Marketing Automation in 2026

Marketing Automation in 2026

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Marketing Automation in 2026 episodes

  • Building Author Hubs: ORCID, Crossref, and Scholar Profiles as Trust Primitives

    Read the full article: Building Author Hubs: ORCID, Crossref, and Scholar Profiles as Trust Primitives

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    Excerpt:

    Building Author Hubs: ORCID, Crossref, and Scholar Profiles as Trust Primitives

    Author hubs are public, connected records that help people and machines answer three basic questions:

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    29 min
  • The New Playbook for Earning AI Citations Across Google AI Overviews, Bing Copilot, and Perplexity

    Read the full article: The New Playbook for Earning AI Citations Across Google AI Overviews, Bing Copilot, and Perplexity

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    Excerpt:

    The New Playbook for Earning AI Citations Across Google AI Overviews, Bing Copilot, and Perplexity

    Introduction: In the new world of search, tools like Google’s AI Overviews, Microsoft’s Bing Copilot, and the Perplexity.ai search engine no longer just show links – they answer questions and then cite the sources they used. These AI-driven answers give users quick information with clickable source links. For websites and content creators, the goal is shifting: instead of only ranking high in the blue link list, you want to be the name or link in those AI answers. To do that, you need a fresh playbook of tactics. In this article, we’ll explain how each AI search tool picks and displays citations, what features on your pages make you more likely to be cited, and how to test and measure your success. We’ll also cover how to build ethically friendly content that AI tools can use. This is Answer Engine Optimization (AEO) for Google, Bing, and Perplexity.

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    20 min
  • Synthetic Query Testing: Probing Assistants to Reverse-Engineer Citation Rules

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    Excerpt:

    Introduction

    Modern AI assistants (chatbots like ChatGPT or Bing Chat) often try to answer user questions and “show their work” by citing sources. However, studies show many answers have bad or missing citations. For example, Stanford researchers found that about half of AI chat answers contained unsupported statements or wrong citations (www.axios.com). In medical tests, new AI tools often gave answers not supported by the sources they cited (doaj.org). These problems mean we need better ways to test AI assistants’ citation behavior.

    To understand how an AI picks what to cite, we propose a large-scale testing plan. We will create many synthetic queries (made-up questions) covering different subject areas and types of questions. We will run these through AI assistants automatically, gather their answers and citations, and label each cited source by its freshness (how recent), authority (how trusted), and structure (type or format). Then we use simple statistics to see which factors make it more likely an AI will cite a source. We will share all our data and tools openly. In this way, we can crowd-source improvements and keep monitoring AI citation behavior over time.

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    9 min
  • Machine-Readable Publishing: Sitemaps, Web Feeds, and Dataset Pages for LLMs

    Read the full article: Machine-Readable Publishing: Sitemaps, Web Feeds, and Dataset Pages for LLMs

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    Excerpt:

    Machine-Readable Publishing: Sitemaps, Web Feeds, and Dataset Pages for LLMs

    Websites reach people and computers (like search engines and chat assistants) by being easy to find and understand. One way to help this is by using structured publishing artifacts – special files and pages that a machine can read. For example, an XML sitemap lists every page on your site so search bots can discover them all (developers.google.com). A web feed (RSS or Atom) lists recent updates so tools see new content quickly (developers.google.com). And dedicated dataset or methodology pages explain any data or methods you used, often with structured data (like schema.org markup) so systems like Google’s Dataset Search can find them (developers.google.com). In this article, we explain how to use these artifacts to improve discoverability. We will look at checking your sitemap coverage and lastmod dates, ensuring feed freshness, creating clear data/method pages, testing changes with tools, and monitoring improvements like crawl frequency and assistant citations. Finally, we offer a maintenance plan and rollout steps.

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    18 min
  • From Snippets to Sessions: Driving Conversions When Answers Are In-Result

    Read the full article: From Snippets to Sessions: Driving Conversions When Answers Are In-Result

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    Excerpt:

    From Snippets to Sessions: Driving Conversions When Answers Are In-Result

    As search engines and AI assistants increasingly show quick answers in-line (like featured snippets or chat responses), many users get their question answered without clicking through. While this zero-click search can seem to undermine traffic, we can still capture demand on those pages. By adding strong, relevant calls-to-action (CTAs), useful tools or assets, and email signups that match the user’s query, sites can turn on-page answers into visits and leads. In this post, we cover tactics to do just that and suggest how to measure success with metrics like micro-conversions, assisted conversions, and branded search lift. We also offer practical guidelines for CTA placement and examples of lead magnets.

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    16 min
  • Embeddings for Marketers: Mapping Topic Space and Finding Gaps

    Read the full article: Embeddings for Marketers: Mapping Topic Space and Finding Gaps

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    Excerpt:

    Introduction

    Modern content marketing is about more than just choosing the right keywords. Marketers are using embeddings – numerical vector representations of text – to map the meaning of all their articles and topics. In simple terms, an embedding turns each sentence or document into a list of numbers that machines can compare. This lets us “see” which articles are similar in topic or intent, even if they don’t use the same words. For example, in today’s search landscape, Google’s AI systems (like MUM and Gemini) use embeddings to understand the context and intent behind queries (www.ranktracker.com). By leveraging embeddings, marketers can plot their content in a “topic space” and spot clusters of related ideas. This approach reveals how well a content library covers different themes – and where the blind spots are.

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    12 min
  • PR for AI: Seeding Quotable, Verifiable Soundbites and Stats

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    Excerpt:

    PR for AI: Seeding Quotable, Verifiable Soundbites and Stats

    AI assistants (like chatbots and voice agents) are changing how people find information about brands and topics. To ensure your key facts show up in their answers, you must shape content so the AI can “pick up and repeat” it. Recent research shows that nearly 95% of AI citations come from earned or PR-driven sources (muckrack.com). In other words, if your news stories, data and thought leadership aren’t online in a clear, cited form, AI will use someone else’s. This means Public Relations (PR) teams need to create and distribute crisp, quotable facts and stats—formatted for AI.

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    10 min
  • Becoming a Preferred Source for AI: E-E-A-T Signals LLMs Recognize

    Read the full article: Becoming a Preferred Source for AI: E-E-A-T Signals LLMs Recognize

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    Excerpt:

    Becoming a Preferred Source for AI: E-E-A-T Signals LLMs Recognize

    Introduction

    AI-powered search systems (like ChatGPT, Google’s Gemini, and Perplexity) now answer questions by citing reliable websites. These engines tend to pick sources that demonstrate expertise, experience, authoritativeness, and trustworthiness (often called E-E-A-T (bluejar.ai)). In practice, that means AI models look for clues – or signals – on your site and page that show it’s written by a knowledgeable human, backed by facts, and published on a trusted site. This article summarizes what kinds of signals help an AI notice and cite your page. We’ve reviewed dozens of AI-cited pages and research studies to pinpoint key E-E-A-T features. You’ll get a clear checklist for improving your content, guidelines for author bios, and basic trust factors every site needs. Follow these best practices to become a preferred source for AI-generated answers.

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    19 min

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Content marketing and podcast marketing are evolving faster than ever — and automation is at the center of it all. Marketing Automation in 2026 is your go-to podcast for cutting through…