2. ABS Digital Activity Report, Australia, Australian Bureau of Statistics reporting on digital platform usage, internet activity, and online search behaviour among Australian consumers and businesses. Used for Australian-specific search behaviour context and market sizing.

3. Bing Webmaster Tools Documentation, Microsoft, Microsoft's official documentation for Bing Webmaster Tools, covering indexation, sitemap submission, and crawl management. Directly relevant for ChatGPT Search visibility given ChatGPT's reliance on the Bing index.

4. Perplexity AI Publisher Programme and Citation Documentation, Perplexity's published guidance for content publishers on how its systems select and attribute sources, including source credibility signals and content formatting preferences. Available via Perplexity's official publisher resources as of early 2026.

5. Google E-E-A-T Quality Rater Guidelines, Google's Search Quality Evaluator Guidelines documentation, covering the Experience, Expertise, Authoritativeness, and Trustworthiness framework used to assess content quality signals that inform both traditional search rankings and AI Overview source selection.

6. Search Engine Land and Search Engine Journal Industry Research 2026, Aggregated industry research and analysis on AI Overview click-through rate impacts, ChatGPT Search growth metrics, and AI search citation frequency data across content categories, used for the quantitative claims regarding platform growth and query volumes cited in this article.