Overview
You want AI that reads your research and helps you connect dots.
Notebook LM lets you ask questions about your documents and get structured responses from them.
Annual price
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Starting from
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Researchers and marketers summarising large documents with AI
Upload PDFs and ask questions to extract insights.
Turn raw notes into briefings or summaries.
Cross-reference across multiple research sources.
Notebook LM
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Consider this before you purchase
Price
NotebookLM is currently free to use, which lowers the barrier to entry for trying it out. There’s no standalone fee at the moment you can upload documents and use all features without paying. Google has hinted at advanced offerings (NotebookLM Plus) for enterprise users, likely bundled with its paid Gemini AI add-on for Workspace. In practice, that means small teams and individual marketers can experiment at no cost, while larger organisations might pay later for enhanced team features. The free-versus-paid split is straightforward: the core tool is free now, and premium capabilities (like higher usage limits or domain-wide sharing) come with a Google Workspace plan.
Ease of use
NotebookLM has an intuitive interface once you understand its approach. It isn’t a traditional blank-page notebook instead, you start by uploading sources related to a topic. The UI then presents a Notebook Guide with auto-generated summaries and suggested questions, making it easy to dive into your material. Interacting with the AI feels as simple as chatting: ask a question at the bottom of the page, and it replies almost instantly. There is a short learning curve (since you must provide content to get value), but Google’s clean design means most marketers will find their way around in minutes. Overall, it’s a no-code, friendly tool that fits neatly into a Google-centric workflow.
Team collaboration
Collaboration is a mixed bag. In the standard (free) version, notebooks are private silos you can’t co-edit or have multiple people querying the same notebook in real time. Each “notebook” is essentially your personal folder of sources and notes. For a team, this means knowledge can end up fragmented by user. However, Google recently introduced sharing capabilities: you can create a public link to a notebook, letting coworkers interact with it in read-only mode. And for Workspace enterprise customers, NotebookLM Plus enables fully shared team notebooks and internal access controls. In short, out-of-the-box collaboration is limited great for solo research, but true multi-user support requires the paid Workspace environment. If you need everyone on the team on the same page, plan for that upgrade or be ready to manually share outputs.
Depth of insight
This is where NotebookLM shines. It uses source-grounded AI, meaning it only draws answers from the documents you provide. The upside is highly relevant, accurate responses with citations for transparency. In practice, the tool can digest large volumes of text think dozens of PDFs, Google Docs or even YouTube transcripts and answer complex questions by synthesising across them. It can handle up to millions of words of input, so you won’t easily hit a limit. The depth of insight you get is impressive: NotebookLM auto-generates summaries, study guides, timelines and even Q&A flashcards from your sources, giving you multiple angles on the content. In my experience, it feels like having an analyst on-call who has read everything and can distil key points on demand. The only caveat: the AI won’t go beyond your uploads, so its brilliance depends on the quality of the material you feed it.
Integration into research habits
For B2B marketers and founders, research rarely lives in one format we juggle books, PDFs, web articles, and videos. NotebookLM fits into these habits by accepting a wide range of source types. You can drag in PDF whitepapers, link a web article or Google Doc, and even paste a YouTube link to ingest the video’s transcript. This flexibility means your competitive analyses, market research reports and recorded interviews can all live in one notebook. It complements existing workflows: if you keep notes in Google Docs, NotebookLM can work directly with them; if you prefer annotating PDFs, you can still upload them here for AI processing. One limitation is that it’s text-focused it won’t analyse raw images or videos without transcripts. And while it doesn’t directly plug into tools like Notion or Evernote, you can export AI-generated summaries or notes and paste them back into your knowledge base. In short, NotebookLM slots in well if your research materials are digitised, and it can become a central hub for synthesising information from all those books, articles and webinars you’d otherwise struggle to manually summarise.
My honest review about
Notebook LM
As someone responsible for growth, I approached NotebookLM with healthy skepticism and a hopeful eye. After using it in real scenarios, I found it to be a powerful adjunct to my workflow with a few caveats.
What NotebookLM does well
Accurate, contextual answers
NotebookLM’s insistence on using your data means it very rarely goes off-script. In practice, I got confident answers sourced from our exact market research and sales decks, rather than generic AI guesses. The built-in citations bolster credibility when sharing findings with the team.
Multi-format ingestion
I was impressed by how easily it digested a mix of content. I uploaded a 50-page PDF, a Google Doc of notes, and a YouTube keynote transcript; NotebookLM combined them and answered questions that spanned all three sources seamlessly. This saved me hours of cross-reading.
Rapid summaries and audio overviews
The auto-generated study guides and summaries are excellent for quick learning. In one case, I used the Audio Overview to turn a lengthy strategy document into a 5-minute AI podcast perfect for absorbing info on my commute. It’s not just novel; it genuinely helped me retain the content by listening.
Free to start
Budget matters in growth teams, so the fact that NotebookLM’s full feature set is free (for now) made it easy to pilot within my organisation. We didn’t have to justify a line item to get value from it, and that’s a big win for trying new technology.
Where NotebookLM falls short
Not a stand-alone note app
Don’t expect NotebookLM to replace your primary note-taking or wiki system. It’s fantastic for analysing and querying documents, but you can’t organically build a connected knowledge web inside it. I missed being able to freely jot thoughts or link concepts between notebooks that kind of personalisation isn’t possible here.
Limited collaboration (in free version)
From a team perspective, the free NotebookLM felt isolating. I could do brilliant research, but there was no smooth way to share that interactive notebook experience with colleagues (aside from sending them a static summary). Google is addressing this with sharing links and the enterprise NotebookLM Plus, but regular users will find it a mostly solo tool. For a growth leader, that means insights might stay stuck with one person unless extra effort is made to distribute them.
Requires quality input
This isn’t a magic oracle that answers anything it’s only as good as the content you give it. If your sources are outdated or shallow, NotebookLM won’t generate deep insights beyond them. I learned that it’s best used when you already have rich data (customer interviews, research reports, etc.) that need synthesising. It’s less useful if you’re starting from scratch on a topic, where a general AI like ChatGPT might actually provide a broader primer.
Workflow fit
Finally, there’s the question of habit. My team found that going to a separate NotebookLM site took getting used to it’s another place to manage content. It integrates with Google Drive to an extent, but it’s not embedded in tools like Gmail or Slack. So while it’s great for focused research sessions, it hasn’t replaced our quick Google searches or internal wiki for on-the-fly queries. It feels like a specialised instrument rather than an everyday universal tool.
Is NotebookLM right for you?
In my view, NotebookLM is a strong fit for B2B professionals who deal with information overload. If you’re a content marketer synthesising long reports, a sales enablement lead gathering battle cards, or a founder doing deep-dive learning on your industry, NotebookLM can be a game-changer. It excels at turning a dump of documents into coherent answers and summaries which is exactly what time-pressed teams need when preparing strategies and client pitches. Its strengths in accuracy and multi-source analysis shine in scenarios where precision matters (think investor memos, product FAQs, or compliance docs).
On the flip side, if your work is more about day-to-day note jotting or brainstorming, you might find NotebookLM less helpful. It won’t manage your to-do list or replace the collaborative knowledge base your team updates daily.
Also, extremely small businesses or early-stage startups might not have enough internal documentation to really leverage the tool’s power there needs to be some meat for the AI to chew on. In those cases, a general AI assistant or traditional note app might suffice. But for anyone regularly consuming dense information, NotebookLM is absolutely worth a try. It’s one of those rare tools that can take a week’s worth of reading and boil it down into an afternoon’s insight, and that alone earns it a spot in the modern B2B toolkit.
Ultimate guide for
Notebook LM
NotebookLM can be more than a novelty it can slot into your business routines in very practical ways. Below is a guide to high-leverage use cases for founders and marketing teams, complete with tips on how to make the most of this AI assistant.
Building research notebooks for marketing and sales teams
The most straightforward way to use NotebookLM is as a collective research brain for your team. You can create separate notebooks for key topics for example, Industry Trends 2025, Competitor Analysis, or Sales Playbook. Into each notebook, upload all relevant materials: market research PDFs, competitor blog posts, product spec sheets, and so on. NotebookLM will then serve as an on-demand researcher, ready to answer questions like “What’s the biggest trend in our industry this year?” or “How does Competitor X position their pricing model?” by drawing only from those curated sources.
For marketing teams, this means faster campaign planning (since you can quickly query past campaign results or customer research stored in a notebook). For sales teams, it means having a dynamic playbook reps can ask the notebook for product details or case study highlights without digging through archives. A best practice here is to keep notebooks focused: grouping sources by theme ensures the AI’s answers stay on-topic. And remember to refresh the content periodically (upload new reports or remove outdated ones) so your team is always querying the latest intel.
Using NotebookLM to prep for sales calls
In B2B sales, preparation is half the battle. NotebookLM can act as your personal briefing assistant before important meetings. Here’s a simple workflow to leverage it for a sales call:
- Gather intel on the prospect: Create a new notebook and add everything you have on the prospective client their website content, any relevant news articles or press releases, LinkedIn posts from their leaders, and your past meeting notes or emails.
- Generate a briefing: Ask NotebookLM for a summary of the company’s background and key initiatives, or pose specific questions like “What pain points has this prospect mentioned in our communications?” The AI will produce a concise brief, citing the exact sources (useful for double-checking facts).
- Prepare talking points: Use the Q&A to drill down into areas of interest. For instance, if the prospect’s blog mentioned a challenge, ask “How have they described their [challenge]?” NotebookLM can pull a direct quote or overview from the text. You can even request a list of questions to ask them, based on their content a handy way to craft insightful questions that show you’ve done your homework.
- On-the-go refresh: If you’re traveling to the meeting, consider using the Audio Overview feature. It can generate a quick podcast-style narration of the briefing notes, so you can listen and reinforce your memory of the details on the way.
By the time you join the call, you’ll have a rich understanding of the client’s context without spending hours sifting through documents. This approach ensures you walk in with confidence, armed with relevant knowledge that can spark meaningful dialogue and tailor your pitch to the client’s known interests.
Collecting and summarising customer interviews
Customer interviews and surveys are goldmines of insight but only if you can extract the patterns from them. NotebookLM helps by taking all those raw transcripts or notes and doing the heavy lifting of synthesis. A recommended method is: after conducting a batch of customer interviews, dump the transcripts (text files, Google Docs, or PDF exports) into a single notebook titled, say, Customer Voices Q1. Then use NotebookLM to ask high-level questions like “What are the top recurring pain points mentioned by customers?” or “Summarise how customers describe our product’s value.” The AI will scan across every interview to find common threads and report them, often with direct quotes and references to which interview they came from.
This not only saves your team days of manually coding responses, but it ensures you don’t miss subtle recurring themes that a quick read-through might overlook. You can also prompt NotebookLM to create a briefing document or FAQ from the customer feedback for example, “Generate a brief that highlights the main suggestions our users gave us.” The result can serve as an internal report for product and marketing teams. For credibility, NotebookLM’s cited answers let you trace each insight back to a specific customer’s words, which is useful when presenting findings (“Customers frequently mention the onboarding process being confusing see quotes from Interview A and B”). In short, this turns a qualitative data dump into actionable intelligence in a fraction of the time.
Creating training notebooks for onboarding
Onboarding new team members is resource-intensive, but NotebookLM can help make it more self-service and engaging. The idea is to create an Onboarding Notebook that becomes a go-to companion for any new hire’s first weeks. Populate it with all the relevant training materials: your company handbook, HR policies, product one-pagers, key strategy docs, and even links to introductory videos or webinars. With everything in one place, a newcomer can use NotebookLM to get up to speed faster.
For instance, they might ask, “What is our ideal customer profile?” and get a distilled answer sourced from your marketing strategy docs. Or if they’re in sales, they could query, “How do we handle common objections?” and NotebookLM will pull from the sales playbook PDF you included. The notebook’s FAQ and summary features are also handy: a new hire can generate their own FAQ list about the business or have the tool produce a “study guide” on the product portfolio to accelerate learning. This empowers the employee to explore and find answers 24/7, without always resorting to pinging a colleague. It’s like an interactive mentor that’s always available. Additionally, the audio overview can turn the dense HR policy document into an easier listening experience not exactly riveting, but certainly more accessible than reading 40 pages. While this notebook won’t replace personal mentorship, it ensures that much of the foundational knowledge transfer can happen asynchronously and consistently. It’s especially valuable in a scaling company where you hire frequently and want a repeatable, high-quality onboarding experience.
Building a notebook around a book or lecture
Continuous learning is crucial for growth leaders and marketers. Whether it’s the latest marketing book or a conference lecture by an industry thought leader, NotebookLM can help turn that content into actionable takeaways for your business. The process is straightforward: after you finish reading a business book (or even midway through), upload the book’s PDF or a lengthy summary into NotebookLM. Similarly, for a lecture or podcast, find a transcript and add it as a source. Now you have a personal AI tutor for that material.
You can start by asking for a chapter-by-chapter summary or the key insights from the content. More importantly, you can query how those insights relate to your context. For example: “What does [Book X] advise about customer retention?” or “According to this lecture, what should a startup focus on in marketing?” Because the AI is grounded in the specific text, it will give you pointed answers or direct quotes from the author. This beats generic book reviews because you’re engaging with the actual material in a dialogic way. I’ve used this approach to quickly harvest ideas from books and then share a one-page brief with my team on how we might apply them. In one case, I even had NotebookLM generate a set of discussion questions from a leadership book, which I then used in a team lunch-and-learn session. Essentially, NotebookLM helps transform passive reading or listening into an interactive study session with outputs you can directly use in strategy decks or team discussions.
Turning documents into podcasts or audio briefings
One of NotebookLM’s most unique features is its ability to generate an audio overview effectively turning written documents into a podcast-like experience. This has several high-leverage uses in a B2B setting. For busy founders, it means you can listen to that lengthy report or whitepaper while driving or exercising, instead of finding time to read it at your desk. For marketing teams, you could transform a case study or research paper into an internal podcast episode and share it with the team for easy consumption. The audio is generated with realistic voice synthesis, and you can even customise it to focus on certain sections or themes of the source material.
To use this feature, pick a source (or multiple) in your notebook and click on the audio overview option. In a few minutes, NotebookLM will produce an MP3 with two AI voices discussing the content of your documents almost like a radio interview that covers the key points. It’s surprisingly engaging and can make dense information more palatable. In my experience, hearing our own strategy document narrated back in a conversational tone was both insightful and slightly eerie (in a good way!). The convenience factor is huge: team members can digest content during otherwise dead time, and you’ve effectively repurposed one piece of content into another format with zero human effort. Just remember that while the audio is high-quality, it’s AI-generated I usually advise giving it a quick listen yourself before distributing, to ensure the emphasis is where you want it. All told, this feature turns NotebookLM into a mini production studio for knowledge sharing, ideal for enabling a learning culture in your company.
Other high-leverage uses in a B2B context
- Competitive and market analysis: Create notebooks that aggregate competitors’ datasheets, blog posts, and analyst reports. NotebookLM can then answer strategic questions like “What is Competitor Y’s unique selling point according to these sources?” or “Summarise the overall market outlook this year.” This helps growth teams quickly pinpoint how you stack up and identify opportunities or threats without reading every line of every report.
- Content marketing research and repurposing: If you’re crafting a whitepaper or an eBook, load up all your source material (industry statistics, previous blog posts, technical papers) into a notebook. Use the AI to pull out key statistics or quotes to strengthen your content. Later, flip the script and use NotebookLM to repurpose the finished content for instance, ask it to generate a brief or an outline that could become a blog post, or use the audio feature to create a podcast version of your whitepaper to share with your audience.
- Internal knowledge base Q&A: Beyond formal onboarding, you can maintain a living notebook for company knowledge (policies, SOPs, meeting notes). Instead of browsing a wiki, team members could query NotebookLM for answers like “How do I request marketing collateral for a client?” and get an instant answer drawn from the latest ops manual. It’s an experiment in making internal documentation more interactive and user-friendly.
In conclusion, NotebookLM is a versatile tool that, when used creatively, can amplify many areas of B2B work. From speeding up sales prep and marketing research to fostering continuous learning, it has the potential to save time and surface insights that might otherwise stay buried. As with any tool, success comes from integrating it into your routine but given how seamlessly it works with common formats and how it’s evolving within Google Workspace, NotebookLM is well worth adding to your arsenal if you’re aiming to work smarter in the world of B2B.
Playbook
AI for marketers
Use AI for research, briefs and QA. Set prompts and review steps, train the team, and track time saved without risking quality. Focus on cases that strengthen the work.
See playbook