Last updated: 31.07.2026

Why Notion Is 20x More Visible on AI Than Airtable (And What It Teaches Us About Content Chunking)

Notion and Airtable are both platforms for creating customisable workflows, so similar products, for similar audiences, competing for the same searches.

But when you ask an AI assistant which one to use, you're far more likely to hear about Notion. Not because it has a better product. Because it has better-structured content.

We ran the data and it's stark: Notion holds a 41% AI visibility score according to the research we did with Searchable, while Airtable sits at 2%. That's not a slight edge. That's a 20x difference between two products that, on paper, do roughly the same thing.

So what's driving that gap? One concept: content chunking.

This case study breaks down exactly what content chunking is, why it matters for AI visibility, and what Notion is doing right that Airtable isn't. More importantly, it shows what you can take from this and apply to your own website.

What Is Content Chunking?

Content chunking is the practice of structuring your website content so that it flows logically, with topical headings followed by self-contained paragraphs that directly answer the question implied by that heading.

Think of it as writing for a very literal, very efficient reader. One that doesn't skim, doesn't infer, and doesn't piece together meaning from scattered paragraphs. That reader is an AI system.

Why AI Systems Need Chunked Content

When AI assistants like ChatGPT, Perplexity, or Google's AI Overviews generate a response to a user query, they pull from content they've indexed, retrieved, and determined to be relevant. The easier you make that process, the more likely your content ends up in the answer.

Content that is well-chunked gives AI systems three things they need:

• A clear signal of relevance: Headings that mirror the queries people are actually searching tell AI exactly what a section is about.

• Extractable answers: Self-contained paragraphs that answer the heading question can be lifted and cited without requiring surrounding context.

• Logical flow: Content that builds from question to answer, section by section, is far easier to index than content that buries key information inside long, unbroken prose.

The inverse is also true. Content that relies heavily on visuals, animations, or vague section titles gives AI systems very little to work with. The visuals might look stunning. The AI doesn't care.

The core principle: If a paragraph can't be understood without reading the three paragraphs before it, it won't get cited. AI needs content that stands on its own.

The Case Study: Notion vs Airtable

To see content chunking in action, you don't need to look far. Two of the most well-known productivity platforms in the market offer a near-perfect natural experiment.

Same category. Completely different results. The difference comes down to how each brand has structured its website content.

What Notion Gets Right

Notion's landing pages follow a consistent pattern: topical heading, followed by an explanatory paragraph that directly addresses what that heading raises. Repeat. This sounds simple. It is. That's the point.

A few things Notion does particularly well:

Query-matched headings. Notion uses headings that reflect real customer queries. When someone searches "best all-in-one workspace for small teams," Notion's copy explicitly speaks to that intent: "Where teams work better, together. Your projects, wikis and docs, all side by side. For small teams to large organisations." The heading signals the topic. The paragraph delivers the answer. AI can extract that as a clean, citable response.

Use-case specific landing pages. Rather than one generic product page, Notion has dedicated landing pages for different use cases, from student organisations to enterprise teams. Each page targets a distinct audience with relevant headings and copy. This means AI systems can match Notion's content to a much wider range of queries.

Conversational FAQ sections. This is where Notion really earns its AI visibility. Their FAQ sections use full, conversational questions as headings: "Are there any discounts for students?", "How do I sign up for the free Education plan?", "What happens when I graduate or leave my educational institution?" These aren't just helpful for users. They are almost verbatim matches for the queries people type into AI assistants. If AI could smile, it would.

Quotable social proof. Notion doesn't just display its G2 awards visually. It converts them into extractable data: "86% ease of use, 90% ease of admin, 91% meets requirements." Specific numbers that AI can pick up, cite, and use to answer comparative queries. That's the difference between decorative proof and citable proof.

What Airtable Gets Wrong

Airtable's website is, genuinely, beautiful. The animations are polished. The visual design is cohesive. And none of that helps AI form an answer.

Airtable's pages lean heavily on moving graphics and visual-first layouts. A section might show a sophisticated animated interface demo with a short headline like "Production apps at prototype speed" and a two-line description underneath. For a human browsing the page, that looks impressive. For an AI system trying to extract information about what Airtable does and who it's for, it's close to useless.

The problem isn't the visuals. The problem is that the visuals are doing the explaining. When your key value propositions live inside an animated graphic rather than a structured, text-based section, AI systems have very little to index.

Airtable also lacks the query-focused FAQ structure that Notion uses so effectively. Without those conversational question-and-answer sections, Airtable misses the opportunity to appear in the growing volume of AI searches that are phrased as natural language questions.

The fix isn't to strip out the design. It's to ensure there is enough extractable, text-based information alongside the visuals for AI to work with.

What This Means for Your Website

• Notion wins AI visibility because its pages are chunked into clear, query-led sections.

• Airtable looks polished, but too much of the explanation lives in visuals rather than extractable text.

• If AI cannot lift an answer from your page without guesswork, your content is already at a disadvantage.

• The fix is not uglier design. It is clearer structure, stronger headings, and more self-contained sections.

The Notion vs Airtable gap isn't a fluke. It's a repeatable pattern. Brands that structure their content for extractability consistently outperform those that don't, regardless of how much they invest in design, paid search, or traditional SEO.

The question is whether your website looks more like Notion's or Airtable's from an AI's perspective.

The Four Principles Behind Notion's Approach

Apply these to your own landing pages and you'll be significantly better positioned than most of your competitors:

1. Match your headings to real queries. Think about the questions your customers type into AI assistants. Then use those questions, or close variants, as your section headings. Not creative headlines. Not vague taglines. Actual questions your audience is asking.

2. Write self-contained sections. Every section on your page should be able to stand alone. If someone reads only that heading and its paragraph, they should walk away with a complete, useful answer. No cliffhangers. No "as mentioned above."

3. Add a conversational FAQ. This is one of the highest-impact, lowest-effort changes you can make. A FAQ section with full, natural-language questions mirrors exactly how people query AI assistants. It's also one of the most reliably extracted content formats across ChatGPT, Perplexity, and Google's AI Overviews.

4. Turn your proof into data. Don't just show awards and logos. Quantify them. "Rated 4.8 by 3,000+ users" is far more citable than a badge graphic. "91% of customers say it meets their requirements" is an answer. A G2 badge is not.

The Bigger Picture

This isn't about gaming AI systems. It's about communicating clearly. The brands that are winning in AI search are the ones that have made it easy for any reader, human or machine, to understand exactly what they do, who they do it for, and why it matters.

Aesthetics and structure are not mutually exclusive. You don't have to choose between a beautiful website and an AI-visible one. You just need to make sure the structure is doing its job alongside the design.

Airtable's website isn't bad. It's just optimised for the wrong audience. The right audience, right now, includes every AI assistant that a potential customer might ask before they ever visit your site.

Need a Website Content Restructure?

If your website looks more like Airtable's than Notion's right now, that's fixable. Content chunking isn't a technical overhaul. It's a strategic rewrite, and it's one of the highest-ROI changes you can make for AI visibility.

At decipher., we help brands restructure their website content so AI systems can actually understand, index, and recommend them. Not generic optimisation. A proper audit of what you have, what's missing, and what needs to change.

Drop us a line if you'd like to find out what your AI visibility score looks like, and what it would take to close the gap.