The 3 Pillars of SEO - Understandability Credibility Deliverability
I created this framework in 2019 when giving a talk in Melbourne, Australia, and at the time I called it the Three Pillars of SEO. The insight was simple: have empathy for Google. If you think about what Google actually needs, you can make optimisation significantly easier. Google’s three fundamental problems are understanding what you’re offering, evaluating the credibility of what it’s found, and determining whether it can deliver your content as the best solution to its user.
That was the original insight, and it still holds. But the world has changed around it.
In 2020, the framework applied to one algorithm on one platform. In 2026, it applies to every algorithm on every platform: Google, ChatGPT, Perplexity, Claude, Copilot, Siri, Alexa. The structural logic proved universal because every algorithm (whether it is a search engine, Knowledge Graph, or Large Language Model) must understand before it can trust, and trust before it can recommend. That is not a choice these systems make. It is a structural constraint of how algorithmic processing works.
The framework is now the backbone of The Kalicube Process™, and the terminology has evolved accordingly. Understanding became Understandability, and the third pillar was originally “Suitability” before I settled on Deliverability. The framework now carries a formal notation: U, C, D.
Here’s how the three pillars work today.
Understandability
The algorithm needs to understand who you are and what your offer is before it can present you to its users.
In 2020, that meant Google showing you in search results. In 2026, it means seven AI platforms recommending you in conversations, and the stakes are considerably higher because these platforms are not showing a list of ten options. They’re giving one answer. If the AI does not understand who you are, you are not in the conversation at all.
Understandability maps to the bottom of the funnel (BOFU). When someone searches your brand name or asks an AI “Who is [Your Brand]?”, the result is your AI Resume (what I call the Brand SERP), and that AI Resume is the moment of truth. If the AI can’t confidently state who you are, what you do, and who you serve, you’re paying what I call the Doubt Tax: revenue lost because the AI hesitates about your brand at the decision moment.
Achieving Understandability still involves many of the same elements I described in 2020: clear copywriting, Schema markup, and explicit communication of what you offer. But it now extends further. You need a single source of truth (your Entity Home, typically your website) that all AI platforms can reference, consistent corroboration of your identity across your entire digital ecosystem, and confidence in the Knowledge Graph’s understanding of your entity and its attributes.
The principle remains: you are trying to explain to algorithms who you are and what you offer. The difference is that you’re now explaining it to seven algorithms simultaneously, and they all need to reach the same conclusion.
Credibility
Once the algorithm has understood that your offer and your competitor’s offer address the same need, how does it decide which one to recommend? Credibility.
You might call it E-E-A-T (experience, expertise, authoritativeness, trustworthiness), and credibility covers the same ground. The algorithm evaluates peer group approval, reviews, editorial endorsements, and third-party corroboration. It is looking for evidence that you are the most trustworthy solution, not just a solution.
Credibility maps to the middle of the funnel (MOFU). When a potential customer asks an AI “What are the best options for [your category]?”, you need to be in that response. If you’re not, you’re paying the Ghost Tax: revenue lost because the AI recommends competitors instead of you. You’re a ghost in the conversation. The AI recommends them not because they are better, but because their Cascading Confidence (the cumulative trust an algorithm builds through its processing pipeline) is higher. Their digital footprint did a better job of educating the algorithm.
Schema markup continues to play a significant role here, pointing the algorithm to all the online signals that confirm your credibility. But credibility in the AI era goes beyond links and reviews. It requires consistent corroboration across multiple sources that are themselves credible. The algorithm is not counting votes. It is evaluating the quality and consistency of the evidence chain.
Deliverability
This is the pillar that most people in digital marketing still overlook, and it’s the one that has evolved the most since 2020.
In 2020, I framed Deliverability as whether Google could pick up your content and deliver it in the SERP. Could it reach into your page, extract the relevant piece, and present it? That’s still part of the picture. Well-structured HTML, Schema markup, appropriate media formats, mobile friendliness, and page speed all contribute to whether an algorithm can deliver your content effectively.
But Deliverability has grown into something larger. It is now about visibility and advocacy. Can the algorithm deliver you to the RIGHT audience, in the RIGHT format, at the RIGHT time? And will it actively advocate for your brand in top-of-funnel discovery conversations?
Deliverability maps to the top of the funnel (TOFU). When someone asks an AI a topic question where your brand should be part of the answer, is the AI introducing you into the conversation? If it isn’t, you’re paying the Invisibility Tax: revenue lost because AI stays completely silent about you. These are the deals you’ll never know you lost, because the pipeline never even formed.
Content repurposing remains HUGELY powerful here (as I noted in 2020) because the overlaps of intent, device, topic, geo, and entity multiply your opportunities for delivery. But the principle now extends across all the platforms in the Algorithmic Trinity (Knowledge Graphs, Large Language Models, and traditional search engines). Your content needs to be present, accessible, and suitable for delivery across all three.
The Build Order
There’s a deliberate sequence to these three pillars, and this is where the framework gains its structural power.
You build in the order U, C, D. Foundation first. You cannot build credibility for an entity the algorithm does not understand. You can’t achieve advocacy from an algorithm that doesn’t yet trust you. Each pillar depends on the one before it.
But you display them in the reverse order: D, C, U. Because the customer journey flows from the top of the funnel to the bottom. The AI first introduces your brand (D), then recommends it in comparisons (C), then confirms your identity at the decision moment (U).
This dual directionality (build U to C to D, display D to C to U) maps to what I now call the Zero-Risk Year: Phase 1 fixes Understandability leaks, Phase 2 locks in Credibility, Phase 3 expands Deliverability. It also maps to Cascading Confidence, where trust that compounds or decays at each stage of the algorithm’s processing pipeline flows through three multiplicative layers: Entity Confidence (U), Content Confidence (C), and Presentation Confidence (D).
What Has Not Changed
If you look at your digital marketing work, everything you do must serve one or more of these three pillars. That was true in 2019 when I first described the framework, it was true in 2020 when Search Engine Journal published this article, and it’s true in 2026 as AI assistive engines become the primary interface between brands and their audiences.
The algorithm still needs to understand you. It still needs to trust you. It still needs to deliver you to the right person, in the right format, at the right moment. And Schema markup still serves all three pillars remarkably well.
What has changed is the scale. One framework, seven platforms, three knowledge representations, nine processing stages. The structural logic I described in a Melbourne conference room in 2019 turned out to be universal. The Three Pillars of SEO became Understandability, Credibility, Deliverability. The framework outgrew its original context, and the discipline outgrew its original name.
That’s the trajectory. And it’s still accelerating.
