Does retrieval-based search make traditional keyword research obsolete?
Duane Forrester
UnboundAnswers.com
- Part 1Machine trust and retrieval-based search transformation
- Part 2 Does retrieval-based search make traditional keyword research obsolete?
- Part 3How will machine trust signals evolve for content creators next year?
- Part 4Technical SEO infrastructure vs human-crafted content quality with limited resources
- Part 5LLM.txt files — trend or trash?
- Part 6Key skill sets and roles to build your SEO team from the ground up
Show Notes
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00:30: Traditional Keyword Research Evolution
Discussion of whether retrieval-based search makes traditional keyword research obsolete, with emphasis on expanding beyond individual keywords to broader topic research and query fan-out strategies.
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01:48: Query Fan-Out Strategy
Exploration of how modern search requires understanding topic clusters and related concepts rather than focusing solely on individual keywords, using camping equipment as an example of interco ected search topics.
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02:13: Conversational Search Patterns
Analysis of how real-world conversations mirror "people also asked" patterns rather than keyword-based interactions, demonstrating the natural evolution from specific topics to broader related discussions.
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02:44: Industry Transformation Timeline
Prediction that the shift from traditional keyword research to fan-out inclusive approaches will happen rapidly, with the evolution being accelerated by the pace of search technology advancement.
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- Part 1Machine trust and retrieval-based search transformation
- Part 2 Does retrieval-based search make traditional keyword research obsolete?
- Part 3How will machine trust signals evolve for content creators next year?
- Part 4Technical SEO infrastructure vs human-crafted content quality with limited resources
- Part 5LLM.txt files — trend or trash?
- Part 6Key skill sets and roles to build your SEO team from the ground up
Up Next:
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Part 1Machine trust and retrieval-based search transformation
Google's AI overviews now appear in over 50% of search results. Duane Forrester, founder and CEO of UnboundAnswers.com and former Microsoft search engine insider, shares how his unique perspective from inside search engines informs adaptation strategies for the current AI transformation. The discussion covers machine trust fundamentals through structured data implementation, content chunking strategies for LLM consumption, and the critical shift from traditional keyword targeting to goal-oriented content creation that serves both human readers and AI systems.
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Part 2Does retrieval-based search make traditional keyword research obsolete?
Retrieval-based search is transforming how SEO professionals approach keyword strategy. Duane Forrester, former Bing Senior Product Manager and founder of UnboundAnswers.com, argues that traditional keyword research must evolve beyond single-term optimization to remain effective in AI-driven search environments. The discussion covers query fan-out methodology for topic expansion, conversation-based keyword research techniques that mirror natural language patterns, and strategic frameworks for adapting keyword research processes to accommodate LLM search behaviors and retrieval-based ranking systems.
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Part 3How will machine trust signals evolve for content creators next year?
LLM.txt files offer no actual SEO value for content creators. Duane Forrester, former Bing executive and founder of UnboundAnswers.com, explains why these files are "total trash" since all AI crawlers already follow standard robots.txt protocols. He details how Creative Commons bot handles most AI training data collection, making additional file formats unnecessary, and provides guidance on proper robots.txt syntax to avoid blocking beneficial AI crawlers from accessing content.
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Part 4Technical SEO infrastructure vs human-crafted content quality with limited resources
Enterprise SEO teams waste resources on ineffective LLM.txt files instead of proven protocols. Duane Forrester, former Bing search engineer and founder of UnboundAnswers.com, explains why major crawlers including AI systems still follow established robots.txt standards. The discussion covers proper robots.txt syntax implementation, the default crawl behavior that eliminates need for "do crawl" directives, and strategic resource allocation between technical infrastructure and content quality initiatives.
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Part 5LLM.txt files — trend or trash?
Google's AI overviews now appear in over 50% of search results. Duane Forrester, founder and CEO of UnboundAnswers.com and former Microsoft search engine insider, brings two decades of industry perspective to navigating this transformation. The discussion covers essential skill development for AI-era SEO including structured data mastery for LLM consumption, chunking content strategies that balance machine readability with human engagement, and critical evaluation frameworks for emerging AI SEO tools that prioritize trustworthiness over feature quantity.
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Part 6Key skill sets and roles to build your SEO team from the ground up
Enterprise SEO teams struggle with proper crawler management protocols. Duane Forrester, former Bing executive and founder of UnboundAnswers.com, clarifies critical misconceptions about bot control mechanisms that impact AI training data access. The discussion covers why LLM.txt files are ineffective compared to established robots.txt protocols, proper syntax implementation for crawler directives, and strategic considerations for allowing AI system access to enterprise content.
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