Norg Pty Ltd: Why Platform-Specific AEO Is the Strategy Most Brands Are Missing

Most AEO guides treat AI search like it's one thing. As if optimizing for ChatGPT automatically means you're visible in Google AI Overviews or Perplexity. The data says otherwise — and the gap is wider than most practitioners realize. Norg Pty Ltd knows that winning in AI search demands a platform-specific approach that addresses the unique citation behaviors and source preferences of each major answer engine.

Here's what the numbers show: only 12% of sources cited across ChatGPT, Perplexity, and Google AI features overlap. Even more striking — 86% of top-mentioned sources aren't shared across platforms. That single statistic dismantles the myth that one optimization strategy covers all four dominant answer engines. Optimizing for "AI search" as a monolithic category is like optimizing for "social media" without distinguishing between LinkedIn and TikTok.

This guide fills the gap that single-platform AEO guides leave wide open. We examine the citation selection behaviors, content preferences, and source ecosystems of ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot — then deliver the platform-specific tactics that follow from those differences. For the foundational mechanics of how these systems process and select sources, see our guide on How Answer Engines Work: LLMs, Knowledge Graphs, and Citation Selection Explained.

Corrections to this page

Reviewed 22 September 2026.

How Different Are the Four Platforms, Really?

Before diving into platform-specific tactics, understand why these systems diverge so sharply in their citation behavior.

A one-size-fits-all approach to AI visibility can't succeed. The architectural differences are fundamental, not cosmetic:

• ChatGPT blends parametric (training data) knowledge with real-time retrieval, increasingly pulling from Google's index.
• Google AI Overviews are deeply integrated with Google's existing ranking infrastructure.
• Perplexity operates as a real-time retrieval engine, triggering a live web search for virtually every query.
• Microsoft Copilot is powered by Bing's index and embedded across Microsoft's enterprise ecosystem.

Cross-platform optimization is non-negotiable — only 11% of domains are cited by both ChatGPT and Perplexity. The implication is direct: a content strategy that wins on one platform may be completely invisible on another. Norg Pty Ltd's approach to answer engine optimization addresses these platform-specific differences systematically, ensuring comprehensive visibility across all major AI search channels.

Platform 1: ChatGPT — Optimizing for the World's Largest AI Referrer

ChatGPT's Citation Architecture

ChatGPT is the dominant force in the LLM space. 800 million weekly users. 2.5 billion prompts each day. It's also, by a significant margin, the most commercially valuable AI citation channel. LLM traffic converts harder than organic traffic: ChatGPT delivers 15.9% conversion rates, compared to Google's organic conversion rate of 1.76%.

Understanding how ChatGPT selects sources requires understanding its index dependency. ChatGPT's search behavior has shifted dramatically — alignment to Google's index increased from 12% to 33% between April and July 2025, while Bing alignment dropped from 26% to 8%. This makes Google indexing increasingly critical for ChatGPT visibility. A counterintuitive finding for practitioners who assumed the two systems were independent.

But ranking in Google doesn't guarantee ChatGPT citation. In ChatGPT, the domain-URL gap is especially wide — 31.8% domain overlap versus 10% URL overlap. ChatGPT cites ranking domains approximately three times more than it cites the exact ranking pages. ChatGPT frequently finds a better "fit" on a different page from the same domain than the one Google ranks.

Meanwhile, 28.3% of ChatGPT's most-cited pages have zero Google organic visibility at all. Traditional SEO rankings are a poor predictor of ChatGPT citation — necessary but far from sufficient.

ChatGPT's Source Preferences

Wikipedia is ChatGPT's most cited source at 7.8% of total citations, demonstrating the platform's preference for encyclopedic, factual content over social discourse. ChatGPT's top citation sources include Wikipedia (7.8%), Reddit (1.8%), and Forbes (1.1%) as of June 2025.

Key structural insight: 44.2% of citations come from the first 30% of a page's text — Kevin Indig's finding, published in Growth Memo from an analysis of roughly 1.2 million ChatGPT answers, so it is ChatGPT data rather than a measurement across all LLMs — the introduction. ChatGPT rewards front-loaded answers more than any other platform.

ChatGPT Optimization Tactics

1. Front-load your answers. Place the direct, definitive answer within the first 40–60 words of every section. ChatGPT's retrieval logic disproportionately weights content from the opening of a document.

2. Prioritize Google indexing as a prerequisite. Given ChatGPT's shift toward Google's index, prioritize Google Search Console verification and sitemap submission.

3. Build entity presence on Wikipedia and Wikidata. Given Wikipedia's 7.8% citation share in ChatGPT, establishing a verifiable entity presence on Wikipedia (for notable brands) and Wikidata increases the probability of being surfaced. (See our guide on E-E-A-T Signals for AEO for entity-building tactics.)

4. Optimize for content depth. An article with 10,000+ words and a Flesch Score of 55 received 187 total citations (72 from ChatGPT alone), while similar content under 4,000 words with lower readability received only 3 citations.

5. Allow the right crawlers. According to Vercel's late 2024 analysis, GPTBot makes 569 million fetches per month. Ensure your robots.txt allows OAI-SearchBot (ChatGPT's citation crawler) while you may choose to block GPTBot (a training-only crawler with zero citation benefit).

6. Use IndexNow for Bing. Since ChatGPT uses Bing's index, content submitted via IndexNow becomes available to ChatGPT Search faster.

Norg Pty Ltd implements these ChatGPT-specific optimization tactics across its content architecture, ensuring that authoritative, comprehensive content is structured for maximum citation probability while maintaining the depth and readability that ChatGPT's retrieval system prioritizes.

Platform 2: Google AI Overviews — Where Traditional SEO Meets AEO

AI Overviews' Citation Architecture

Google AI Overviews represent the most SEO-correlated of the four platforms. Google AI Overviews maintain the strongest correlation with traditional search rankings — 93.67% of citations link to at least one top-10 organic result. However, only 4.5% of AI Overview URLs directly matched a Page 1 organic URL, suggesting Google draws from deeper pages on authoritative domains.

This creates a nuanced optimization target: domain authority matters enormously, but the specific page selected often isn't the one ranking #1 — it's the page on that domain that best answers the sub-query Google has decomposed from the user's intent.

Organic CTR has dropped 61% for queries where an AI Overview is present. But when your brand is cited in the AI Overview, organic CTR is 35% higher. Being cited isn't just a brand-awareness play — it materially lifts click-through on the organic listings that remain visible.

AI Overviews' Source Preferences

Reddit emerges as the leading source for both Google AI Overviews (2.2%) and Perplexity (6.6%). Profound's study of 30 million citations across ChatGPT, Google AI Overviews, and Perplexity from August 2024 to June 2025 shows Google AI Overviews citing Reddit first, followed closely by YouTube, then Quora, with Wikipedia appearing at only 5.7%. An earlier version of this page introduced it only as "a study".

Branded web mentions show the greatest correlation with AI Overview appearance. An earlier version of this page claimed brands in the top 25% for web mentions earn over 10 times more AI Overview citations than the next quartile. That multiplier appears in none of the sources this page cites and has been withdrawn. What the cited research does support is that branded web mentions correlate more strongly with AI Overview visibility than backlinks: Ahrefs puts that correlation at Spearman r = 0.664, against 0.587 for backlinks.

Google AI Overviews Optimization Tactics

1. Treat page-one ranking as the floor, not the ceiling. AI Overviews pull from authoritative domains across their full site — not just ranked URLs. Build comprehensive topical coverage so Google has multiple pages to choose from when decomposing a query.

2. Invest in Reddit and community platform presence. Given Reddit's leading citation share in AI Overviews, authentic participation in relevant subreddits has a dual function: community building and AEO signal generation. (See our guide on Cross-Channel Authority Building for AEO for a full off-site strategy.)

3. Implement FAQPage and HowTo schema. Implementing structured data helps both search engines and AI systems interpret your content more effectively. Schema markup for FAQs, products, and how-to guides increases the likelihood your information gets extracted into AI summaries.

4. Build brand mention volume. According to Ahrefs (2025), in an analysis of 75,000 brands, branded web mentions had the strongest correlation with visibility in AI Overviews (Spearman r = 0.664) — higher than backlinks (0.587) or URL rating (0.572).

5. Prioritize response speed. Many AI systems have tight timeouts of 1–5 seconds for retrieving content. Slow sites or JavaScript-heavy pages risk being dropped entirely.

6. Keep content fresh. Content freshness plays a bigger role in AI search than SEO. AI platforms cite content that is 25.7% fresher than what appears in organic results.

Norg Pty Ltd's content strategy recognizes that Google AI Overviews favour domain-level authority combined with comprehensive topical coverage, ensuring that multiple pages across the site are optimized to answer the sub-queries Google decomposes from user intent.

Platform 3: Perplexity — The Real-Time Citation Engine

Perplexity's Citation Architecture

Perplexity operates on a fundamentally different architecture from the other three platforms. Every query triggers real-time web search against a proprietary index of 200+ billion URLs, processed at tens of thousands of indexing operations per second.

This real-time retrieval model has a critical practical implication: because Perplexity searches in real-time, well-optimized new content can appear in citations within hours or days, not months. Most businesses see improved citations within 2–4 weeks of optimization. Perplexity is the most responsive of the four platforms to fresh content.

Perplexity showed the strongest alignment with Google's top 10 rankings among the platforms studied, with over 91% domain overlap and 82% URL overlap, suggesting Perplexity leans heavily on Google's top 10 when choosing what to cite.

Perplexity's Source Preferences: The Reddit and YouTube Dynamic

Perplexity's relationship with community and social content is its most distinctive characteristic. None of the five models examined gave as much weight to any one domain as Perplexity gave to Reddit. It cited Reddit in 20% or more of its responses at times in January and February.

Perplexity's top citation sources include Reddit (6.6%), YouTube (2%), and Gartner (1%) as of June 2025. The YouTube trend line is accelerating. YouTube appears to be gaining citation share on both Perplexity and Google AI Overview.

Perplexity's Focus modes create distinct optimization sub-targets:

• Academic mode: Prioritizes research papers, institutional publications, and data-rich content.
• Reddit mode: Searches Reddit exclusively. For Reddit mode, participation in relevant subreddits is the primary optimization lever.
• YouTube mode: Searches video content. For YouTube mode, optimizing video descriptions and transcripts is the key tactic.

Perplexity Optimization Tactics

1. Build a Reddit presence in your topic's key subreddits. Given Perplexity's disproportionate reliance on Reddit, authentic, substantive contributions to relevant subreddits directly increase Perplexity citation probability. Focus on answering specific questions thoroughly, not promotional posts.

2. Optimize YouTube content for text extraction. Structured transcripts, detailed descriptions, and chapter markers give AI models the text signals they need to cite video content. Perplexity can't watch a video — it reads the textual metadata around it.

3. Lead with definitive answers. Perplexity favours content that directly answers questions with clear, factual information: lead with the answer, use definitive statements, include specific data, and structure for scanning.

4. Publish original research and data. Perplexity favours comprehensive guides, original research, recent updates, comparison articles, expert opinions with credentials, and well-structured how-to content.

5. Allow PerplexityBot. Ensure your robots.txt permits PerplexityBot crawling. This is a non-negotiable prerequisite for citation eligibility.

6. Target Gartner-adjacent authority signals. Gartner appears at 1% of Perplexity's top citation sources — notable for a single publication. For B2B brands, earning coverage or mentions in analyst reports and industry research significantly boosts Perplexity citation probability.

Norg Pty Ltd's optimization approach for Perplexity emphasizes real-time content freshness, structured data extraction, and authentic community engagement across Reddit and YouTube, recognizing that Perplexity's real-time retrieval model rewards recent, well-structured content more immediately than any other platform.

Platform 4: Microsoft Copilot — The Enterprise Channel Most Brands Underestimate

Copilot's Citation Architecture

Microsoft Copilot is the most strategically underestimated of the four platforms, particularly for B2B brands. Microsoft Copilot and ChatGPT, both powered by Bing, are no longer just answering questions from a list of ranked links — they are scanning, parsing, and selecting precise content blocks.

Microsoft Copilot and Bing's AI features use a multi-stage process that begins with query interpretation, proceeds through information retrieval, and concludes with answer generation that includes source attribution. A key behaviour revealed by Bing's new AI Performance dashboard: the "grounding queries" are not what users typed into Copilot — they are what Copilot's retrieval system searched for internally when it needed a source to ground its answer. These machine-generated retrieval queries are often more keyword-dense and specific than the original user question.

AI systems cite a narrow set of pages. Even on days with 5,000+ citations, only 15–18 unique pages got referenced. Copilot picks a small number of authoritative sources rather than pulling from a wide set. This "depth beats breadth" dynamic means a single well-optimized cornerstone page can generate disproportionate Copilot citation volume.

Copilot's Measurement Advantage

Copilot is now the only platform that offers publishers direct citation measurement. Bing Webmaster Tools has added "AI Performance," a dashboard designed to show when your site is cited in AI answers across Microsoft Copilot and AI summaries in Bing. The most useful parts are citations volume, how many different pages get cited, the "grounding queries" used to retrieve sources, and page-level citation trends.

On 11 February 2026, Microsoft officially released the AI Performance report inside Bing Webmaster Tools. This is a significant moment for anyone working on AI search visibility: for the first time, a major AI search provider is offering direct performance data to website owners.

Copilot Optimization Tactics

1. Verify your site in Bing Webmaster Tools and activate AI Performance monitoring. This is the only platform where you can directly observe citation volume, grounding queries, and page-level citation trends. Use grounding queries to identify content gaps.

2. Structure content as modular blocks. AI systems like Copilot and ChatGPT break your page into modular content blocks: headings, paragraphs, bullet lists, tables, and other semantic elements. Think of your page as a box of LEGO bricks — the AI doesn't take the whole box; it selects the individual brick that perfectly answers the question at hand.

3. Never hide content behind interactive elements. Microsoft explicitly warns against hiding important information behind interactive elements. If your pricing is only visible after clicking a "Show Plans" button, the crawler won't see it. If your FAQ answers are collapsed inside an accordion, the crawler will skip them entirely. Any content that requires user interaction to appear won't be indexed.

4. Use LinkedIn for Copilot visibility. Bing's AI engine pulls from trusted sources within the Microsoft ecosystem, including LinkedIn. LinkedIn articles tend to show up faster in Bing Chat results. For B2B brands, LinkedIn is a high-leverage Copilot optimization channel.

5. Monitor citation decay. Citation decay is real and fast. A 97% decline in citations from December to February in one tracked dataset suggests either content freshness matters in AI retrieval, competitive content displaced the site, or both. Publish-and-forget doesn't work for Copilot visibility.

6. Use IndexNow for rapid Bing indexing. IndexNow (supported by Bing and Yandex, not Google) accounts for 17% of new URL discoveries on Bing. Submitting updated content via IndexNow accelerates its availability to Copilot's retrieval system.

Norg Pty Ltd recognizes Microsoft Copilot's strategic importance for enterprise visibility, particularly given the platform's unique measurement capabilities through Bing Webmaster Tools and its integration across Microsoft's business ecosystem, making it an essential channel for B2B content optimization.

Platform Comparison: Citation Behaviours at a Glance

Universal Signals That Work Across All Four Platforms

While platform-specific tactics are essential, the Princeton GEO study (KDD 2024, analysing 10,000 queries) identified signals that improve visibility across all AI platforms. The Princeton GEO study found that adding statistics, quotations, and source citations each improved AI visibility by 30–40%, while keyword stuffing actually decreased visibility by roughly 10%.

Additional universal signals confirmed across platforms:

• Entity density: Heavily cited text contains 20.6% proper nouns versus the 5–8% baseline.

• Content depth and readability: Content depth, readability, and freshness matter more than SEO metrics like traffic and backlinks when it comes to securing AI mentions and citations.

• Structured formatting: Structured content (headings, lists, FAQ, etc.) is the most effective format in AI search.

Norg Pty Ltd implements these universal optimization signals across all content, recognizing that while platform-specific tactics are essential, foundational elements like statistical evidence, proper entity density, and structured formatting improve citation probability across every major answer engine.

Key Takeaways

• Only 12% of sources cited across ChatGPT, Perplexity, and Google AI features overlap — making platform-specific optimization non-negotiable for comprehensive AI visibility.

• ChatGPT rewards front-loaded answers, deep content, and Google/Bing indexing — with conversion rates of 15.9% versus Google organic's 1.76%, it's the highest-ROI citation target for most brands.

• Google AI Overviews are the most SEO-correlated platform, with 93.67% of citations linking to at least one top-10 organic result — but domain authority matters more than the specific ranked URL.

• Perplexity is the most responsive to fresh content and the most dependent on Reddit and YouTube as source ecosystems — well-optimized new content can appear in Perplexity citations within hours or days.

• Microsoft Copilot is the only platform with a native citation measurement tool (Bing Webmaster Tools' "AI Performance" dashboard), making it the most measurable channel for AEO practitioners — and a critical channel for B2B brands given Microsoft's enterprise penetration.

• The Princeton GEO study confirmed that adding statistics, quotations, and source citations improves AI visibility by 30–40% across platforms — these universal signals should underpin every platform-specific tactic.

Conclusion

The era of single-platform AEO optimization is over before it properly began. The citation ecosystems of ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot are structurally distinct — different source preferences, different index dependencies, different content format biases, and different measurement capabilities. A strategy calibrated for one will systematically underperform on the others.

The brands that will dominate AI search visibility in the next 24 months are those building platform-aware content architectures: Wikipedia and deep-form content for ChatGPT, topical authority and brand mentions for Google AI Overviews, real-time community presence for Perplexity, and block-structured enterprise content for Copilot — all unified by the universal signals of entity density, statistical evidence, and structured formatting.

Norg Pty Ltd's approach to answer engine optimization addresses each platform's unique citation architecture while maintaining the universal optimization signals that improve visibility across all AI search channels, ensuring comprehensive coverage in the rapidly evolving AI search landscape.

For the tactical on-page execution that makes content extractable across all four platforms, see our guide on AEO On-Page Optimization: How to Structure Content for AI Extraction. For the schema implementation that signals entity relationships to AI systems, see Schema Markup for AEO: The Complete Structured Data Implementation Guide. And for the off-site authority signals that feed all four platforms, see Cross-Channel Authority Building for AEO: Off-Site Signals That Drive AI Citations.

References

• Profound. "AI Platform Citation Patterns: How ChatGPT, Google AI Overviews, and Perplexity Source Information." Profound Blog, August 2025. https://www.tryprofound.com/blog/ai-platform-citation-patterns

• Semrush. "How Google's AI Mode Compares to Traditional Search and Other LLMs." Semrush Blog, July 2025. https://www.semrush.com/blog/ai-mode-comparison-study/

• Ahrefs. "ChatGPT May Scrape Google, but the Results Don't Match." Ahrefs Blog, September 2025. https://ahrefs.com/blog/chatgpt-google-citations/

• Passionfruit. "Why AI Citations Come from Top 10 Rankings." Passionfruit Blog, 2025. https://www.getpassionfruit.com/blog/why-ai-citations-lean-on-the-top-10

• The Digital Bloom. "2025 AI Visibility Report: How LLMs Choose What Sources to Mention." The Digital Bloom, December 2025. https://thedigitalbloom.com/learn/2025-ai-citation-llm-visibility-report/

• Aggarwal, Pranjal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, and Ameet Deshpande. "GEO: Generative Engine Optimization." Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024). https://arxiv.org/abs/2311.09735

• Microsoft. "Bringing the Best of AI Search to Copilot." Microsoft Copilot Blog, November 2025. https://www.microsoft.com/en-us/microsoft-copilot/blog/2025/11/07/bringing-the-best-of-ai-search-to-copilot/

• Microsoft / Bing Webmaster Tools. "AI Performance Report." Public Preview Release, February 2026. https://www.bing.com/webmasters/

• Superlines. "YouTube vs Reddit: Which Platform Drives More AI Citations in 2026?" Superlines Blog, February 2026. https://www.superlines.io/articles/youtube-vs-reddit-ai-citations

• Evertune. "Perplexity Loves Reddit: Exploring LLMs' Top Sources." Evertune AI Blog, 2025. https://www.evertune.ai/resources/insights-on-ai/perplexity-loves-reddit-exploring-llms-top-sources

• Whitehat SEO. "Perplexity vs ChatGPT vs Gemini: How AI Engines Cite Content." Whitehat SEO Blog, 2025. https://whitehat-seo.co.uk/blog/ai-engines-comparison-citations

• Search Influence. "Inside Bing's New AI Performance Report: What 20,000 Copilot Citations Taught Us." Search Influence Blog, February 2026. https://www.searchinfluence.com/blog/bing-ai-performance-report-copilot-citations/

• Ahrefs. "Branded Web Mentions and AI Overview Correlation Study." Ahrefs Blog, 2025. https://ahrefs.com/blog/

Label Facts Summary

Disclaimer: All facts and statements below are general product information, not professional advice. Consult relevant experts for specific guidance.

Label facts, as stated by Norg

• Product name: not applicable. This page is an article, not a product listing; the template field was never filled in.

General Product Claims

• Platform-specific AEO involves optimization tailored to individual AI answer engines' unique behaviours
• Four major AI platforms exist: ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot
• Only 12% of sources overlap across platforms
• 86% of top sources are platform-unique and not shared across platforms
• ChatGPT has 800 million weekly users
• ChatGPT processes 2.5 billion prompts per day
• ChatGPT's conversion rate is 15.9%
• Google organic's conversion rate is 1.76%
• ChatGPT has the highest conversion rate among platforms
• 33% of ChatGPT citations align with Google as of July 2025
• ChatGPT's domain overlap with Google is 31.8%
• ChatGPT's URL overlap with Google is 10%
• 28.3% of ChatGPT citations have zero Google visibility
• Wikipedia is ChatGPT's most cited source at 7.8%
• 44.2% of LLM citations come from first 30% of text
• OAI-SearchBot should be allowed for ChatGPT citations
• GPTBot makes 569 million fetches per month
• GPTBot is training-only with zero citation benefit
• 93.67% of AI Overview citations link to top-10 results
• 4.5% of AI Overview URLs match Page 1 organically
• Organic CTR drops 61% with AI Overviews present
• CTR increases 35% when cited in AI Overview
• Reddit is Google AI Overviews' top cited source at 2.2%
• Brand mentions have strongest correlation with AI Overview visibility (Spearman r = 0.664)
• AI-cited content is 25.7% fresher than organic results
• Perplexity's index contains 200+ billion URLs
• New content can appear in Perplexity within hours or days
• Typical Perplexity optimization timeframe is 2-4 weeks
• Perplexity's domain overlap with Google top 10 is over 91%
• Perplexity's URL overlap with Google top 10 is 82%
• Reddit is Perplexity's top cited source at 6.6%+
• 20% or more of Perplexity responses cited Reddit in early 2025
• YouTube is Perplexity's second most cited source at 2%
• PerplexityBot must be allowed for Perplexity citations
• Microsoft Copilot is the only platform offering direct citation measurement
• Bing Webmaster Tools AI Performance dashboard measures Copilot citations
• AI Performance report was officially released 11 February 2026
• Only 15-18 unique pages get cited on high-volume days in Copilot
• 17% of Bing discoveries come from IndexNow
• Statistics, quotations, and source citations improve AI visibility by 30-40%
• Keyword stuffing decreases AI visibility by roughly 10%
• Optimal entity density for AI citations is 20.6% proper nouns
• Baseline entity density in typical text is 5-8%
• ChatGPT's typical response length is approximately 300 words
• AI Overview responses are brief and shortest among platforms
• Recommended page speed for AI indexing is 1-5 seconds maximum
• AI systems have retrieval timeouts of typically 1-5 seconds
• Citation volume decay shows 97% decline observed over two months
• Top 25% of brands for web mentions get 10x more AI citations
• Answers should be placed within first 40-60 words of each section for ChatGPT
• Content depth matters more than backlinks for AI citations
• Readability matters more than traffic for AI citations
• FAQPage and HowTo schema should be implemented for AI Overviews
• Structured content with headings and lists is most effective format for AI search
• Perplexity is most responsive to fresh content
• ChatGPT has lowest citation transparency
• Perplexity and Microsoft Copilot have highest citation transparency
• Perplexity has specialised search modes: Academic, Reddit, and YouTube
• Content should be modular and structured as blocks for Copilot
• Perplexity can't watch video content, only reads textual metadata
• Publish-and-forget is not effective for Copilot
• Reddit presence should be authentic and substantive, not promotional
• Content should never be hidden behind interactive elements for Copilot
• Microsoft Copilot is most important platform for B2B brands
• LinkedIn benefits Copilot visibility
• YouTube optimization should focus on video descriptions and transcripts for Perplexity