Cooper Patton

RE: SPX at ATH while Consumer Sentiment at ATL (per great cht from @charliebilello, bottom): If you price SPX in gold (red, LS) & then chart it v. Consumer Sentiment (blue, RS), the reason for the divergence b/t Wall St & Main St becomes clear: It's a currency/inflation issue.

Gen AI traffic share update Main takeaways: → Claude and Gemini continue to grow. → ChatGPT moves closer to the 50% mark. 🗓️ 12 months ago: ChatGPT: 77.6% Gemini: 7.27% DeepSeek: 6.01% Grok: 3.17% Perplexity: 1.75% Copilot: 1.56% Claude: 1.37% 🗓️ 6 months ago: ChatGPT: 69.5% Gemini: 15.9% DeepSeek: 4.06% Grok: 3.31% Perplexity: 2.22% Claude: 2.12% Copilot: 1.97% 🗓️ 3 months ago: ChatGPT: 61.2% Gemini: 23.9% Grok: 3.94% DeepSeek: 3.09% Claude: 3.29% Copilot: 1.87% Perplexity: 1.74% 🗓️ 1 month ago: ChatGPT: 53.7% Gemini: 26.7% Claude: 7.95% DeepSeek: 3.97% Grok: 3.20% Copilot: 1.98% Perplexity: 1.50%

I spent the last 3 weeks running what might be the most comprehensive LLM ranking factors analysis to date. 29,562 unique domains tracked and scored across 145 industries, 1,595 buyer personas, and 105k+ ChatGPT prompts. Over 500TB of data, and 12 external signals correlated against rank-weighted LLM recommendation scores. This is a large-scale correlation study: what external signals actually predict whether a brand gets recommended by ChatGPT, across 145 industries and 1,595 buyer personas. -- Research Process 145 industries from 500 candidates. 11 personas each (10 targeted + 1 neutral). 25 runs per persona, rank-weighted scoring. 29,562 unique domains tracked. Data collected: - Common Crawl: 1.15B pages, domain mentions + phrase co-occurrences - Reddit: 5B+ posts and comments scanned - Google Search: 15,697 queries, top 100 results; 1.5M+ results captured - SERP HTML: parsed for outbound links and phrase presence - Wikimedia: 300M+ Wikidata entities + Wikipedia citations - Backlinks (Common Crawl Web Graph): PageRank + Harmonic Centrality; 4B+ - Top Site Homepages: parsed for persona-specific phrases -- Analysis Process 13 signals per domain. Spearman ρ vs. LLM recommendation score, per-industry and globally. R² shows variance explained. Lift measures over-representation in the top 10% most-recommended domains. Tiered: Dominant (ρ ≥ 0.30) down to Baseline (< 0.05). -- Key Findings SERP appearances, SERP rank, and outbound links from search results pages are the three strongest signals. Traditional SEO is the dominant measurable influence on LLM recommendations. Backlink authority (PageRank, Harmonic Centrality) follows. Combined, these point to one thing: established search authority drives LLM visibility. Signal hierarchies vary by industry. Wikidata dominates in established categories (hotels, ERP, furniture). Reddit drives community-driven ones (enterprise AI, live entertainment). No universal strategy. 80–85% of recommendation variance is inside the model. All external signals combined explain under 20%. You cannot infer LLM visibility from search rankings; you have to test it directly. -- The Two Conclusions That Matter 1. SEO is the foundation. OpenAI is using search data today and building their own index. As that matures, the connection between search authority and LLM visibility deepens. Traditional SEO principles are not obsolete, they're the starting point for LLM visibility too. 2. Persona is the measurement unit. The #1 airline for a frequent flyer is a different site from the #1 for a student flying abroad. Same model, same industry, different person, different result. You don't have one LLM rank, you have a rank per buyer segment. Monitor by persona or the number is meaningless. -- Full Report and data for all 145 industries and 1,595 personas available here: oppalerts.com/LLM-Ranking-Fa…

When looking at "citation portability" - only 2.37% of pages rank in ChatGPT, Gemini + Perplexity. Guides + blogs have the best portability rates of any content type:

Interested in Schema impact on AI citations? Here's the latest study from @ahrefs -> We Tracked 1,885 Pages Adding Schema. AI Citations Barely Moved "We tracked 1,885 web pages that added JSON-LD schema between August 2025 and March 2026, matched them against 4,000 control pages, and measured citation changes across Google AI Overviews, AI Mode, and ChatGPT. Adding schema produced no major uplift in citations on any platform." ahrefs.com/blog/schema-ai…

The single biggest winner from the budget: the tax-free owner-occupied home, which is where people will put their money. After the budget doubles the capital gains tax on productive businesses/assets from circa 23.5% to 46-47%, investors will understandably pull money from businesses, shares, commercial property and rental housing and plough it into their tax-free owner-occupied home. It's a great way to push up the prices of these houses. On the other hand, cutting negative gearing while also doubling CGT makes investing in rental properties extremely unattractive. It hammers the capital gain upside on any asset: shares, commercial property, the small or medium sized business you built, venture capital and private equity. It will give Australia the most unattractive capital gains tax in the WORLD (see table below)! So the government's policies will (1) push up owner-occupied house prices, (2) push up rents, and (3) reduce the capital available for investing in any small, medium or large sized business that is driving employment, innovation, growth and productivity/prosperity. Investors will go to other countries where they pay half the capital gains tax, or less. Since these pollies have never worked a day of their lives in the private sector, it is no surprise that when they decide to completely and unilaterally rewrite the entire tax system for all investors and businesses -- after promising before the last election more than 50 times NOT to change the capital gains tax and negative gearing rules -- that they would blow the entire Aussie economy up... Your best bet will be to buy a house, live in it, and hope they keep dropping 500,000 new people into the country every year to pump-up prices...

Young Australians should be enraged by the new super tax. The statist talking heads will tell you "it's only on balances above $3M. The rich." Most Aussies will fall for it. Run the numbers. 35yo today. $200k in super. Contributes $15k a year. Earns 8% returns (long run super average). In 30 years their balance is $3.7 million. Caught by the tax. But here's the trick. Australia's money supply has grown about 8% a year for the past two decades. RBA's own data. So that $3.7M buys what $369k buys today. Same groceries. Same house. Same petrol. You didn't get rich. You ran on the spot. And the $3M line? Frozen. In 30 years it only buys what $300k buys today. It's lost 90% of its real value. The govt doesn't have to move the line. Inflation does the work for them. No different from the obscene overreach on anti-money laundering rules. The $10k cash transaction threshold was set in 1988 and never moved. $10k then is $26k in today's money. Adjusted for money supply growth, it's $170k. Same threshold. Almost 3x more transactions caught by CPI, 17x by money supply. That's why you get interrogated at the bank for withdrawing what only covers half a year of school fees. Same trick with income tax. Wages rise with inflation. Brackets don't. Suddenly the average worker is in a "high earner" bracket they were never meant to be in. You don't earn more. The line moved. This one policy tells you everything you need to know about the government and its intentions. It's all about grift and theft. Meanwhile, the kids who get hit hardest are kept busy by an education system arguing about hate speech, social media, and the climate apocalypse promised in 2012. Nobody teaches them how money actually works. The govt likes it that way. So they vote for more taxes. Bigger govt. More "fairness." Pouring petrol on the fire burning their house down. The fix isn't communism. It's the opposite. Smaller govt. Lower taxes. Index every threshold to the actual money supply, not the CPI lie. Decentralise the banks. Despite everything, Australians are entrepreneurial and predominantly hardworking. Imagine what this country could become without the government's boot on its neck.

New: AI Citation Ranking Factors Everyone talks about AI Citations as a way to boost visibility + traffic, but what works? To find out, I gathered every study/experiment from the past 2 years, and scored the biggest wins 22 Ranking Factors associated with earning AI citations

We’ve agreed to a partnership with @SpaceX that will substantially increase our compute capacity. This, along with our other recent compute deals, means that we’ve been able to increase our usage limits for Claude Code and the Claude API.

Accurate

🔥 Great news for Websites: @Google is releasing new updates to AI Mode and AI Overviews to find relevant websites, deep insights and original content from across the web 👇 1. Explore new angles: You’ll start to see suggestions for where to go next at the end of many AI responses. This section links to unique articles or in-depth analyses on different facets of your topic. 2. See links right where you need them: To help you dig deeper into useful websites as you’re reading, you’ll now also see more links directly within AI responses — right next to the relevant text. 3. More UGC! Get advice from people who have been there: AI responses will now include a preview of perspectives from public online discussions, social media, and other firsthand sources. They're adding more context to these links, like a creator’s name, handle, or community name, etc. 4. Get more context on linked websites: They're now giving you a quick preview of a website when you hover over an inline link in AI experiences on desktop. You’ll see helpful information, like the name of the website or title of the web page, so users have a better idea of the site to help click through. 5. Easily access your news subscriptions: A new feature that highlights links from your news subscriptions in AI Mode and AI Overviews. Subscription linking information for publishers can be found here: developers.google.com/news/subscribe… --- These look like useful new releases that should improve referrals towards sites 🙌 Read more here: blog.google/products-and-p… - can't wait to see the impact 👀 /ht @rmstein

UCP has been spotted in the traditional Search results.

Prompts about Mother’s Day are ~3x more likely to trigger ads in ChatGPT due to strong purchase intent Who’s advertising: → Global Rose → 1-800-Flowers → Nordstrom → jcpenney → Etsy Who’s winning organic visibility (LLMs + AI search): → Etsy → Sephora → Nordstrom → Macy's → Target Based on a relatively small US sample, but the gap in ad frequency is large enough to be meaningful.

@screamingfrog what good is an X button if it doesn't terminate the process? looks pretty though. there goes my morning.

They should plaster this chart throughout hallways of American schools. Savers lose and investors win.

Google just published a study about indirect prompt injection. Important for SEOs and site owners to understand -> Google Says Prompt Injection Moving From Theory Into Real Abuse From @btabke: "This is the AI-era cousin of hidden text, doorway tactics, comment spam, parasite content, and schema abuse. The new wrinkle is that the instruction is not only aimed at a ranking system. It is aimed at the language model or agent that reads the page after retrieval." "Some SEOs will be tempted to test prompt instructions as an AI visibility tactic. That is a short road to a very ugly swamp. The behavior is easy to classify as manipulative because the intent is to override the AI system’s normal summarization or selection process." searchengineworld.com/google-says-pr…

Uh oh -> OpenAI missed an internal goal of reaching 1B weekly active ChatGPT users by 2025's end, and missed multiple monthly revenue targets earlier in 2026 "Chief Financial Officer Sarah Friar has told other company leaders that she is worried the company might not be able to pay for future computing contracts if revenue doesn’t grow fast enough, according to people familiar with the matter." "The “buy everything” computing strategy was buoyed by ChatGPT’s seemingly invincible success, and had the support of both Friar and the board. But the chatbot’s growth slowed toward the end of last year, sowing fresh doubt among company leaders about the approach." wsj.com/tech/ai/openai…

@_The_Prophet__ Hayes called this. Is it crypto? This is a US government play to get consumer demand for US treasuries. All social media apps will do this. Welcome to the future.

⚡️Musk is building the everything app and X Money is the financial layer. Most of the coverage understates what is happening because it focuses on consumer banking features without recognizing what those features represent structurally. What X Money actually is. The 3% cash back, 6% savings rate, free transfers, metal card pitch is the consumer-facing surface. The structural reality is that Musk is positioning X to capture a meaningful share of consumer banking and payments at a moment when traditional banks are vulnerable to disruption. The user base of approximately 600 million globally provides a built-in distribution channel that no fintech startup can match. The integration with the existing X platform creates network effects that traditional banks cannot replicate. The brand association with Musk specifically attracts a demographic that overlaps significantly with high-balance customers (tech workers, entrepreneurs, crypto holders, libertarian-adjacent professionals). The deeper structural play. Musk’s stated ambition is for X to become an everything app comparable to WeChat in China. The everything app combines social, payments, commerce, content, identity, and increasingly financial services into a single platform that captures most of a user’s digital activity. This is the most powerful business model that has emerged from the modern internet. WeChat captures the equivalent of social media plus PayPal plus Amazon plus several other categories simultaneously. The integration produces customer lock-in that no single-purpose product can match. The American digital landscape has not produced an equivalent because of regulatory fragmentation, antitrust concerns, and the fact that no single platform achieved dominant cross-category position. Apple has come closest with its ecosystem but has not pushed into financial services aggressively. Meta tried and failed multiple times. Google has tried with limited success. The opening that exists for an everything app in the United States has remained open precisely because no one has pulled all the pieces together. Musk is attempting to pull all the pieces together. X provides the social layer. xAI provides the intelligence layer. X Money provides the payments and banking layer. The car businesses (Tesla) provide a hardware integration point. SpaceX/Starlink provides connectivity. Neuralink eventually provides the human interface. The integrated picture is the most ambitious vertical stack that has been attempted in American technology. This is also why X Money matters more than the consumer banking pitch suggests. The financial layer is the connective tissue that transforms separate products into an integrated platform. Once payments flow through X, every other product on the platform gains friction reduction. Tipping content creators happens within the app. Buying products advertised on the platform happens within the app. Sending money to other users happens without leaving the platform. Each transaction adds data, adds switching costs, adds reasons for users to spend more time on the platform.

I've had the Audio Overviews experiment live since it launched and I can count on one hand the times I have played those. Hard to believe Google is testing expanding that feature... IMO, I don't believe the Audio Overviews feature will roll out. But hey, maybe people are actually listening to them in the SERPs... We'll see. :)

Agent-to-Agent Commerce. Interesting experiment from Anthropic -> Anthropic details Project Deal, a marketplace experiment where Claude models bought, sold, and negotiated personal belongings on behalf of Anthropic employees "The first thing to say is that our experiment worked. It is possible for AI agents to represent humans in a marketplace. In our “real” run, our 69 agents struck 186 deals across over 500 listed items, for a total transaction value of just over $4,000. And these were far from trivial, one-click deals. Agents had to identify potential matches, propose prices, field counteroffers, and reach agreement—all in natural language, without a prebaked negotiation protocol." "But not every agent did equally well. When we looked at the two runs with a mix of Opus and Haiku agents, we found that Opus outperformed Haiku on most objective measures." anthropic.com/features/proje…