Autorentext

Rodrigo (Rod) Stockebrand is an expert in Answer & Search Engine Optimization (AEO/SEO) with 18+ years experience as a practitioner, trainer, speaker and consultant in the industry. His work can be seen across nearly half of the Fortune 500, including leading AEO/SEO teams and projects at Amazon, Pfizer, Entain, Starbucks, Apple, Microsoft, Nike, NASA, KPMG, Deloitte, Univision, Bain & Co., Intel, American Express, LVMH, Hugo Boss, Travelocity, Pottery Barn, Carnival Cruises, Bass Pro Shops, Peloton, T-Mobile, McAfee, Overstock.com, and hundreds of others. Rod has been featured in Moz, Search Engine Land, MediaPost, Forbes, Rolling Stone Magazine, and Adage, as well as serving as a guest lecturer at Harvard Business School. Rod also teaches one of the most popular AEO/SEO courses at the University of Miami since 2009, which has now expanded to over 12 other universities across North America and Europe.

Klappentext

Answer engines like ChatGPT are changing how people search for information. Instead of returning lists of web pages, these systems provide direct answers, sourced from content they can confidently access and interpret. As a result, clicks from traditional SEO efforts continue to decline, making it clear a new approach is needed.

This book introduces the emerging discipline of answer engine optimization, a practical framework for making content more discoverable and citable by generative AI systems. Drawing on decades of experience, author Rodrigo Stockebrand explains how large language models retrieve, evaluate, and decide which sources to include--and not include--in the final answer. You'll explore how to design, structure, and maintain content so answer engines can reliably interpret and reference it, and how to position your organization as a trusted source for AI systems.

• Understand how answer engines evaluate and select information
• Structure content to improve comprehension by large language models
• Use semantic HTML and structured data to improve content recognition
• Build topical authority that supports credibility and citation across platforms
• Measure performance across AI systems using emerging tools and metrics