https://www.cmswire.com/digital-marketing/the-aeo-seo-readiness-playbook-every-marketing-team-needs/?utm_source=flipboard&utm_content=other
Tuesday, June 23, 2026
Why Google’s New NotebookLM 2.0 Update is a Massive Game Changer
Why Google’s New NotebookLM 2.0 Update is a Massive Game Changer
By
NotebookLM 2.0 introduces a suite of upgrades aimed at enhancing productivity and adaptability across various workflows. Powered by the advanced Gemini 3.5 AI model, this version emphasizes both performance and transparency, making it particularly effective for tasks like data analysis and content creation. Paul Lipsky highlights how the platform’s expanded file export options, such as editable PDFs and PowerPoint presentations, integrate seamlessly with external applications like Google Slides. For instance, users can generate a presentation within NotebookLM, refine it externally and maintain formatting integrity throughout the process, an invaluable feature for professionals managing complex projects.
Dive into this breakdown to uncover how NotebookLM 2.0 supports more personalized workflows, allowing users to create tailored outputs like charts, summaries and reports. You’ll also gain insight into its secure cloud environment for advanced research, as well as its commitment to source integrity, making sure that outputs remain accurate and reliable. Whether you’re exploring its transparent reasoning process or learning how it adapts to unique data sets, this guide offers a clear look at the platform’s capabilities and practical applications.
Expanded File Creation and Export Options
TL;DR Key Takeaways :
- NotebookLM 2.0 introduces enhanced file creation and export capabilities, allowing users to generate and export editable PDFs, PowerPoint presentations, Excel spreadsheets and charts, making sure seamless integration with tools like Google Slides and Excel.
- Powered by the advanced Gemini 3.5 AI model, the platform delivers more accurate and reliable outputs with transparent reasoning, making it ideal for complex tasks like data analysis and market trend evaluations.
- The platform features advanced research and analysis tools, including a secure cloud computing environment and an intuitive chat interface, allowing deeper data evaluations and context-aware suggestions.
- Personalized workflows allow users to create tailored notebooks with customized outputs such as charts, summaries and reports, streamlining tasks and providing actionable insights for both personal and professional use.
- NotebookLM 2.0 emphasizes source integrity, making sure outputs are grounded in user-provided or approved data, making it a trustworthy tool for sensitive projects like financial reporting, academic research and legal documentation.
NotebookLM 2.0 introduces a significant upgrade in file creation and export functionalities, allowing users to generate and export editable PDFs, PowerPoint presentations, Excel spreadsheets and charts directly from the platform. These files are fully compatible with external tools such as Google Slides and Excel, making sure seamless integration into existing workflows. For instance, if you are preparing a business presentation, you can generate a PowerPoint deck within NotebookLM, refine it in Google Slides and preserve both formatting and data integrity throughout the process. This feature simplifies complex tasks, saving time while maintaining professional standards.
Enhanced Performance with Gemini 3.5
The integration of the Gemini 3.5 AI model brings a significant leap in performance, delivering outputs that are not only more accurate but also more reliable. A standout feature of this upgrade is its transparent reasoning process, which explains how results are generated. This is particularly beneficial for complex tasks such as data analysis or market trend evaluations. For example, when analyzing market trends, the AI provides clear, step-by-step explanations for its conclusions, allowing you to verify the results and make informed decisions. This transparency fosters trust and ensures that the outputs are both actionable and dependable.
Here is a selection of other guides from our extensive library of content you may find of interest on NotebookLM.
- Google Just Put NotebookLM Inside Gemini and It Changes Everything
- New Powerful NotebookLM Updates for Workflow, Outputs, Slide Decks, Mind Maps & More
- Gemini Gems Bring NotebookLM Notes into Google Docs & Sheets
- Using NotebookLM with Gemini for Evidence-Based Content Creation
- Google Just Put NotebookLM Inside Gemini: Here’s What You Can Do Now
- 10 NotebookLM Tips & Tricks to Instatntly Improve & Speedup Your Workflows
- New NotebookLM Features : 10 Infographic Presets & Custom Styles
- How Combining NotebookLM and Obsidian Transforms Your Research Workflow
- NotebookLM vs Gemini : Quick Guide to Choosing the Right AI Tool
- Why NotebookLM’s Gemini 3.5 Upgrade is a Major Shift for Data Analysis and Research
Comms Stategy Tools - Julien Cole
If you love Comms Strategy,
Here are 7 tools and resources that I personally use;
1. Consumer Journey Research Template - https://lnkd.in/gtsmSMfA
2. The Noun Project - library of icons to make your deck look pro https://lnkd.in/gfWyCuAM
3. ToolboxToolbox - a treasure trove of process docs for workshops https://lnkd.in/gpbtxG7W
4. Hyper Island Toolbox (gated access, requires registration) - If you're running consumer journey workshops, there are a number of good activities in here https://lnkd.in/gQ_X8RAB
5. 12 Q's Comms Strategy Checklist - Once you understand what is central to your idea, use these questions to show how far the idea can stretch. https://lnkd.in/gi-h9Ac2
6. Comms Strategy Stats - Strategists, this document is going to save you hours. Need proof of the value of Comms Strategy? I got the receipts in this deck. https://lnkd.in/gUgPf7JH
7. 10 Campaign Ecosystem Examples - There’s no one right size with campaign ecosystems. This deck highlights some of the popular types of ecosystem, along with examples from Pringles, Dove, Reddit, and more. https://lnkd.in/guSSKxYF
If you’re interested in getting the essential skills for effective comms strategy
Generative Engine Optimization (GEO) in 2026: How to Get Your Content Cited by ChatGPT and AI Overviews
Generative Engine Optimization (GEO) in 2026: How to Get Your Content Cited by ChatGPT and AI Overviews
a 2026 evergreen guide — the deal is the clearest market signal yet, not a breaking-news event — to what GEO is, why it matters, and how to actually do it.
By Richard L. Wells
Published: Jun 14 2026, 17:26 PM EDT
ChatGPT application displayed on a smartphone screen, highlighting its growing role in everyday life and the increasing reliance on artificial intelligence tools that are shaping decision making and automating tasks, amid rising concerns over AI monopolizing certain jobs and prompting companies to reduce their workforce, in Tunis,Tunisia on May 5,2026. Imen Ben Youssef/Getty Images
When Adobe agreed to acquire Semrush for about $1.9 billion in an all-cash deal announced on November 19, 2025, it put a price tag on a discipline that barely had a name two years ago: Generative Engine Optimization, or GEO. Adobe framed the purchase explicitly around brand visibility "in the agentic AI era," and Semrush has spent the past year pitching GEO as a growth channel that sits beside traditional search engine optimization (SEO) rather than replacing it. This is a 2026 evergreen guide — the deal is the clearest market signal yet, not a breaking-news event — to what GEO is, why it matters, and how to actually do it.
What GEO Is (and Its Many Aliases)
Generative Engine Optimization is the practice of structuring content and managing online presence so that AI answer engines — ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude — cite, quote, or recommend you inside the answers they generate. If classic SEO is about ranking a blue link on page one, GEO is about being part of the synthesized answer itself.
The term was coined in a 2023 academic paper, "GEO: Generative Engine Optimization," by researchers led by Pranjal Aggarwal. Since then a thicket of near-synonyms has grown up around it. According to Wikipedia's entry on the topic, related terms include answer engine optimization (AEO), artificial intelligence optimization (AIO), AI SEO, and large language model optimization (LLMO); generative search optimization (GSO) is also used. The distinctions are mostly marketing nuance — AEO leans toward direct-answer formats, LLMO toward the model layer — but they all describe the same goal: getting machines that write answers to surface your content.
Why GEO Matters Now
The shift is being driven by sheer usage. OpenAI said ChatGPT reached more than 900 million weekly active users, a figure it disclosed in late February 2026 alongside a new funding round — up from 800 million in October 2025 and roughly double the 400 million reported a year earlier.
The traffic data is shifting too. Previsible's 2025 State of AI Discovery report, which analyzed 1.96 million large-language-model sessions, found AI-referred sessions jumped 527% between January and May 2025 — from roughly 17,000 to about 107,000 in the dataset. The report cautions that all AI-platform traffic still amounts to less than 1% of total web traffic, so the percentage is explosive growth from a small base.
Analysts expect the base to grow. Gartner predicted in February 2024 that traditional search engine volume would fall 25% by 2026 as users turn to AI chatbots and virtual agents — a forecast about search-volume erosion, not a measured share of answers. (Note: this is a projection, not a confirmed measurement of current AI answer share.)
How GEO Actually Works
The mechanism underneath GEO is retrieval-augmented generation (RAG). As Wikipedia describes, generative search systems index, embed, and retrieve semantically relevant text passages from external documents, then synthesize an answer and cite the passages they leaned on. That changes the unit of optimization from the page to the passage. Content is chunked, embedded as vectors, and pulled in when it is the most semantically relevant match for a query — so clarity, structure, and self-contained claims matter more than keyword density.
Several practical implications follow. Front-loading matters: AI retrieval and summarization weight opening content heavily, so the answer to the question should appear in roughly the first 200 words. Structured, semantic formatting — clear headings, lists, tables, and direct question-and-answer phrasing — makes passages easier to extract. Schema and structured data help machines parse facts. And authority signals matter: Wikipedia notes that GEO practitioners emphasize E-E-A-T (experience, expertise, authoritativeness, trustworthiness) and external citations, while academic auditing has found generative search engines draw heavily on news and media sources, with measurable commercial and geographic citation bias. A newer concept is "prompt volume" — how often people ask an AI about a topic — which is replacing keyword search volume as the demand signal marketers chase.
GEO vs. SEO: An Additive Layer, Not a Replacement
The most authoritative voice on this is Google itself. In May 2026, Google published its first official guide to optimizing for generative AI features on Search. Its position, as Search Engine Journal summarized, is blunt: because AI Overviews and AI Mode are rooted in core Search ranking systems, "optimizing for generative AI search is still SEO," and AEO and GEO are treated as part of SEO rather than separate disciplines. Google also said llms.txt files, AI-specific content rewriting, and special schema are not needed for its generative features — the same foundations apply: useful content, crawlable pages, clear structure, and a trustworthy page experience.
The practical takeaway: GEO is an additive layer on top of solid SEO, not a replacement for it. Content that already ranks well in organic search tends to perform well in AI Overviews.
The Tools: Semrush and Ahrefs
Two incumbents now anchor the GEO tooling market. Semrush's AI Visibility Toolkit tracks how brands appear across ChatGPT, Gemini, Google AI Overviews, and AI Mode, drawing on what the company describes as a database of more than 261 million prompts and responses. Its Prompt Volume / Prompt Research feature estimates topic-level AI demand — the GEO analog to keyword volume.
Ahrefs launched Brand Radar in March 2025 as an AI visibility tool. It now tracks brand mentions across six AI indexes — Google AI Overviews, Google AI Mode, ChatGPT, Perplexity, Gemini, and Microsoft Copilot — and, unlike tools that use synthetic prompts, derives its prompts from real search behavior.
A GEO Checklist for Publishers and Marketers
Front-load the answer in the first ~200 words; put the conclusion before the explanation.
Structure for extraction: clear headings, short paragraphs, lists, tables, and explicit Q&A.
Add and maintain schema/structured data so machines can parse facts.
Strengthen E-E-A-T: bylines, credentials, citations to primary sources, and original data.
Earn third-party authority: credible coverage and digital PR raise citation odds.
Track prompt volume, not just keyword volume, with a tool like Semrush or Ahrefs Brand Radar.
Test prompts yourself across ChatGPT, Perplexity, and AI Overviews; see who gets cited and why.
Keep doing SEO: crawlable, fast, trustworthy pages remain the foundation.
Frequently Asked Questions
What is GEO (Generative Engine Optimization)? GEO is the practice of structuring content so AI answer engines — ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude — cite or recommend it in the answers they generate. The goal is to be part of the AI's answer, not just a ranked link.
Is GEO the same as SEO? Not exactly, but they overlap heavily. Google's official 2026 guidance says optimizing for its generative AI features "is still SEO," and most experts treat GEO as an additive layer on top of strong SEO rather than a separate discipline.
How do I optimize for ChatGPT and Google AI Overviews? Front-load the answer in the opening lines, structure content for extraction with headings and Q&A, add schema, strengthen authority signals, and earn citations from credible third parties. Then test your target prompts and study which sources the engines cite.
Does GEO replace SEO? No. GEO sits on top of SEO. Content that already ranks well organically tends to perform well in AI Overviews, and Google says the same foundations — useful, crawlable, trustworthy pages — drive both.
Monday, June 15, 2026
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Here's how I actually set up Claude to run like a marketing system:
Step 1 — Universal instructions
→ Go to Settings → Custom Instructions.
↳ Tell Claude who you are, your brand voice, your audience, your tone, what you never say.
Every conversation inherits this. You stop re-explaining yourself every single time.
Step 2 — Projects
→ Create a Project for each function: content, email, client work, research.
↳Upload your SOPs, past examples, brand docs directly into the Project.
Claude now has context that persists. It remembers what matters for that role.
Step 3 — Skills
→ Build repeatable prompt templates inside each Project.
↳ One for writing LinkedIn posts. One for campaign briefs. One for customer journey analysis.
You stop prompting from scratch. You run plays.
Step 4 — MCP connections
→Connect Claude to your actual tools — Google Drive, Gmail, your CRM, your calendar — using MCP (Model Context Protocol).
Now Claude runs like your marketing command center.
It reads your files, pulls your data, acts inside the systems you already use.
→ Step 1 gives Claude your identity
→ Step 2 gives Claude your context
→ Step 3 gives Claude your process
→ Step 4 gives Claude your infrastructure
Most people just use Claude as a chatbot and skip all 4 and wonder why AI feels like extra work.
The tool was never the problem. The setup was.
I wrote a full guide on how to master claude for marketing. If you want it, just follow me and DM me "Claude Setup" and I'll send it to you.