Summarized answers generated directly in Google search results by AI models.
A mode in Google Search where AI Overviews are shown instead of traditional results, powered by Google’s Gemini models.
Assigning credit to different touchpoints, including generative outputs, in a conversion journey.
A set of tools that allows developers to interact with software systems (like LLMs) programmatically, including sending prompts and receiving responses.
A Google model that helps understand query context in natural language.
Instances of a brand name being referenced without a link
Backlinks (Implied)
Mentions of an entity or site without an explicit hyperlink, interpreted by AI as credibility indicators.
Direct references to sources within AI-generated content.
A conversational AI developed by OpenAI, powered by large language models (LLMs) like GPT-4, capable of understanding and generating human-like text.
Content Atomization
Breaking large content pieces into smaller, reusable chunks optimized for AI comprehension.
Conversational AI
AI systems like chatbots that interact through natural language, often powered by LLMs.
Claude
A family of conversational AI models developed by Anthropic, known for their focus on safety, helpfulness, and constitutional AI principles.
Copilot
A set of AI tools developed by Microsoft (powered by OpenAI models), embedded into Office and developer products to assist with writing, coding, and productivity tasks.
Data Voids
Topics with limited high-quality information online, often leading AI to hallucinate or guess.
Dialogflow
Google’s natural language processing platform for building conversational interfaces.
Domain Authority (AI)
The perceived trustworthiness and relevance of a website as understood by AI models.
Deepseek
A Chinese-developed open-source language model aimed at research and enterprise usage, positioned as a competitor to GPT and Claude models.
Decoder
The component of a Transformer that generates output sequences, often used in language generation tasks (e.g., translation, chat).
Entity Recognition
AI’s ability to detect and classify names, brands, and key topics within content.
E-A-T (Expertise, Authoritativeness, Trustworthiness)
A Google principle also valued by AI in source selection.
Explainable AI (XAI)
The goal of making AI outputs understandable; clear, structured content helps with this.
Encoder
The part of a Transformer that reads and processes the input sequence to build contextual representations of the data.
Featured Snippets (AI-driven)
Direct answers surfaced by AI models, often sourced from structured or well-formatted content.
Factuality
The accuracy and verifiability of information, critical for generative models to avoid hallucinations.
Factual Knowledge Graph
A structured map of facts and relationships used by AI to understand entities.
Feedforward
A fully connected sub-layer within each Transformer block that processes the outputs from the attention mechanism.
Generative AI (GenAI)
AI that produces text, images, or code based on patterns learned from data.
Generative Engine Optimization (GEO)
Optimizing digital assets to increase visibility in AI-generated outputs.
Gemini
Google’s family of multimodal generative AI models, integrated into products like Search (via AI Overviews), Workspace, and Bard (now Gemini app).
Grok
An AI chatbot developed by xAI (Elon Musk), integrated into X (formerly Twitter), with real-time access to platform data.
Hallucinations (AI)
Instances where AI confidently presents false or made-up information.
Human-in-the-Loop
Incorporating human oversight into AI content workflows for quality and compliance.
Hyper-relevance
Matching user query intent with extreme precision to increase inclusion in AI outputs.
Intent Understanding (AI)
The AI’s ability to infer the goal behind a query, even if it’s ambiguous.
Information Architecture (for AI)
Structuring content for clarity and extractability by AI, not just for humans.
Iterative Refinement
Repeatedly improving content based on how it performs in AI responses.
JSON-LD
A structured data format that helps AI and search engines understand the context of content.
Just-in-Time Information
Delivering concise, relevant content at the exact moment it’s needed in an AI interaction.
Journalistic Integrity
Content accuracy and transparency; influences how AI assesses trustworthiness.
Knowledge Graph Optimization
Enhancing how entities are represented and linked in structured data for AI.
Knowledge Panels (AI-driven)
Information boxes populated by AI using structured and unstructured sources.
Keyword Prominence (Semantic)
AI emphasizes semantic placement and meaning of keywords, not just frequency.
AI models trained on massive text corpora to understand and generate language.
Latent Semantic Indexing (LSI)
Technique used to uncover hidden relationships between words and concepts in content.
Long-form Content (Strategic)
In-depth articles designed to provide rich context for AI to draw from.
Layer Normalization
A normalization technique applied to neural network layers to stabilize training and reduce internal covariate shift.
Multimodal AI
AI that integrates and processes text, images, and audio together in generating responses.
Meta-descriptions (for AI)
Short summaries that can help AI quickly understand page context and utility.
Machine Learning (ML)
The broader field that powers AI model training, including content generation and retrieval.
Manus
A startup building an enterprise-grade answer engine based on generative AI, focused on trustworthy knowledge retrieval.
Natural Language Generation (NLG)
AI’s ability to turn data into coherent human-like language.
Natural Language Processing (NLP)
The field of AI focused on understanding and interpreting human language.
Named Entity Recognition (NER)
NLP task where AI identifies and categorizes names, brands, and locations.
Ontology (AI)
A structured way of representing knowledge and relationships for better AI comprehension.
Open-domain QA
AI systems that can answer questions on any topic, not limited to a specific subject area.
Organizational Schema Markup
Structured data for businesses, helping AI recognize and attribute content correctly.
Prompt Engineering
The craft of designing prompts to guide AI models to generate desired outputs.
Programmatic SEO (for AI)
Generating scalable, structured pages targeting specific queries readable by AI.
Personalization (AI-driven)
Tailoring generative answers based on user behavior and context.
Perplexity
A generative AI search engine that cites sources in real time and offers a transparent alternative to traditional search.
Positional Encoding
A way to inject information about word order into the Transformer model, which otherwise has no inherent sense of sequence.
Prompt
The input given to an AI model (e.g., a question or command) to elicit a response.
When a single query leads AI to consult multiple diverse sources before answering.
Query Expansion (AI-driven)
How AI broadens user queries with related terms to improve response coverage.
Quality Rater Guidelines (Google)
Human-assigned quality scores used by Google, indirectly influencing AI outputs.
Retrieval-Augmented Generation (RAG)
A technique where AI pulls external knowledge in real-time before generating.
Relevance Scoring (AI)
AI’s method of determining how well a source matches a query’s context and intent.
Reputation Management (AI)
Controlling and improving online presence to shape how AI models describe a brand.
Residual Neural Network
A structure where the input of a layer is added to its output to improve learning stability and help train deep networks.
SEO (Search Engine Optimization)
The practice of optimizing web content to rank higher in traditional search engines like Google.
Semantic SEO
Optimizing content to reflect the true meaning behind queries, not just surface keywords.
Schema Markup
Structured vocabulary that signals context to search engines and AI models.
Synthetic Content
Content created by AI that still needs optimization to be reused by other models.
SGE (Search Generative Experience)
Google’s AI-powered search feature that shows generative responses.
Self-Attention
A mechanism that allows models to weigh and relate different parts of the input when processing language, enabling contextual understanding.
System Prompt
An invisible instruction that sets the tone, behavior, or rules for how an AI assistant should respond to user prompts.
Topic Clusters
Interlinked pages covering a central theme and subtopics, aiding AI understanding.
Trust Signals (for AI)
Elements that convey content credibility, such as author bios, citations, and accuracy.
Transparent Sourcing
Clearly showing where information comes from, helping AI attribute content correctly.
Transformer
A neural network architecture introduced in the paper “Attention Is All You Need”, revolutionizing NLP by using attention mechanisms instead of recurrence.
Token
A basic unit of text (such as a word, subword, or character) used by language models for processing and generation.
User Experience (AI-enhanced)
Ensuring AI-generated responses enhance user satisfaction and utility.
Unstructured Data Processing
How AI extracts meaning from free-form content like blog posts or transcripts.
Understanding of Nuance
AI’s capability to grasp subtle context, tone, or implied meaning in content.
Voice Search Optimization
Adapting content to match conversational, spoken queries processed by AI.
Verification (AI Output)
Ensuring that generative AI responses align with verifiable, factual source content.
Vertical Search (AI-integrated)
AI-powered niche search tools (e.g. for healthcare, legal) using GEO strategies.
Vector Embedding
A numerical representation of text (or other data) in high-dimensional space, used by AI models to understand semantic meaning and similarity.
Web Crawling (for AI)
How AI models gather and index data across the web to build their internal knowledge.
Weighted Keywords (AI-driven)
AI’s process of giving contextual weight to certain words in content.
Workflow Automation (GEO)
Automating GEO tasks like content tracking, prompt testing, or entity tagging.
XML Sitemaps (for AI Discovery)
Structured listings of website content that help AI find and index pages.
YAML (for Structured Feeds)
A data format occasionally used in structured content, aiding AI parsing.
Yield Generation (from Content)
Maximizing the utility of a content piece across AI platforms and formats.
Your Money or Your Life (YMYL)
Sensitive content types (health, finance) requiring high trustworthiness.
Zero-Click Content
Content that directly answers the user query in the AI layer, bypassing click-throughs.
Zoom-in / Zoom-out (AI Comprehension)
AI’s ability to analyze both granular details and broader context in content.
Z-score (AI Use)
A statistical concept that may be used to assess the uniqueness or outlier nature of content elements.
