Ashu Dubey is the Co-founder and CEO of Alhena where he is building transformative customer experiences using Agentic AI. Before Alhena, he drove product growth at LinkedIn.
A fan-out query is one of the several background searches an AI engine runs before answering a single prompt. This guide explains how query fan-out works across ChatGPT, Perplexity, and Google AI Mode, why your AI visibility depends on ranking for those hidden searches, and how to close the gaps.
ChatGPT builds shopping answers from public retail pages, merchant feeds, and its own synthesis. This guide explains how the product card is assembled and gives a seven-step playbook to compete for it, from baselining product visibility to attributing revenue.
AI shopping assistants recommend specific products, not brands. SKU-level AI visibility tracks which of your products appear in ChatGPT's answers, whether the card renders with the right price, and which of your bestsellers are invisible to AI. A concept explainer plus a six-step how-to.
LLM-referred traffic to online stores grew 6.5x (a 550% increase) in 12 months on a stable cohort of 30 US brands, and converts at 2.68%, ahead of Google Ads and Meta Ads. New first-party research from Alhena across 310 brands and about 190M visitors, with full methodology and limitations.
An AI visibility platform monitors how ChatGPT, Google AI Overviews, Gemini, Perplexity, and Claude describe and recommend your brand, shows which sources shape those answers, and helps you change the outcome. Here is how they work, what they cost, and the four jobs to evaluate them on.
Not 'were we mentioned?' but 'what did AI search sell?' How to classify inbound traffic by AI engine, join it to purchase events, and report it against your sitewide baseline, plus a maturity ladder from blind to incremental and real conversion benchmarks from 310 online stores.