SEO experts really need to stop making up new acronyms

Rand Fishkin advocates against new SEO acronyms like AIO and GEO, supporting "Search Everywhere Optimization" instead.

Luis Rijo

May 30, 2025 • 6 min read

SEO acronym confusion ends: Keep familiar SEO, expand E from Engine to Everywhere - problem solved!

SparkToro co-founder Rand Fishkin published a direct criticism of the search marketing industry's proliferation of new acronyms on May 29, 2025. The marketing expert argued against replacing SEO with alternatives like AIO (AI Optimization), GEO (Generative Engine Optimization), and LLMEO (Large Language Model Engine Optimization), advocating instead for Ashley Liddell's "Search Everywhere Optimization" terminology.

According to Fishkin, professionals have been attempting to rebrand SEO with multiple new acronyms despite having an existing solution that maintains the familiar three-letter format.

The search marketing field has seen multiple alternative acronyms emerge across professional networks. AIO refers to AI Optimization, focusing on optimizing content for artificial intelligence systems and machine learning algorithms. AEO stands for Answer Engine Optimization, which targets AI-powered systems that provide direct answers rather than traditional search result listings.

GEO represents Generative Engine Optimization, designed specifically for generative AI platforms that create responses rather than curating existing content. LLMEO denotes Large Language Model Engine Optimization, targeting optimization strategies for systems like ChatGPT, Claude, and similar AI platforms.

Additional variants include EIO (Everything In Optimization) and other permutations that attempt to capture the expanding scope of search optimization beyond traditional engines. According to Fishkin's observations, he encountered approximately 15 different acronyms on LinkedIn during a single day of professional discussions.

According to Fishkin's analysis, traditional Search Engine Optimization focuses on achieving higher rankings on Google, Yahoo, Bing, and other search platforms. The proposed Search Everywhere Optimization expands this definition to encompass "influence audiences in all the places they go to consume content about your topic."

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The technical distinction represents a fundamental shift in optimization strategy. Traditional SEO metrics center on search engine rankings and organic traffic from specific platforms. Search Everywhere Optimization requires tracking engagement across multiple content discovery channels, including social media platforms, recommendation algorithms, and AI-powered search interfaces.

Fishkin's framework emphasizes that existing SEO professionals already possess the necessary technical skills for this expanded approach. According to his assessment, SEO practitioners routinely manage "ever-changing algorithms and evolving user behaviors" while learning "entirely new systems every time Google rolls out a new tab."

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Industry adoption patterns and resistance

The terminology debate reflects broader changes in content discovery mechanisms. According to Fishkin's observations, marketing teams already receive requests for visibility across platforms including YouTube, Reddit, Pinterest, and large language models. These demands suggest the industry has already moved toward multi-platform optimization without formal acknowledgment.

Ashley Liddell from Deviation originally coined "Search Everywhere Optimization" several years ago, according to Fishkin's attribution. The concept gained additional support from NP Digital's head of SEO, Nikki Lam, who adopted the terminology for client work. Despite this established usage, multiple alternative acronyms continue appearing across professional networks.

The resistance to new acronyms extends beyond semantic preferences. Fishkin acknowledged his own historical branding challenges, citing SOCEngine and SEOmoz as examples of difficult-to-pronounce brand names. His critique of current alternatives includes AIO, AEO, GEO, and LLMEO, which he encountered across LinkedIn discussions.

Search Everywhere Optimization demands expanded measurement frameworks compared to traditional SEO approaches. Practitioners must track content performance across disparate platforms with varying analytics capabilities and attribution models. Each platform employs different ranking algorithms, requiring specialized optimization techniques.

The technical complexity increases when managing cross-platform content strategies. According to Fishkin's framework, optimization extends beyond keyword research to encompass platform-specific content formats, engagement patterns, and algorithmic preferences. This includes understanding video optimization for YouTube, community engagement for Reddit, and visual content optimization for Pinterest.

AI-powered platforms introduce additional technical considerations. Large language models require different optimization approaches compared to traditional search engines, focusing on content authority, factual accuracy, and comprehensive topic coverage rather than keyword density and traditional ranking factors.

The terminology shift carries practical implications for marketing teams and agencies. Standardized language facilitates communication between departments, external vendors, and executive leadership. According to Fishkin's perspective, maintaining the established SEO acronym while expanding its definition reduces confusion and training requirements.

Professional certifications and educational programs face similar considerations. Industry courses, conference presentations, and certification programs built around SEO terminology would require minimal adjustments under the Search Everywhere Optimization framework. Alternative acronyms would necessitate complete curriculum revisions and new learning materials.

The competitive landscape influences terminology adoption. Marketing agencies differentiating their services through proprietary methodologies may prefer unique acronyms to distinguish their approaches. However, this fragmentation potentially confuses potential clients who must navigate multiple definitions for similar services.

Data-driven performance metrics

Search Everywhere Optimization requires comprehensive measurement across multiple touchpoints. Traditional SEO metrics include organic traffic, keyword rankings, and click-through rates from search engine results pages. The expanded framework incorporates social media engagement, video view duration, community participation metrics, and AI system citations.

Attribution modeling becomes more complex when tracking cross-platform performance. Users may discover content through AI recommendations, engage via social media, and convert through organic search results. This multi-touchpoint journey requires sophisticated tracking mechanisms and unified reporting systems.

The technical infrastructure for Search Everywhere Optimization includes API integrations across platforms, centralized analytics dashboards, and automated reporting systems. Teams must establish measurement standards for platforms with different data collection capabilities and privacy restrictions.

Platform algorithm considerations

Each content discovery platform employs distinct algorithmic approaches requiring specialized optimization strategies. Google's search algorithm emphasizes page authority, content relevance, and user experience signals. YouTube prioritizes watch time, engagement rates, and video completion percentages. Reddit values community interaction, upvote ratios, and discussion quality.

AI-powered platforms introduce additional algorithmic variables. Large language models consider content accuracy, source credibility, and comprehensive topic coverage when generating responses. These systems may reference multiple sources simultaneously, requiring optimization for citation-worthy content rather than singular page rankings.

The algorithmic landscape continues evolving rapidly. According to Fishkin's assessment, SEO professionals already adapt to frequent platform changes and new feature rollouts. This adaptability becomes essential for Search Everywhere Optimization success across multiple evolving platforms.

Industry standardization challenges

Professional organizations face decisions regarding terminology adoption and standardization. Industry conferences, trade publications, and certification bodies influence widespread terminology acceptance through their content and educational materials. The search marketing field lacks a central governing body to establish official terminology standards.

Global considerations complicate standardization efforts. Different regions may prefer different terminology based on local market conditions and existing industry practices. International teams require consistent language for effective collaboration and knowledge sharing.

The timing of terminology adoption affects market acceptance. Early adopters may gain competitive advantages through clear positioning, while late adopters risk confusion during transition periods. Industry leaders' public positions, such as Fishkin's advocacy, significantly influence broader adoption patterns.

Technical skill transferability

According to Fishkin's analysis, existing SEO professionals possess transferable skills applicable to Search Everywhere Optimization. These include experience with algorithm analysis, content optimization, and performance measurement across changing platform requirements.

The learning curve for expanded optimization appears manageable based on current industry practices. Marketing teams already track performance across multiple channels, manage content for different platforms, and adapt to algorithmic changes. Search Everywhere Optimization formalizes these existing practices under unified terminology.

Training requirements focus on platform-specific optimization techniques rather than fundamental strategy changes. Teams must understand each platform's unique requirements while maintaining consistent brand messaging and optimization objectives across channels.

Market reaction and adoption timeline

Industry response to Fishkin's position reflects broader debates about search marketing's future direction. Social media discussions following his May 29 announcement show mixed reactions, with some professionals supporting terminology standardization while others defend platform-specific optimization approaches.

The adoption timeline for Search Everywhere Optimization depends on several factors including industry leader endorsements, educational program integration, and client demand for expanded services. Historical precedent suggests terminology changes require 18-24 months for widespread adoption across marketing organizations.

Competitive pressures may accelerate adoption among agencies seeking to demonstrate comprehensive capabilities to prospective clients. Organizations already providing multi-platform optimization services may quickly adopt the terminology to better describe their existing offerings.

Why this matters

This development signals a critical juncture for the search marketing industry as it grapples with AI integration and platform diversification. The terminology debate reflects deeper questions about professional identity and service scope as traditional search boundaries dissolve.

Marketing teams must navigate increasing complexity in content discovery mechanisms while maintaining coherent strategies and measurement frameworks. The Search Everywhere Optimization concept provides a structured approach to this challenge without requiring complete methodology overhauls.

The industry's response to this terminology proposal will influence how marketing education, professional development, and client communications evolve over the coming years. Standardized language facilitates knowledge sharing, reduces training costs, and improves client understanding of service deliverables.