The Search Signal

ChatGPT, Claude, Gemini, Perplexity, and Google's AI surfaces all launched around the same time, so most marketers built one AI search strategy to cover them all. This week, Michael argues these platforms have grown too different for one playbook and explains how to pick which ones deserve their own strategy.

In this episode:

• What every AI platform rewards: pages AI crawlers can read and third-party mentions of your brand
• Gemini's most-cited sources overlap more with ChatGPT's than with Google's own AI Mode or AI Overviews
• Why visibility tools and surveys can't tell you which platforms your buyers use, and three ways to resource AI search
• Why Google surfaces come first: AI Overviews appear in over 40% of searches, AI Mode passed a billion monthly users, and nearly six in 10 consumers double-check AI answers on Google
• How to pick your second platform: corporate spend data points B2B brands to Claude, while Pew keeps ChatGPT the B2C front-runner

Key sources are below. Find the complete list of links on the episode page:

https://victorious.com/podcast/which-ai-platform-to-optimize/

Chapter Headings

[00:01:11] This week in search: Search Console platform properties roll out worldwide

[00:03:52] Why a whole category of AI search got treated as one channel

[00:06:06] AI is not a monolith

[00:09:22] What every AI platform has in common: page rendering and third-party mentions

[00:11:52] Where the platforms diverge: training data, live search, and citation overlap

[00:13:36] Claude's brand-owned citations and Perplexity's moving target

[00:15:37] Why the same platform won't answer the same way twice

[00:17:07] Why your visibility tools can't tell you where your buyers are

[00:18:36] Three credible surveys, three different numbers

[00:19:58] Three ways to resource an AI search strategy

[00:23:34] Why Google surfaces come first, and the case for AI Mode

[00:28:08] Picking a second platform: B2B, B2C, and citation pools

[00:34:28] Four takeaways

Sources

Google Search Central Blog, "Platform properties roll out globally," July 29, 2026, https://developers.google.com/search/blog/2026/07/platform-properties-social-video-guide

Victorious, "Quarterly Search Report," 2026, https://victorious.com/quarterly-search-report/

Ramp, "AI Index," June 26, 2026, https://ramp.com/data/ai-index-june-2026

Pew Research Center, "How Americans' Opinions and Use of AI Differ by Age," June 17, 2026, https://www.pewresearch.org/internet/2026/06/17/how-opinions-and-use-of-ai-differ-by-age/

Google, "Q2 2026 Earnings Call: Remarks from Our CEO," July 22, 2026, https://blog.google/company-news/inside-google/message-ceo/alphabet-earnings-q2-2026/

Related Episodes

• AI Search Right Now

  https://victorious.com/podcast/ai-search-right-now/

• How Do AI Platforms Affect Your Brand Reputation? https://victorious.com/podcast/brand-reputation/
• The Q2 2026 Quarterly Search Report https://victorious.com/podcast/q2-2026-quarterly-search-report/

Every competitor can buy the same AI tools you can, at the same price, this afternoon. That makes AI table stakes, which means the thing actually worth funding is the judgment directing it. In this episode of The Search Signal, Michael Transon puts a number on that: about 1 percent of revenue, or $800 a month at $1 million in revenue and $80,000 at $100 million, plus the four arguments to make when your CFO asks why AI can't just do all of this now. What you'll hear in this episode:

• Marketing budgets have fallen to 7.8 percent of company revenue from 9.5 percent four years ago, while the AI share of those shrinking budgets climbed past 15 percent
• The production layer AI genuinely handles well: data pulls, first drafts, keyword research, and reporting, the work a junior analyst or a freelancer used to do
• Why clearing the baseline earns you nothing, using last quarter's research: AI described 96 percent of brands accurately and nine out of 10 still never got mentioned in a buyer answer
• Two cost assumptions that don't hold up: a Harvard Business Review field study that spent eight months inside a 200-person tech company and found AI intensified work instead of reducing it, and the fact that AI is only this cheap because providers are absorbing billions in losses to build adoption
• What each tier funds: $800 to $1,000 a month at $1 million in revenue, $8,000 at $10 million, $15,000 to $17,000 at $20 million, and $80,000 at $100 million and up
• The four arguments for a CFO, including organic search as a compounding asset rather than a cost, and why ground competitors are abandoning is the cheapest ground you'll ever take
  

[00:01:12] Alphabet's earnings put Cloud ahead of search

[00:03:27] Google's information agents push answers before you search

[00:04:31] AI Mode connects to Instacart, Canva, and YouTube Music

[00:06:02] Top Stories moves inside AI Overviews

[00:07:40] A judge throws out Google's copyright case against SerpApi

[00:08:52] The question: should you run search in-house with AI?

[00:10:31] Budgets are down, the AI line item is up

[00:13:19] Why search should keep its funding

[00:15:35] What AI genuinely does well

[00:17:06] Everyone buys the same tools, so no tool is the advantage

[00:20:11] Spreadsheets, Google Analytics, and the chisel

[00:23:20] Assumption 1: AI lets you do the same work with fewer people

[00:25:35] Assumption 2: AI stays this cheap

[00:27:55] AI isn't a fourth option, it's a layer underneath

[00:29:49] The rule of thumb: 1 percent of revenue

[00:31:07] At $1 million in revenue

[00:32:24] At $10 million in revenue

[00:33:39] At $20 million in revenue

[00:36:43] At $100 million and up, run both

[00:38:26] The case to make to your CFO

[00:42:36] Three takeaways

Find all sources referenced in this episode here: http://victorious.com/podcast/marketing-budget/

• CMO Spend 2026 – Gartner: https://www.gartner.com/en/articles/cmo-spend
• AI Doesn't Reduce Work, It Intensifies It – Harvard Business Review: https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it
• The State of Business Buying, 2026 – Forrester: https://www.forrester.com/blogs/state-of-business-buying-2026/
• Q2 2026 Quarterly Search Report – Victorious: https://victorious.com/quarterly-search-report/
• Top Stories roll out in Google AI Overviews – Search Engine Land: https://searchengineland.com/top-stories-roll-out-in-google-ai-overviews-482615
• Google AI Mode adds Instacart, Canva and YouTube Music integrations – Google: https://blog.google/products-and-platforms/products/search/connected-apps/

This week we discuss Victorious' new quarterly search report and unpack some of the findings. Learn what separates the handful of companies AI names from everyone else it merely recognizes, and why closing that gap happens on the parts of the web you don’t own.

What you’ll hear in this episode:

• Why AI recognizing your brand and AI naming your brand are two different things: 96% of brands were described accurately, but 89% don't show up in category answers
• The signals that do predict a mention: referring domains and third-party web mentions led, while SEMrush Authority Score, Knowledge Graph presence, and organic rankings barely moved the number
• The third-party mention threshold: brands with fewer than 2,000 pages mentioning them got named about 3% of the time, and brands above 30,000 got named 64% of the time
• Why AI almost never cites your own website, and why your site still matters anyway
• How a buyer’s question changes everything: early “do I need this” questions and late “what’s the best option” questions pull completely different sources, and brands get named more than 12 times as often in comparison answers

Sources from this episode linked below:

https://victorious.com/podcast/q2-2026-quarterly-search-report/

[00:01:04] Google becomes AI Mode's No. 2 cited domain
[00:02:03] Merchant Center's new AI performance insights
[00:03:03] Ask YouTube opens to US desktop
[00:04:18] The report: AI knows you, but 89% never get named
[00:09:22] What predicts a mention: referring domains, third-party mentions, and co-occurrence
[00:14:14] Why AI's citation sources differ by industry
[00:15:21] The third-party mention threshold
[00:16:41] Beyond the report: PR coverage, follow links, and anchor text
[00:24:05] Does AI ever cite your own website?
[00:26:52] How the buyer's question changes the answer
[00:30:43] What to do about it, and where to start this week

Profound, “Google is AI Mode’s No. 2 Most-Cited Domain: Report,” July 15, 2026, https://www.tryprofound.com/blog/google-com-is-now-ai-mode-s-2-cited-domain 

Google Merchant Center, “AI Performance Insights for AI Mode and AI Overviews,” July 14, 2026, https://support.google.com/merchants/answer/17200695 

YouTube, “Ask YouTube AI Search Experience Expands to US Desktop Users,” July 9, 2026, https://support.google.com/youtube/thread/448540943/try-a-new-conversational-search-experience-with-ask-youtube 

Victorious, “Q2 2026 Quarterly Search Report,” 2026, https://victorious.com/quarterly-search-report/ 

Episode 3: How To Tell If AI Search Is Working, https://victorious.com/podcast/how-to-tell-if-ai-search-is-working/ 

Episode 5: How Do AI Platforms Affect Your Brand Reputation?, https://victorious.com/podcast/brand-reputation/ 

Most marketers focus on two AI search numbers: mentions and citations. Neither one tells you if a platform describes your brand in a way that introduces reputational risk.

What you’ll hear in this episode:

• The commercial cost when AI gets your brand wrong.
• Two kinds of AI memory and how to address reputation issues accordingly.
• Why ChatGPT, Gemini, and Google AI Overviews can describe brands differently, with more consistency among some industries than others.
• How to diagnose where a bad answer comes from and what to do about it.

[00:00:48] Google's new Search Console Platform Properties report
[00:02:00] SEMrush: how B2B buyers rely on AI to pick vendors
[00:03:59] SEMrush: AI Overviews move into commercial searches
[00:05:48] Mentions and citations vs. brand reputation
[00:09:03] Why AI misrepresentation is a commercial risk
[00:14:37] The two kinds of AI memory: corpus and retrieval
[00:17:22] Why your reputation changes depending on the platform
[00:18:44] Where AI actually learns about your brand
[00:21:34] How to monitor your AI reputation
[00:23:54] Diagnosing the source: citation or corpus
[00:27:37] Seeding, co-occurrence, and third-party content
[00:31:48] The one takeaway and where to start this week

AirOps, “2026 State of AI Search,” December 2, 2025, https://www.airops.com/report/the-2026-state-of-ai-search 

Fractl, “AI Search Consumer Trust Study: Brand Visibility Strategies for 2026,” June 25, 2026, https://www.frac.tl/ai-statistics/ 

Profound, “The AI Mention Effect,” July 1, 2026, https://www.tryprofound.com/blog/the-ai-mention-effect 

Idea Grove, “Only 2% of Consumers Buy From an AI-Recommended Brand Without Checking It First,” April 15, 2026, https://www.ideagrove.com/blog/ai-recommendations-survey 

Lewis et al. (NeurIPS), “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,” 2020, https://arxiv.org/abs/2005.11401 

BrightEdge, “BrightEdge Data Reveals New AI Brand Risk for CMOs,” March 5, 2026, https://www.brightedge.com/news/press-releases/brightedge-data-google-ai-overviews-more-likely-to-criticize-brands-than-chatgpt 

Peec AI, “Top Domains Cited by AI Search,” March 31, 2026, https://peec.ai/blog/top-domains-cited-by-ai-search-analysis-based-on-30m-sources 

BrightEdge, “Why AI Engines Cite Different Sources but Recommend the Same Brands,” April 24, 2026, https://www.brightedge.com/resources/weekly-ai-search-insights/ai-search-same-brands-different-sources

More resources: https://victorious.com/podcast/brand-reputation/

Ask an LLM about a well-known company and it answers fast, and usually gets it right. Ask something obscure and it can be just as confident and completely wrong. This episode traces that behavior back 40 years, to two rival ideas about how to make a machine understand the world, and shows how their recent fusion is what actually answers questions about your company in AI Search today.

What you’ll hear in this episode:

• Why hallucinations run on the exact same machinery that produces correct answers
• The hand-built approach: Cyc, triples, the semantic web, and how Freebase became Google’s Knowledge Graph
• The pattern-learning approach, and how Word2Vec turned a word’s meaning into math you can do arithmetic on
• How the 2017 Transformer and “attention” let a model read a whole sentence in context, and how next-word prediction trained GPT-3
• Why RAG bolts the two systems together, and what it means that you can edit the “knower” but only earn the “talker”
  

Chapter Headings

[00:02:09] Why an LLM can be confidently wrong

[00:05:45] Teaching machines by hand: Cyc and the 1980s

[00:07:18] Triples, the semantic web, and Freebase

[00:08:51] Google's Knowledge Graph: things not strings

[00:14:08] The other approach: patterns, not facts

[00:16:00] Word2Vec turns meaning into math

[00:18:05] Attention and the Transformer

[00:23:07] BERT, GPT-3, and next-word prediction

[00:26:25] Why hallucinations happen

[00:28:44] Bolting the two brains together with RAG

[00:35:42] The takeaway: the knower you edit, the talker you earn

Resources

Cyc Project (1984) — https://www.cycorp.com/ | https://en.wikipedia.org/wiki/Cyc

Freebase (2007–2016) — https://en.wikipedia.org/wiki/Freebas...)

Wikidata — https://www.wikidata.org/ | https://www.wikidata.org/wiki/Wikidat...

Google Knowledge Graph (2012) — https://blog.google/products/search/i... | https://support.google.com/knowledgep...

Word2Vec (2013) — https://arxiv.org/abs/1301.3781

"Attention Is All You Need" (2017) — https://arxiv.org/abs/1706.03762

BERT (2018) — https://arxiv.org/abs/1810.04805

Retrieval Augmented Generation (2020) — https://arxiv.org/abs/2005.11401

GPT-3 (2020) — https://openai.com/api/

Find the transcript for this episode and additional resources on our blog: https://victorious.com/podcast/history-of-ai-search/

Every marketing team has a search dashboard. But that dashboard has a structural blind spot: it can’t see what’s happening in AI search, and it won’t flag that anything is missing. When a buyer finds your brand through ChatGPT, Gemini, Claude, or Perplexity, that visit typically lands as direct traffic with no source attribution. There’s no indication AI was involved and nothing in your reporting to suggest a gap is there.

What you’ll hear in this episode:

• Why most AI-driven sessions land in your direct traffic bucket, including why Google’s May 2026 GA4 patch only covers part of the problem
• How AI Overviews are compressing click-through rates by 58% on top-ranking queries, so session counts decline while rankings hold steady and your report gives no explanation
• Why a brand appearing consistently in AI responses can see almost nothing in its referral data
• The case for building measurement infrastructure now, when AI traffic is 0.2% of total visits but growing at 623% year over year, and you can’t retroactively create a baseline
• Four signals that together give you a credible picture of AI visibility: AI brand share of voice per platform, branded search volume trend, a GA4 AI referral segment, and self-reported attribution on every lead form

UK Competition and Markets Authority, “Further CMA action to secure a fairer deal for businesses and improve Google Search services in UK,” June 2026, https://www.gov.uk/government/news/further-cma-action-to-secure-a-fairer-deal-for-businesses-and-improve-google-search-services-in-uk

Similarweb, “The Downstream Impact of AI Visibility,” June 2026, https://www.similarweb.com/corp/the-downstream-impact-of-ai-visibility/

Ahrefs, “What Is a Good Organic CTR? Real Website Benchmarks (June 2026),” June 2026, https://ahrefs.com/blog/what-is-a-good-ctr/

Ahrefs, “Update: AI Overviews Reduce Clicks by 58%,” February 2026, https://ahrefs.com/blog/ai-overviews-reduce-clicks-update/

Semrush, “Why Category Entry Points Belong in Every AI Search Strategy,” June 2026, https://www.semrush.com/blog/category-entry-points-ai-search/

Loamly, “The AI Traffic Attribution Crisis: Why Your Analytics Are Wrong,” February 2026, https://www.loamly.ai/blog/ai-traffic-attribution-crisis

Contentsquare, “2026 Digital Experience Benchmark: AI-Referred Traffic,” April 2026, https://contentsquare.com/blog/ai-referred-traffic/

Find a complete list of resources at: https://victorious.com/podcast/how-to-tell-if-ai-search-is-working/ 

As AI platforms reshape the search landscape, many marketers are falling back on an old, unreliable playbook: chasing individual keyword ranks. In this second episode of The Search Signal, Michael Transon explains why a single snapshot of an AI search response is just noise—and why you need to update your tracking strategy. He breaks down how platforms like ChatGPT, Copilot, and Perplexity source their information differently, gives a hands-on blueprint for auditing your brand visibility, and shares the tactical levers required to earn a compounding share of voice.

What you'll hear:

• Why tracking AI like traditional keyword ranking fails, and why a sustainable approach means measuring a collective share of voice percentage instead.
• The distinct ways Perplexity, Copilot, and ChatGPT index and source their answers, and why performance on one engine doesn’t translate to another.
• How to conduct a rigorous manual audit in incognito mode to establish an accurate baseline and map out your competitors' visibility.
• The differences between citation rate and mention rate, and the unique, high-intent roles they play in the conversion process.
• The three pillars for moving the needle on your presence: digital PR outreach, structured entity signals, and answer-first commercial page optimizations.

All sources referenced in this episode are linked below.

Sources

• The Search Signal, Episode 1: https://victorious.com/podcast/ai-search-right-now/
  Ahrefs, "AI Overviews vs. AI Mode" https://ahrefs.com/blog/ai-overviews-study/
• SparkToro, "Search Happens Everywhere," https://sparktoro.com/blog/new-research-search-happens-everywhere-an-analysis-of-41-websites-with-significant-search-activity/
• Google, "Optimizing Your Website for Generative AI Features on Google Search," https://developers.google.com/search/docs/appearance/ai-overviews
• iPullRank, "Google Algorithm Leak Analysis," https://ipullrank.com/google-algo-leak
• The Growth Memo, "Users Behave Differently in AI Overviews," https://www.growth-memo.com/p/users-behave-differently-in-ai-overviews
• Adobe, "AI-Referred Traffic Conversion Analysis," https://business.adobe.com/blog/the-latest/adobe-digital-insights-ai-traffic-grows-significantly-during-2024-holiday-shopping-season
• SISTRIX, "Position One Click-Through Rate Data, March 2026," https://www.sistrix.com/blog/

Complete list of resources at: https://victorious.com/podcast/ai-search-right-now/

Most search marketers have gotten two completely different answers to this question, and both sound convincing. One camp says answer engine optimization (AEO) is its own discipline that needs its own budget. The other says it's just search engine optimization (SEO) with a new name and your existing program already covers it. In this debut episode of The Search Signal, Michael Transon cuts through the acronym soup to show what the data actually says, where this confusion is coming from, and what it means for how you should be allocating your search marketing budget right now.

What you'll hear in this episode:

• Why the overlap between organic search rankings and AI citations dropped from roughly 75% in late 2024 to somewhere between 20% and 38% by early 2026, and what's driving that shift
• What mention rate and citation rate measure, why they behave differently, and why you need to track both separately
• What actually predicts AI visibility and why domain authority has essentially zero correlation with it
• How AI visibility plays out differently across healthcare, SaaS, financial services, legal, and ecommerce, and what's behind each pattern
• The honest two-part answer to whether AEO and SEO are the same thing, and three specific things you can do in the next 90 days

Sources

• SparkToro "In 2026, Less than One Third of Google Searches Still Send a Click" June 8, 2026 https://sparktoro.com/blog/in-2026-less-than-one-third-of-google-searches-still-send-a-click/
• Burson "The Credibility Paradox" (report title) Via Search Engine Journal: "AI Mentions May Not Translate To Trust, New Analysis Suggests" June 8, 2026 https://www.searchenginejournal.com/ai-mentions-may-not-translate-to-trust-new-analysis-suggests/578388/
• BrightEdge "BrightEdge Data Finds AI Accounts for Less Than 1% Search, Organic Traffic Continues to Dominate" October 2025 https://www.brightedge.com/news/press-releases/brightedge-data-finds-ai-accounts-less-1-search-organic-traffic-continues
• Ahrefs "Update: 38% of AI Overview Citations Pull From The Top 10" January 2026 https://ahrefs.com/blog/ai-overview-citations-top-10/
• Ahrefs "How to Rank in AI Overviews: What Actually Works (Based on Data, Not Speculation)" 2026 https://ahrefs.com/blog/how-to-rank-in-ai-overviews/
• Victorious Q1 2026 Quarterly Search Report https://victorious.com/quarterly-search-report/ 

Find a complete list of resources at https://victorious.com/podcast/is-aeo-just-seo/

The Search Signal is a weekly podcast from Victorious founder and CEO Michael Transon, built for marketing leaders trying to make sense of how search is changing. Each week, Michael takes one thing happening in search, breaks down what it means, and helps you think through your next move. No hype, no filler. Just clear thinking for busy marketing leaders. New episodes every Tuesday. Subscribe wherever you listen.