AI Search Optimization
insights
Research, guides, and practical playbooks for understanding how brands appear in ChatGPT, Gemini, Claude, and other AI answer engines.
The conversation is the real AI search query: evidence from three studies
Three Aiso papers connect the hidden search work inside AI answers, the intent that develops after the opening prompt, and the conversation context that materially changes the final response. A new measurement framework for conversational demand.
The prompt is not the query: how request state evolves across AI conversations
Our second arXiv paper measures how a user's request spreads across the turns of an AI conversation. Across 8,133 conversations the final prompt carries a median 36% of the session's user vocabulary, and about half the time a stated need never reaches the final prompt. Why AI-search demand has to be measured at the session, not the query.
How much search is hidden in one AI answer? Introducing search density
Our first arXiv paper measures the query and source work compressed into one conversational answer. The median information-seeking answer packs 11 retrievable facts into 3 facets, and a 6-case web pilot shows one broad query covers 70% of it. What answer-reconstruction search density means for measuring AI demand.
Luxury's AI gap: 82% of top buyers use AI, and it rarely cites the brand
Bain's 2026 luxury study found 82% of top spenders used AI in their last purchase, but 90% of the sources AI cites for luxury queries are third-party. Aiso's analysis of the demand-supply gap, with new ratios and conclusions for luxury marketers.
How GEO became the default name for AI search optimization
We asked four AI systems to name the practice of optimizing for AI answers. Three led with GEO. None led with AEO, even when citing a vendor who prefers it. Here's how one term won—and what it teaches about influencing the machines.
How LinkedIn's Feed Algorithm Gets Posts to Millions of Views
LinkedIn's March 2026 feed-engineering post says the feed ranks millions of posts, refreshes embeddings within minutes, and processes 1,000+ prior interactions. Here is what that means for writing posts that recommendation systems and LLMs can understand.
ChatGPT-User Traffic Is Already Half of AI Bot Visits to Travel Sites: A Free Benchmark from Cloudflare
Cloudflare Radar's free AI Insights dashboard shows ChatGPT-User, the agent that fires when a real person asks ChatGPT about your brand, at 47.4% of user-triggered AI bot traffic on travel sites. Here is what the data shows and how to use it as a benchmark.
Everything you trust is a black box
The most common objection to AI is that nobody can fully explain how it works. True, but name one thing you use every day that you can. On Bergson's intuition vs analysis, tacit knowledge, and how people already let AI pick their next purchase, plus real anonymized ChatGPT conversations where shoppers ask the model to just decide.
How many prompts should you track in AI search?
A benchmark from across our AI-visibility projects: track 10 prompts for a first look, 100 for ongoing monitoring, and around 1,000 for a full content-and-tracking setup. Includes a typical working set broken down by funnel stage and intent, and how to pick your own number.
How often should you run your AI search prompts?
AI answers are noisy, so each run is a sample, not a fact. A benchmark on run frequency: a category leader needs as little as 1 run a day to be representative, an established mid-size brand around 10, and a long-tail challenger around 40, set by how variable its mention rate is. The sampling logic, with charts.
The Brave of AI search: why full opt-in conversation data wins
Brave built an independent search index on strictly opt-in, anonymized, k-anonymous browsing data. Aiso applies the same principle to AI search: every conversation in our 5M+ IP panel is voluntarily shared, anonymized, and reported only in aggregate. The analogy, the mechanics, and why consent-first data is also better data.
Why one ChatGPT query tells you almost nothing about your brand visibility
We ran 19 real consumer prompts through ChatGPT ten times each under identical conditions. Two runs share only 55% of recommended brands on average. 27% are 'ghosts' - mentioned in one run and never again. Only 16% are stable across all ten runs. Why single-screenshot AI visibility audits are statistically indefensible.
Is your portfolio company winning AI search? 4 metrics that matter (and 1 that lies)
A scorecard for investors evaluating portfolio companies' AI search performance - and for the marketing leaders who'll get the question. Commercial-intent mentions, the referral underestimation problem, visibility per dollar, and revenue per dollar, with public benchmarks plus original data from Aiso's panel of millions of real anonymized AI prompts and a live gpt-5.3-chat-latest replay.
Bing just redefined the index: grounding is now the unit of value, not pages
Microsoft Bing's May 2026 post draws a sharp line between traditional search and grounding for AI answers. The five dimensions Bing now uses to measure index quality - and what brands should change.
LLM Ranking Factors: What Actually Determines Whether AI Recommends Your Brand
We analyzed millions of AI answers to uncover the top factors influencing brand recommendations across ChatGPT, Gemini, and Claude.
How Much ChatGPT Traffic Should Brands Expect?
Benchmarks from 500+ brands across industries on AI referral traffic, conversions, and growth potential.
Most Popular ChatGPT Models: Real Data Analysis
Discover which ChatGPT models users actually prefer based on real query data - and what that means for your optimization roadmap.
What Are the Real Sources Used by ChatGPT? A Detective Investigation
We isolated unique phrases and traced them back to Reddit, directories, and training data to reveal AI's real source mix.
Our ChatGPT Sample Demographics: Overview & Limitations
An honest look at the consent-based panel powering Aiso - who's in it, what biases to know, and how we mitigate them.
Testing ChatGPT's Non-Ranking Nature: Espresso Machines
We ran 400 queries to test whether ChatGPT maintains consistent rankings - and found something more nuanced.
ChatGPT Search Market Share
Google's global search market share fell below 90% for the first time in a decade. Real-world clickstream data on how ChatGPT is reshaping where users go for answers, and what the shift means for brands.
Comparing Major LLMs in 2025
A side-by-side breakdown of how the top LLMs differ on retrieval, citations, and brand recommendation behavior.
What Are People Searching for on ChatGPT?
Real data on the most frequent prompts, products, and brands people query inside ChatGPT.
ChatGPT Scrapes Google and Leaks Prompts
An investigation into how ChatGPT scrapes Google Search and leaks user prompts into Google Search Console.
How AI Question Types Determine Citation Sources
Different prompt types pull from different sources. Here's the mapping for research, comparison, how-to, and purchase queries.
AI Chatbot Conversion Study
Conversion data from AI-referred traffic across e-commerce, SaaS, and travel sites.
How We Test and Run Experiments at Aiso
Our scientific commitments - falsificationism, hypothesis-driven design, replication - applied to AI search research.
Brands See AI Traffic Surge
The brands quietly winning AI referral traffic in 2026, and the tactics they share in common.
Advertising in ChatGPT: The Next Frontier of Marketing
How OpenAI's monetization roadmap will reshape paid acquisition - and how to prepare your team and content.