AI SEO: The Complete Australian Guide (2026)

This is a data report. Every claim is sourced. The data comes from Ahrefs (76,000+ websites tracked), Semrush (230,000 prompts and 100 million citations analysed), the Princeton/Georgia Tech GEO research paper (peer-reviewed, KDD 2024), Seer Interactive (25.1 million impressions), and multiple independent conversion studies. Where sources disagree, we present both figures.

AI SEO is the highest-CPC keyword in the Australian search market at $48.59 per click. That number reflects what agencies are willing to pay to reach people asking this exact question. This guide is intended to answer it more thoroughly than any paid result can.

Three ways AI is changing search

AI is reshaping search through three distinct mechanisms, each with different implications for businesses.

1. Google AI Overviews

Google AI Overviews are AI-generated summaries that appear above organic results for a growing percentage of queries. When they appear, they change how users interact with the page. Organic clicks drop. Citation in the AI Overview becomes a new form of visibility.

How prevalent are they? The data varies by source:

The discrepancy is significant. It comes from different keyword samples, different geographies, and different measurement methodologies. What every source agrees on: the percentage is growing, and the growth is accelerating. AI Overviews were initially limited to informational queries. By late 2025, they had expanded into commercial, transactional, and navigational searches (Semrush, December 2025).

The click impact is measurable. Seer Interactive studied 3,119 informational queries across 25.1 million organic impressions and found a 61% reduction in organic CTR for queries where AI Overviews appeared. A separate study of 300,000 keywords found a 58% organic click reduction.

But being cited in the AI Overview flips the equation. Sites cited in AI Overviews receive 35% more organic clicks than non-cited competitors at similar ranking positions, and 91% more paid clicks when the brand is also cited.

The practical implication: if AI Overviews appear for your target keywords, being cited is better than ranking first in organic and not being cited.

2. ChatGPT as a search engine

ChatGPT processed 2.5 billion prompts per day as of July 2025, with over 800 million weekly users by October 2025. Roughly 65% of that usage qualifies as search (things people would traditionally have searched on Google), according to Ahrefs' analysis of a 1.5 million conversation dataset published by OpenAI and Harvard.

That gives ChatGPT approximately 12% of Google's search volume for traditional search queries.

ChatGPT dominates AI referral traffic. Across multiple tracking studies, it holds 78 to 80% of AI search traffic share as of early 2026. Perplexity holds 2 to 15% depending on methodology, and Google Gemini roughly 6%.

3. Perplexity and the citation-first model

Perplexity was built around citations. Nearly every response includes numbered source links. This makes it the most transparent AI search platform and the one most aligned with traditional web publishing.

Perplexity's traffic share is smaller (roughly 2% of AI search traffic), but it sends pre-qualified visitors. Seer Interactive measured a 10.5% conversion rate from Perplexity traffic, compared to 1.76% from Google organic.

Perplexity also has the highest citation overlap with Google of any AI platform. 28.6% of Perplexity's citations point to pages in Google's top 10, compared to just 8% for ChatGPT. If you already rank well in Google, you are closer to Perplexity visibility than ChatGPT visibility.

The traffic data: Google still dominates

Before investing in AI SEO, it is worth understanding the scale difference.

Source: Ahrefs Web Analytics, 76,000+ websites, February 2026

Google sends 190 times more traffic to websites than ChatGPT. Google makes up nearly 40% of all website traffic. ChatGPT makes up 0.22%. All AI assistants combined, including Perplexity, Gemini, Claude, and others, account for 0.25%.

The narrative that "AI search is replacing Google" is not supported by the traffic data. What the data shows instead is two different business models operating at two different scales. Google connects people to websites. ChatGPT keeps them in conversation.

The growth rate matters

AI search traffic grew 700% between 2024 and 2025 according to Ahrefs' analysis. ChatGPT's traffic share grew 3 times between January and September 2025. No other traffic source has grown at that rate.

For context, social media at a comparable growth stage grew 40 to 60% annually. AI referral traffic is accelerating at roughly 10 times that pace.

The absolute numbers remain small. But ignoring a channel that grows at 700% per year and converts at dramatically higher rates is not a defensible strategy either.

The conversion premium: why AI traffic matters despite low volume

This is where the AI search story shifts from "interesting but irrelevant" to "strategically important."

Five independent studies have measured conversion rates from AI search traffic. The methodologies differ. The sample sizes range from thousands to millions. The findings point in the same direction.

Sources: Ahrefs, Seer Interactive via SERPs.io, Superprompt via SERPs.io, Microsoft Clarity via Loamly, Digital Bloom

The conversion premium is real, but it is not universal. Amsive's study across 54 websites found no statistically significant difference in conversion for some business models. A 61-page research study found that ChatGPT referrals convert worse for ecommerce impulse purchases.

The pattern: AI search conversion rates are highest for high-consideration purchases (SaaS, professional services, B2B) and lowest for commodity ecommerce. The reason is pre-qualification. By the time someone clicks a link from ChatGPT or Perplexity, the AI has already handled the research phase. The visitor arrives with higher intent.

For Australian professional services firms (law, accounting, consulting, financial advice), this pattern is directly relevant. These are high-consideration services where a potential client researches extensively before making contact.

Conversion rates by AI platform

Not all AI platforms send the same quality of traffic.

Source: Seer Interactive, Superprompt, Digital Bloom

Claude has the highest conversion rate at 16.8% despite having the smallest traffic share. Perplexity's audience skews towards senior leadership (30% according to Similarweb data via Digital Bloom). These are valuable audiences even at small volumes.

The dark traffic problem

One complication: 70.6% of AI traffic arrives without referrer headers, making it invisible to standard GA4 attribution. It gets misclassified as "direct" traffic. This dark AI traffic converts at 10.21%, compared to 2.46% for standard non-AI direct traffic (a 4.1 times premium).

The practical implication: you are almost certainly getting more AI search traffic than your analytics report. If your direct traffic has increased and your direct conversion rate has improved, AI search may be a contributing factor you are not measuring.

AI citations and Google rankings are decoupling

One of the most significant findings in AI SEO research: ranking well in Google does not guarantee you will be cited by AI.

Ahrefs analysed 15,000 prompts across ChatGPT, Gemini, Copilot, and Perplexity. On average, only 12% of URLs cited by AI assistants also ranked in Google's top 10 for the same prompt. 80% of AI-cited URLs did not rank anywhere in Google's top 100 for the original query.

The platform-level breakdown:

Source: Ahrefs Brand Radar study, 15,000 prompts

Perplexity is the outlier. Nearly 1 in 3 of its citations point to pages in Google's top 10. ChatGPT, the dominant AI search platform, shows just 8% overlap.

A separate analysis of Google AI Overviews specifically tells a similar story but from the other direction. In July 2025, 76% of AI Overview citations came from pages ranking in the organic top 10. By February 2026, that figure had collapsed to 38% (Ahrefs, 863,000 keywords).

Among the 62% of AI Overview citations now coming from outside the top 10: 28% come from positions 11-50, 16% from positions 51-100, and 18% from beyond the top 100 entirely.

This decoupling has a direct implication for AI SEO strategy. You cannot rely solely on Google rankings to earn AI citations. You need to optimise for how AI models select sources, which is a different process than how Google ranks pages.

What AI models cite: the domain-level data

Semrush analysed 230,000 prompts and 100 million citations across ChatGPT, Google AI Mode, and Perplexity over 13 weeks (July to October 2025). The most-cited domains reveal what AI models consider authoritative.

Most-cited domains by platform

ChatGPT: Before September 2025, Wikipedia and Reddit appeared in roughly 55-60% of all prompt responses. After a major shift in mid-September (coinciding with a Google search parameter change), both dropped significantly: Reddit fell from ~60% to ~10%, Wikipedia from ~55% to ~20%. After the shift, PRnewswire, Forbes, Medium, and LinkedIn gained citation share.

Google AI Mode: A more balanced mix. Top cited domains include LinkedIn, YouTube, Reddit, Google, and Google Blog. Google AI Mode consistently cited LinkedIn in nearly 15% of responses. YouTube and Reddit also feature prominently. Google-owned properties (YouTube, Google Blog, Google Support) together account for a substantial share.

Perplexity: Strong showings for Reddit, LinkedIn, government sources, and expert publications. More stable citation patterns than ChatGPT, with less dramatic month-to-month volatility.

Citation patterns across all AI platforms

Google's own data on AI Overview citations shows distinct preferences:

Source: DemandSage, citing SE Rankings and Try Profound

Compared to ChatGPT's citation preferences:

Source: DemandSage, citing SE Rankings

The pattern: AI models heavily favour user-generated content platforms (Reddit, Quora, YouTube), established reference sources (Wikipedia), professional networks (LinkedIn), and authoritative institutions (government sites, NIH). For businesses, this means having a presence on these platforms, not just on your own website, directly influences whether AI models cite your brand.

GEO: the Princeton framework for AI visibility

The most rigorous academic research on AI SEO comes from a team at Princeton University, Georgia Tech, IIT Delhi, and the Allen Institute for AI. Their paper, "GEO: Generative Engine Optimization," was published at KDD 2024, the top academic conference for data mining and knowledge discovery.

The researchers created a benchmark of 10,000 queries, tested nine content optimisation methods, and measured their impact on source visibility in generative engine responses.

The nine methods tested

Source: Aggarwal et al., GEO: Generative Engine Optimization, KDD 2024

Three methods stood out. Quotation Addition, Statistics Addition, and Cite Sources each produced visibility improvements of up to 40% on the Position-Adjusted Word Count metric. The effect was strongest for lower-ranked sources (positions 3-5), meaning GEO strategies are most valuable for content that would otherwise be marginal in AI responses.

Keyword stuffing was the only method that hurt visibility. This is a direct inversion of early-era SEO tactics.

Domain-specific effects

The GEO paper found that different strategies work better in different subject areas:

• Citing sources worked best for factual information queries
• Statistics had the strongest effect in law, government, and opinion-based queries
• Quotations boosted visibility most in people and society, explanation, and history domains
• Authoritative tone helped most with debate-style and historical queries

For Australian professional services businesses, the combination of statistics and citations is the highest-impact strategy, because the queries they target (legal questions, financial advice, healthcare information) fall squarely in the factual and YMYL categories where these methods are most effective.

GEO strategies also applied to Perplexity

The researchers tested the same methods on Perplexity.ai and found similar results. This is significant because Perplexity uses a fundamentally different retrieval architecture than the generative engine used in the primary experiments. The consistency across platforms suggests these are not quirks of one system but reflect how language models in general evaluate source quality.

How to optimise for Google AI Overviews

Google AI Overviews select sources through a multi-stage process that is distinct from organic ranking. Understanding that process is necessary for optimisation.

How AI Overviews select sources

Based on available research, Google AI Overviews narrow candidates through a pipeline that moves from semantic retrieval to authority filtering to passage-level extraction. The key signals:

Content structure and extractability. AI Overview extracts favour passages of 134 to 167 words that form self-contained answer units. Approximately 62% of featured content falls within this length range. Pages that bury the answer deep in the text are less likely to be extracted.

E-E-A-T as a binary gate. 96% of AI Overview citations come from sources that clear Google's Experience, Expertise, Authoritativeness, and Trustworthiness threshold. This is not a gradual signal; it functions more like a filter. Sources that do not meet the threshold are excluded from the candidate pool.

Content depth. Pages above 20,000 characters average approximately 10.18 citations each, compared to 2.39 for pages under 500 characters. Comprehensive content dominates citation selection.

Structured data. Pages with Schema markup receive 3.2 times more AI citations than equivalent pages without it. Article, HowTo, FAQ, and Organisation schemas are the most relevant types.

Practical optimisation checklist for AI Overviews

1. Front-load the answer. Place a direct, factual answer to the target query in the first 100 to 150 words of the page. AI Overview extraction heavily weights the opening content.
2. Write extractable passages. Structure key claims as self-contained paragraphs of 134 to 167 words. Each passage should answer one question without requiring surrounding context.
3. Add structured data. Implement Article schema with author, datePublished, and dateModified. Add FAQ schema for question-based content. Add Organisation schema site-wide.
4. Use H2/H3 headings that match query patterns. If people search "how much does AI SEO cost," use that exact phrasing as a heading, then answer it directly beneath.
5. Cite credible sources. The Princeton GEO study found this is one of the three highest-impact strategies. Every factual claim should link to its source.
6. Publish deep content. Thin pages with fewer than 500 characters rarely get cited. The data favours comprehensive coverage.
7. Update regularly. AI Overviews preference fresh content. Add an updatedAt signal (structured data or visible on-page date) and maintain a consistent update cadence.

How to optimise for ChatGPT and Perplexity

ChatGPT and Perplexity use different retrieval systems than Google, which means they require partially different optimisation approaches.

ChatGPT: entity authority and domain trust

ChatGPT uses a retrieval-augmented generation (RAG) system that pulls from multiple search indexes. Ahrefs' research found that ChatGPT generates 1.78 search queries per prompt on average, with 75% of prompts triggering exactly two searches. Only 6.82% of ChatGPT's search results appear in Google's top 10, and 83.39% do not appear in Google's results at all for the same queries.

What ChatGPT favours:

• Third-party brand mentions. Brands are 6.5 times more likely to be cited via third-party sources than their own domain (SE Ranking, 2025). Having other credible sites mention your business matters more than what you publish on your own site.
• Domain authority. High-DR sites receive preferential citation. ChatGPT draws heavily from domains with established trust signals.
• Answer-first page structure. 72.4% of blog posts cited by ChatGPT included a clearly identifiable "answer capsule," a concise 120 to 150 character explanation placed directly after a question-based heading (Search Engine Land audit of nearly two million user sessions).
• Freshness. ChatGPT's traffic share grew 3 times in 9 months. The platform values current information and regularly updated pages.

ChatGPT has a unique behaviour worth noting: there is only a 10% overlap between the pages ChatGPT cites most and the pages that drive the most traffic from ChatGPT. Users click ChatGPT citations when they need to take action (pricing pages, sign-up pages, product pages), not when they need background information.

Perplexity: citations, freshness, and outbound links

Perplexity is the most citation-transparent AI platform. Its entire product identity is built around "answer with sources."

What Perplexity favours:

• Recency. 50% of Perplexity citations come from content published in 2025 alone. Freshness is its single strongest signal. Content updated within 3 to 6 months gets cited 3 to 4 times more than older content.
• Outbound citation density. Pages linking to 5 or more authoritative external sources are cited more frequently by Perplexity than equally strong pages with fewer outbound links.
• Author credentials. Perplexity is selective about authority signals. Detailed author bios, credentials, and links to professional profiles improve citation likelihood.
• Google rankings. Unlike ChatGPT, Perplexity shows 28.6% citation overlap with Google's top 10. Ranking well in Google gives you a meaningful head start with Perplexity.

Cross-platform optimisation

Despite their differences, all AI search platforms share core citation preferences validated by the Princeton GEO research:

• Content with statistics and source citations gets cited up to 40% more than unoptimised content
• Answer-first structure increases extraction probability
• 44% of all LLM citations come from the first 30% of a page's content (Seer Interactive)

The practical approach: write for the shared patterns first (answer-first structure, statistics, citations), then layer platform-specific signals on top.

Traditional SEO is not dead

It is worth stating this plainly, because the marketing industry's appetite for "SEO is dead" narratives is bottomless.

Google processes 5 trillion searches per year. It sends roughly 40% of all website traffic. Organic search drives 53% of all trackable website traffic (BrightEdge).

AI search platforms combined send 0.25% of website traffic.

Google sends approximately 190 times more traffic than ChatGPT alone. Even if AI search traffic doubles or triples in the next year (which the growth trajectory suggests is possible), the absolute gap remains enormous.

For an Australian business relying on organic search for leads and revenue, neglecting traditional SEO in favour of AI SEO would be a serious mistake. The foundation must be traditional optimisation: technical SEO, content quality, backlinks, page speed, Core Web Vitals.

What the data does support is layering AI SEO on top of that foundation. The good news for practitioners: the core GEO strategies (citing sources, adding statistics, writing extractable answer passages, structuring content clearly) are also good practices for traditional SEO and content quality generally. There is significant overlap between "content that ranks well in Google" and "content that gets cited by AI." The additional effort to optimise specifically for AI is incremental, not a wholesale change in approach.

The case for doing both

Consider the maths for an Australian professional services firm:

• Traditional SEO drives 500 organic visits per month at a 2% conversion rate = 10 leads
• AI search drives 5 visits per month at a 15% conversion rate = 0.75 leads

At current volumes, traditional SEO generates 13 times more leads. AI search is a rounding error.

But layer in the growth trajectory (AI search traffic growing at 700% per year) and the brand impression value of being cited by ChatGPT when a potential client asks "who is a good web design agency in Sydney," and the strategic case for AI SEO becomes clear. Not as a replacement. As a complement.

Practical implementation guide

This section translates the research into a concrete workflow.

Phase 1: Audit your current AI visibility (Week 1)

Run 20 to 30 queries relevant to your business across ChatGPT, Perplexity, and Google (to check AI Overviews). Document:

• Which queries trigger AI Overviews in Google
• Whether your brand or competitors are cited in AI Overviews
• Whether your brand appears in ChatGPT and Perplexity responses
• Which competitors are mentioned and what content they publish

Check your GA4 traffic acquisition data. Filter by source to see traffic from chatgpt.com, perplexity.ai, and other AI referrers. Note that 70.6% of AI traffic may be hidden in your "direct" bucket.

Phase 2: Optimise existing content (Weeks 2-4)

Start with your highest-traffic pages. For each page:

1. Add a direct answer to the page's core question in the first 100 to 150 words
2. Add statistics with sources to replace qualitative claims
3. Add relevant expert quotes where available
4. Structure the page with H2/H3 headings that match how people phrase questions
5. Add or update structured data (Article, FAQ, Organisation schemas)
6. Ensure the page is accessible to AI crawlers (check robots.txt for GPTBot, CCBot, PerplexityBot)
7. Update the page's published/modified date

Phase 3: Build entity authority (Ongoing)

Third-party mentions are the strongest signal for ChatGPT citation. Build your brand's presence across the web:

• Contribute expert commentary to industry publications
• Maintain active profiles on LinkedIn, Reddit (where relevant), and YouTube
• Earn mentions in roundups, comparisons, and industry guides
• Publish original research and data that other sites will reference

Phase 4: Create citation-ready content (Ongoing)

When publishing new content, apply GEO principles from the start:

• Open every section with a direct, factual answer (the "answer capsule")
• Include at least 5 cited statistics per 1,000 words
• Link to 5 or more authoritative external sources per page
• Include relevant expert quotes
• Write self-contained paragraphs of 134 to 167 words for key claims
• Add FAQ sections that target "People Also Ask" queries
• Update content every 3 to 6 months to maintain freshness signals

Phase 5: Measure and iterate (Monthly)

Track these metrics:

• AI Overview appearance rate for target keywords (Semrush or Ahrefs)
• Citation rate across ChatGPT, Perplexity, and AI Overviews
• AI referral traffic in GA4 (including estimated dark traffic)
• Conversion rates from AI referral sources compared to organic
• Brand mention frequency across AI platforms

Australian-specific considerations

Search behaviour differences

Australian search volumes are smaller than US volumes, but the competitive dynamics are different. The keyword "ai seo" has 1,000 monthly searches in Australia at $48.59 CPC. That CPC is among the highest in the entire Australian digital marketing keyword set, reflecting intense commercial intent from agencies and consultants.

AI Overviews have rolled out in Australia, though coverage may differ from US levels. Google's expansion has been global but not uniform. Australian businesses should audit their specific target keywords rather than relying on US-centric prevalence data.

The Australian agency landscape

Most Australian SEO agencies have not yet adapted to AI search. Their processes were built around Google rankings, backlinks, and content volume. AI SEO requires different capabilities: structured data implementation, entity authority building, citation monitoring across multiple platforms, and content structured for extractability.

This creates a window of advantage for businesses that move early. The Princeton GEO strategies are not complicated to implement. They require discipline more than technical sophistication. Citing sources, adding statistics, structuring answers clearly: these are editorial practices, not engineering challenges.

AI SEO and content quality

For Australian businesses in regulated industries (legal, financial, healthcare), AI SEO aligns naturally with regulatory expectations. YMYL (Your Money or Your Life) queries show the strongest divergence between traditional rankings and AI citations. AI Overviews for health, finance, and legal queries show only 24% overlap with the top 10 organic results, meaning they draw heavily from authoritative, credible sources outside the first page.

If your business already produces well-sourced, expert-authored content (as professional services firms should), you are closer to AI citation readiness than you might think.

What gets cited: a summary of the evidence

Synthesising across the Princeton GEO study, the Ahrefs citation research, the Semrush domain analysis, and the multiple conversion studies, the content characteristics that drive AI citations are:

The anti-pattern is clear: thin content without sources, packed with keywords, is the worst possible approach for AI SEO. It actively reduces visibility.

Methodology

This report synthesises data from the following primary sources:

Academic research:

• The Princeton/Georgia Tech GEO paper tested nine content optimisation methods across 10,000 queries using a purpose-built benchmark (GEO-bench). Results were replicated on Perplexity. Published at KDD 2024, the top academic venue for data mining research.

Traffic and citation studies:

• Ahrefs Web Analytics tracks referral traffic across 76,000+ websites. Their ChatGPT vs Google comparison uses publicly available data updated monthly.
• Ahrefs Brand Radar analysed citation overlap across 15,000 prompts for four AI assistants.
• Semrush analysed 230,000 prompts and 100 million AI citations across ChatGPT, Google AI Mode, and Perplexity over 13 weeks.
• Semrush Sensor tracks AI Overview prevalence across 10 million keywords.

Conversion studies:

• Five independent studies measured AI search conversion rates with sample sizes ranging from 10,969 sessions (Seer Interactive) to 12.3 million visits (Superprompt).

Where sources disagree (particularly on AI Overview prevalence), we present multiple figures and note the methodological differences. The AI search landscape is evolving rapidly, and measurement approaches are not yet standardised.

All data cited in this report is from publicly available sources. Links are provided for verification. Our own original analysis is limited to synthesising these sources and applying the findings to the Australian market context.

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Sources

• Aggarwal, P. et al. GEO: Generative Engine Optimization, KDD 2024 - The foundational academic paper on AI content optimisation. Nine methods tested across 10,000 queries. Up to 40% visibility improvement from citations, statistics, and quotations.
• Ahrefs: ChatGPT Has 12% of Google's Search Volume but Google Sends 190x More Traffic - February 2026 analysis of ChatGPT vs Google search volume, traffic share, and CTR differences.
• Ahrefs: Only 12% of AI Cited URLs Rank in Google's Top 10 - 15,000 prompt study showing 12% citation overlap between AI assistants and Google rankings.
• Ahrefs: The ChatGPT Traffic Playbook - AI traffic conversion data (23x premium), growth rates, and tracking methodology.
• Ahrefs: Is ChatGPT Really Powered by Google? - Analysis of 118,931 fan-out queries showing ChatGPT's multi-source retrieval approach.
• Ahrefs: ChatGPT May Scrape Google, but the Results Don't Match - Three-study series on citation overlap between ChatGPT, Perplexity, and Google.
• Ahrefs Web Analytics: AI vs Search Traffic - Live dashboard tracking referral traffic from Google vs AI assistants across 76,000+ websites.
• Semrush: The Most-Cited Domains in AI (3-Month Study) - 230,000 prompts, 100 million citations across ChatGPT, AI Mode, and Perplexity.
• Semrush: We Studied 200,000 AI Overviews - 200,000 keywords analysed for AI Overview patterns, industry distribution, and URL overlap.
• Semrush: AI Overviews Impact on Search in 2025 - 10M+ keywords, clickstream data, AI Overview prevalence and growth trends.
• SERPs.io: AI Search Traffic Converts 23x Higher Than Organic - Synthesis of five independent conversion studies with methodology comparison.
• Digital Bloom: Gen AI Website Traffic Share Report, February 2026 - Platform traffic share, conversion rates, dark traffic analysis across 446,405 visits.
• Loamly: State of AI Traffic 2026 Benchmark Report - Year-over-year growth rates, platform distribution, industry benchmarks.
• ZipTie.dev: Google AI Overviews Source Selection - Reverse-engineering of AI Overview source selection pipeline, E-E-A-T analysis.
• Digital Applied: AI Search Citations Drop to 38% from Top 10 Pages - 863,000 SERPs analysed for AI citation source distribution.
• Digital Applied: Google AI Overviews Surge 58% - AI Overview growth from 34.5% to 48% prevalence in three months.
• SearchSignal: 2026 AI Search Referrals and Citations Benchmark - 31 source-backed statistics on AI search impact.
• DemandSage: 50 AI Overviews Statistics 2026 - Comprehensive statistics compilation on AI Overview prevalence, citations, and CTR impact.
• Seenos.ai: Google AI Overviews SEO Impact - 50,000+ queries across 12 verticals, Q3 2025 through Q1 2026.
• AI In Marketing: GEO Paper Analysis - Detailed practitioner analysis of the Princeton GEO paper findings.
• SEO Juice: How to Get Cited by ChatGPT, Perplexity, and Google AI - 7-week case study of improving AI citation through entity authority building.
• NeuronWriter: How to Rank in Perplexity and Get Cited by ChatGPT - Answer capsule strategy, original data impact, authority signals.
• SerpNap: GEO Content Playbook - Platform-specific GEO strategies with citation tracking framework.
• Search Engine Land: Google's AI Mode is Citing Google More Than Any Other Site - SE Ranking analysis of 68,313 keywords and 1.3 million AI Mode citations.
• BrightEdge: Channel Share of Traffic - Organic search drives 53% of all trackable website traffic.