Insights, analysis, and product updates on AI visibility, search behavior, and brand discovery.
ChatGPT Ads go live in 31 European markets on 24 August with contextual targeting only. Here's why that makes your content decide whether your ad runs.
An AI summary told customers a solar company was being sued. It wasn't. There's no correction form for that, so here's what to do instead.
Between 13 June and 3 August 2026, four Chinese AI labs each released a flagship model: GLM-5.2 from Zhipu, Kimi K3 from Moonshot, a rebuilt DeepSeek V4-Flash, and Alibaba's Qwen3.8-Max. All four are described as open, and the word means something different every time. This piece compares them on the differences a leaderboard cannot show, including a more than fiftyfold gap in running costs, licence terms that only bite above a certain company size, and a set of files Alibaba has promised but not published.
Most brands measuring AI visibility are measuring citations. Citations prove a model could read you. However, they do not prove it recommends you, and the gap between the two is where deals are lost.
AI assistants are changing how people find brands. Here's how SEO and GEO fit together and where your team's effort should actually go.
This week, a federal courtroom in San Francisco will help decide who gets to shop on your behalf, and which brands AI agents are allowed to see when they do.
Product Feed Audit helps brands analyze and optimize their product feeds for AI discovery and recommendation. Built to work with Shopify feeds and e-commerce RSS integrations, Product Feed Audit evaluates structured product data to assess how AI platforms interpret, surface, and compare products. It analyzes feed completeness, attribute clarity, schema structure, taxonomy mapping, and recommendation-readiness signals — identifying exactly where products risk becoming invisible inside AI answers. With Product Feed Audit, brands transform operational product feeds into AI-ready growth infrastructure.
AI assistants are reshaping how shoppers discover products. Here's how retailers can measure and improve their visibility in AI answers quickly, with a lightweight proof-of-value pilot.
Quadrant’s new Prompt Volume feature helps brands understand how often people actually ask AI about their category. It makes AI demand measurable, helps teams prioritize high-impact prompts, and guides content strategy toward the questions that truly matter.
How Retail Brands Win Visibility and Preference
Quadrant's new Personas feature lets you create targeted AI content for specific audience segments. Define personas by demographics, job roles, and industry, then track visibility scores and optimize content for each audience type.
AI assistants are the new gatekeepers of product discovery. This 90-day playbook shows brands how to move from guesswork to predictable visibility by treating AI citations as a measurable channel. Learn how to audit your presence, optimize content for LLM extraction, and use data-led sprints to secure your place in the answers that matter.
Quadrant's Query Fan-Out reveals the hidden searches AI engines perform behind the scenes. See exactly what queries ChatGPT, Claude, and other AI platforms generate from user prompts, and optimize your content for the searches that actually drive citations.
