Back to School: AI Visibility 101 for B2B Marketing Leaders

A practical 101 to help B2B teams get cited, trusted, and chosen in AI search.

AI search is reshaping how buyers research and decide. Impressions are up while clicks stagnate because AI Overviews now dominate the first scroll. 

In this 101 session, Liudmila Kiseleva, CEO of Rampiq and Founder of Vertology.ai, explains why that shift matters, how LLMs “see” your brand, and what you can do this quarter.

You’ll learn the difference between memory and live results, how to run an AI visibility audit, which technical foundations unlock citations, and the content formats LLMs cite. The goal: a clear plan for better citations, more qualified traffic, and pipeline growth in the AI era.

You Will Learn

  1. Why impressions rise while clicks stall, and how AI Overviews reduce CTR
  2. Memory vs. live results in LLMs, and why 40% of chats run without search
  3. A simple audit workflow to compare model memory with live sources
  4. Technical foundations for LLM crawlers, including robots.txt governance and content accessibility
  5. How granting LLM access to priority PDFs improves citation quality
  6. LLM-aligned content formats that outperform blogs, including documentation, lists, glossaries, and definitions
  7. How to measure first-party AI traffic and connect it to pipeline outcomes

Who It’s For

B2B marketing leaders, SEO leads, CMOs, founders, and growth teams who want control over how their brand appears in AI platforms and want that visibility to convert into traffic, leads, and revenue.

Bonus

Use promo code WEBINAR for a discounted live audit and comparison report on Vertology.ai. See where models source your information and fix misalignment between memory and live results.

Fill in the form to get instant access →

liudmila kiseleva
Host
Liudmila Kiseleva

I’ve helped 100s of tech companies get better marketing results and win more business from digital channels over my 17+ years of my career. I don’t just talk about AI Search – I’ve studied it, tested it, and cracked the code.

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