Afleveringen
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The podcast covers Olaf Kopp's two blog posts on the importance of branding and E-E-A-T former E-A-T for search engine rankings. The first post explains how digital branding can be built and measured through positive customer experiences at different touchpoints. The second article focuses on E-A-T (Expertise, Authoritativeness, Trustworthiness) and thematic brand positioning as critical success factors for SEO, examining on-page and off-page factors that influence E-A-T. Both texts emphasize the need for consistent brand presence and positioning in the digital space to build trust with users and search engines. Kopp argues that E-A-T has a significant impact on Google rankings and is closely linked to brand positioning.
https://www.kopp-online-marketing.com/e-a-t-topical-brand-positioning
https://www.kopp-online-marketing.com/digital-brand-building-the-interplay-of-online-branding-customer-experience
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This episode is about a Google Docs. A quick guide to the “Twiddler” framework within Superroot, a search result ranking system. It describes Twiddler as C++ objects that reorder search results based on different methods (e.g. Boost, BoostAboveResult, Filter). The guide explains the different Twiddler types (Predoc and Lazy), the available API methods and how to use them, as well as the concepts of categories and constraints to fine-tune the results. Special attention is paid to the isolation of twiddlers and the avoidance of pagination problems. The guide serves as an introduction and refers to further documentation.
https://www.kopp-online-marketing.com/patents-papers/twiddler-quick-start-guide
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Zijn er afleveringen die ontbreken?
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The podcast covers the components for effective SEO. In addition to technical expertise and ranking experience, he emphasizes the importance of empathy and communication skills. It criticizes the superficial knowledge transfer in the SEO industry and recommends basic knowledge of information retrieval.
https://www.kopp-online-marketing.com/how-to-become-a-really-good-seo
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The podcast looks at Google's E-E-A-T concept for improving the quality of search results. E-E-A-T evaluates the expertise, experience, authority and trustworthiness of authors by analyzing various on- and off-page signals. Google uses machine learning, in particular Natural Language Processing (NLP), to identify authors from unstructured content and assign content to them. The analysis of author embeddings compared to document embeddings enables the assignment of content to authors and the evaluation of their credibility. In addition, various Google patents are presented that detail methods for author identification and evaluation.
https://searchengineland.com/google-identify-evaluate-authors-e-e-a-t-395639
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In this episode a Google patent is focussed that details a method for improving search engine ranking results. It combines global ranking factors (offsite data such as backlinks) with local factors (onsite data such as internal linking and page positioning) to evaluate the relevance of websites more precisely. The process first calculates a global and then a local rank, which are then combined to produce a combined ranking. The weighting of the onsite factors depends on the authority of the website. The patent includes detailed descriptions of the methodology, algorithms and implications for search engine optimization (SEO).
https://www.kopp-online-marketing.com/patents-papers/onsite-and-offsite-search-ranking-results
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The podcast sheds light on the concepts of relevance, pertinence and quality in the context of search engines. Relevance describes the objective importance of a document for a search query, pertinence the subjective importance for the user, and quality the evaluation of websites and content. Kopp explains these three factors using Google's algorithms and emphasizes the challenges of taking individual user needs into account. The article discusses how Google integrates these factors into the ranking process and how they influence each other. Finally, the importance of factors such as E-E-A-T is emphasized.
https://www.kopp-online-marketing.com/relevance-pertinence-and-quality-in-search-engines
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The podcast deals with the role of different content types and formats along the customer journey. Various content types (e.g. videos, blog posts, infographics) and formats (text, audio, video) are described and their use in the various phases of the customer journey (pre-awareness to loyalty) is explained. The author emphasizes the importance of target group analysis and platform selection for the content strategy. Finally, influencing factors such as industry, target group and search intention on the content selection are discussed.
https://www.kopp-online-marketing.com/content-types-and-formats-customer-journey
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This episode discusses a patent that describes a system and method for categorizing resources using a deep neural network. Resource features are converted into numerical values by embedding functions, processed in neural network layers and finally evaluated by a classifier to predict category membership. The method is used in search engines, for example to detect spam and optimize search results. The patent covers various implementations of the system and method, including software and hardware aspects. The accuracy and efficiency of the categorization are emphasized.
https://www.kopp-online-marketing.com/patents-papers/classifying-resources-using-a-deep-network -
The podcast explains how Google understands and processes search terms using entities and machine learning (RankBrain, BERT, MUM). It describes the steps of search term processing, from thematic classification to query refinement. It analyzes various Google patents that shed light on the underlying technologies, in particular the identification of entities and their relationships in the knowledge graph. The focus is on the semantic interpretation of search queries in order to precisely capture the user's search intention and return relevant results. Finally, the interaction of RankBrain, BERT, MUM and the Knowledge Graph in the context of modern search engine optimization is explained.
https://www.kopp-online-marketing.com/search-query-processing
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The podcast examines the Google Knowledge Vault, a former Google project for the automated creation of a comprehensive knowledge database. Although the Vault has not been mentioned since 2015, the article describes its original functionality based on published research. It highlights the challenges of algorithmic data mining and how it differs from the Google Knowledge Graph. The author clears up misconceptions about the Knowledge Vault and presents it as a possible predecessor system to the Knowledge Graph, which today functions more as an entity extraction and validation process.
https://www.kopp-online-marketing.com/what-is-the-google-knowledge-vault
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The podcast is focussing on the Google patent titled "Systems and methods for improving the ranking of news articles". The patent describes a system for improving search results for news articles by evaluating the quality of sources. Several metrics, such as number of articles, length, timeliness and writing style, are used to assign a quality score to sources. This score influences the placement of articles in search results, favoring higher quality news sources. The system aims to provide users with more reliable information and increase the objectivity of search results. The algorithm also takes into account factors such as originality of reporting and diversity of sources.
https://www.kopp-online-marketing.com/patents-papers/systems-and-methods-for-improving-the-ranking-of-news-articles
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The podcast covers how the Google Knowledge Graph works, in particular the concepts of entities, entity types, classes and attributes. It explains how Google collects and processes information from various sources (structured, semi-structured and unstructured data) to create and extend the Knowledge Graph. The relevance of attributes to the entities and the challenges of extracting information from unstructured data are also highlighted.
https://www.kopp-online-marketing.com/entity-types-classes-attributes
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The podcast examines how Google processes information from Wikipedia and Wikidata for its Knowledge Graph. Semi-structured data from Wikipedia, in particular info boxes and introductory texts, are extracted and used. Structured data from Wikidata and databases such as DBpedia and YAGO also play an important role. The article describes Google's methods for identifying entities, extracting attributes and aggregating information for featured snippets and knowledge panels. Wikipedia serves as an important data source and “proof of entity”. Finally, the challenges of processing unstructured data and ensuring data quality are addressed.
https://www.kopp-online-marketing.com/wikipedia-knowledge-graph
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In this episode a new Microsoft patent is in focus. The patent provides information on how Copilot selects sources in the RAG process.It is important for LLMO / GEO to know which criteria are used in order to get clues for optimization. It also shows how important classic SEO or optimization for search engine rankings is for the output of generative AI.The Microsoft patent titled "Informational grounding with respect to a generative model" describes a computing system that integrates a search engine with a generative AI model to provide more accurate and contextual responses to user queries.
https://www.kopp-online-marketing.com/patents-papers/informational-grounding-with-respect-to-a-generative-model
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The podcast examines how Google extracts information from unstructured data sources and integrates it into its Knowledge Graph. He highlights the challenges of ensuring completeness, validity and timeliness of the data, especially when dealing with tail entities. Various methods such as named entity recognition, event extraction and the use of machine learning are explained. Finally, the Knowledge Vault is presented as an advanced approach to knowledge fusion that combines both structured and unstructured data sources. The author emphasizes the importance of Natural Language Processing (NLP), but believes that Google is still at the beginning of fully utilizing unstructured information in the Knowledge Graph.
https://www.kopp-online-marketing.com/entities-from-unstructured-content
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The podcast discusses the importance of E-E-A-T (expertise, experience, authority, trust) for Google rankings. E-E-A-T goes beyond simple SEO and requires a holistic approach that includes content marketing, PR and branding. The author argues that Google ranks websites based on entities and their authority, with on-page and off-page signals playing a role. Successful ranking therefore requires collaboration between different departments within the company. Finally, the changed role of the SEO expert as an advisory and coordinating contact is described.
https://www.oncrawl.com/technical-seo/times-eeat-why-simple-seo-no-longer-enough/
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In this podcast episode are discussed three patents by Google researcher Dan Popovici about the Click and Skip Re-ranking concept.
Google's three patents describe methods for improving the relevance of search results by analyzing user interactions (clicks and skips). One patent evaluates the proximity of search terms in the results, another the optionality of search terms and the last the reordering of search terms. All three patents use click and skip data to adjust rules to optimize search results. The algorithms are controlled by weighted ratio formulas and thresholds.
https://www.kopp-online-marketing.com/patents-papers/click-or-skip-evaluation-of-reordering-rules
https://www.kopp-online-marketing.com/patents-papers/click-or-skip-evaluation-of-query-term-optionalization-rule
https://www.kopp-online-marketing.com/patents-papers/click-or-skip-evaluation-of-reordering-rules
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The podcast deals with Google's development towards a semantic search engine, the individual steps and innovations of Google since 2010, in particular the role of the Knowledge Graph, machine learning and natural language processing. It also focuses on a deeper understanding of semantic search, the importance of entities and their impact on ranking, and how the Knowledge Graph works.
https://www.kopp-online-marketing.com/googles-semantic-search-engine
https://searchengineland.com/semantic-search-entity-based-search-388221
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The podcast explores the concept of “Digital Authority Management”, a new marketing discipline that highlights the growing importance of E-E-A-T (Experience, Expertise, Authoritativeness, Trust) in the context of search engine optimization and generative AI. E-E-A-T is described as an important quality classifier that influences visibility in search results and guides the selection of trustworthy sources for the training of Large Language Models (LLMs). The author argues for the need for closer collaboration between SEO, brand management and PR to generate algorithmically measurable signals of authority and brand positioning. The role of the Digital Authority Manager is to form this interface and optimize digital branding with regard to E-E-A-T.
https://searchengineland.com/authority-management-new-discipline-428948
https://www.kopp-online-marketing.com/digital-authority-management
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The Google patent US10055467B1 discussed in the podcast describes a system for improving the relevance of search results. It uses group-based modification factors, calculated from metrics such as repeat clicks and direct visits, to adjust the initial scores of search results. Thresholds control the strength of the adjustment, treating navigation and non-navigation queries differently. The goal is higher relevance and improved user experience.
https://www.kopp-online-marketing.com/patents-papers/ranking-search-results
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