Videos

AI search visibility is no longer determined by what sits on your website alone.AI systems can surface information from a much wider ecosystem: niche publications, communities, reviews, third-party mentions, forums, citations and other sources that shape how a brand is understood and recommended.In this episode of #SEOTalk, we discuss why the traditional SEO audit needs to evolve into something broader. The conversation explores how brands should assess their presence across external platforms, how reputation and AI visibility are becoming closely connected, and why being mentioned is not enough if the information about your brand is inaccurate or inconsistent.In this episode, we discuss:• Why an AI Search Audit must go beyond your own domain • The role of third-party sources, communities and brand reputation • Why SEO fundamentals still matter, even when AI agents behave differently • How to assess where and how your brand appears across AI search • The growing overlap between SEO, GEO/AEO, ORM, brand and demand generation • Why every industry may need a different AI visibility playbook • How brands can start scoring technical, off-site, external-source and visibility signals • Why the end goal should be recommendation and business impact, not just citationOne of the strongest takeaways from the discussion is that AI Search Audits are beginning to develop their own frameworks. Instead of auditing only technical SEO and on-page factors, teams are starting to score external presence, AI visibility and other signals, then track those scores over time.If your current AI Search Audit stops at your website, this episode will help you think about what you may be missing.
AI Search Audit: Why Your Own Site Isn't Enough
Ranking on Google no longer guarantees visibility across ChatGPT, Gemini, Claude, Grok, or AI Overviews.In this episode of #SEOTalk Spaces, we explore what authority means in AI search, why some brands are repeatedly cited while others remain invisible, and how businesses can build stronger signals across their website, social platforms, communities, trusted publications, and third-party conversations.The discussion moves beyond citation tracking and tackles the harder business question: Does AI visibility create meaningful traffic, pipeline, and revenue?• Why rankings and AI citations measure different things • How third-party mentions shape brand authority • The role of Reddit, YouTube, X, reviews, and niche communities • Why established brands may have an advantage in AI systems • How model training data and query fan-out can influence visibility • Whether newer brands can build authority quickly • Why publishing more AI-generated content is not a strategy • How sales calls, support tickets, churn feedback, and internal data can create valuable content • Why content should be measured by conversion and pipeline, not traffic alone • The technical SEO fundamentals that still matter • Why brands should avoid overengineering AI search with unnecessary complexityThe key takeaway is clear: Authority cannot be self-declared. It is earned through consistent expertise, useful content, credible third-party recognition, and a clear presence wherever your audience and AI systems look for information.Listen to the full conversation for a practical and candid view of what it takes to build an authority-led AI search strategy
How to Build an Authority-Led AI Search Strategy
What happens when the customer no longer searches, compares or even visits your website before making a purchase?In this episode of #SEOTalk Spaces, we explore the rise of agentic commerce, where AI agents can discover products, evaluate options, check policies, compare prices and eventually complete transactions on behalf of users.The conversation examines the new “decision layer” forming between brands and buyers. A layer where AI systems may decide which products are visible, trusted and recommended before a human enters the journey.In this episode, we discuss:• How agentic commerce could change product discovery and online buying • Which categories are likely to see early adoption • Why product feeds, structured data and technical SEO matter more • How brands can become discoverable and understandable to AI agents • The growing importance of reviews, policies, inventory and product-page clarity • Whether algorithmic bias could replace human bias • How trust, payment security and authorization may affect adoption • Why traditional traffic and attribution models may no longer tell the full story • The role of AI platforms, marketplaces and payment providers in controlling the customer journey • What e-commerce brands should start auditing todayAs AI becomes more involved in the buying process, brands may need to optimise not only for human attention, but also for machine interpretation, trust and actionability.The key question is no longer whether AI will influence commerce.It is: When AI buys, who really wins?
Agentic Commerce: When AI Buys, Who Wins?
What makes Google choose one source over another in AI Overviews?In this SEOTalk webinar, we’ll break down what gets cited, why citation patterns differ, and what SEOs, publishers, and brands can do to improve their chances of being referenced in AI-generated answers.Join us for a practical discussion with Vijay Chauhan on relevance, authority, content structure, freshness, and the changing role of rankings in AI Search.
Decoding Google AI Overview: What Gets Cited And Why? | Vijay Chauhan
AI Search strategies are being built. Audits are happening. Gaps are being mapped. Dashboards are being created.Teams are experimenting with ChatGPT, Claude, Perplexity, Google AI Overviews, citations, mentions, and AI visibility tracking.But here is the uncomfortable truth:Many AI Search strategies do not fail because the strategy is weak.They fail because leadership never truly buys in.In this episode of #SEOTalk, we discuss why AI Search needs C-Suite attention and why SEO teams cannot drive this change alone.The conversation goes beyond rankings, traffic, and impressions. We look at how AI Search connects with revenue, brand visibility, attribution, content quality, reputation, product clarity, customer trust, and cross-functional execution.We also discuss the practical blockers SEO teams face when presenting AI Search strategies to founders, CMOs, and leadership teams.What we cover in this episode:• Why AI Search strategies often remain stuck in presentations • Why leadership buy-in matters more than technical explanation • How to connect AI Search outcomes with business metrics • Why attribution and ROI are major blockers today • Why vanity metrics like mentions and citations need business context • How pilots and MVPs can help build early confidence • Why brand building reduces dependency on paid channels • How SEO, PR, brand, content, product, CRO, and leadership need to work together • Why founders and CMOs may look at AI Search differently • What SEO teams should do to make AI Search a boardroom conversationAI Search is not just a new SEO layer.It is a business visibility challenge.And the brands that win will be the ones that can align leadership, build trust, create stronger content, and connect organic visibility to real business outcomes.
Why AI Search Needs C-Suite Buy-In?
AI Search is changing SEO, but not every new tactic deserves your time, budget, or panic.In this #SEOTalk Live session, we spoke with Harpreet Singh, AI Search consultant and publisher of SEO Espresso, about the real state of AI Search, GEO, AEO, LLMO, and what SEO teams should actually focus on.The discussion cuts through the noise around new acronyms and gets into the practical side of AI Search: what still comes from strong SEO fundamentals, what genuinely needs to change, and what brands risk getting wrong if they chase short-term AI visibility.In this episode, we discuss:📌 Is GEO/AEO/LLMO really different from SEO, or just SEO evolving? 📌 Where traditional SEO ends and AI Search strategy begins 📌 Why SEOs are now part of social, video, PR, and brand conversations 📌 Short-term AI Search tactics that are worth testing 📌 Why video content should be a priority for brands 📌 How third-party platforms, reviews, PR, YouTube, Reddit, and G2 influence AI visibility 📌 Why AI citations can become a vanity metric 📌 The trade-off between visibility, traffic, quality, and trust 📌 Why over-optimizing for AI Search can damage long-term organic performance 📌 What small businesses should do first before spending on AI Search strategy 📌 Why brands should focus on mentions, messaging consistency, and reputation signalsOne of the biggest takeaways from the conversation:AI Search is not a reason to abandon SEO fundamentals.It is a reason to expand how we think about visibility, trust, content distribution, brand mentions, and user intent.Harpreet also shares real experiments, including how press releases can influence AI-generated answers, why this creates trust issues, and why marketers need to be careful about treating AI outputs as absolute truth.This episode is useful for SEO professionals, content marketers, founders, digital marketers, and marketing leaders who want a clear, practical, and grounded view of AI Search without the hype.Watch the full conversation and share your thoughts in the comments:What is the biggest trade-off in AI Search today: visibility vs traffic, or scale vs quality?Subscribe to The SEOTalkers for more practical conversations on SEO, AI Search, content strategy, and digital growth.
AI Search Tactics, Strategy, and the Real Trade offs with Hapreet Singh | SEOTalk Webinar
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