SAW: Entity-Based SEO Must Replace Keyword Research, Why and How

5 minutes; 2 minutes for the Overview and bold text.

Overview

This post concludes a 6-part series about LLM tech and, increasingly through the series, application to business and especially SEO and CRO (conversion rate optimization). This final post summarizes a staggering quantity of DISC’s in-house research aimed at battle-testing the practical guide below. That research is available to DISC’s clients upon request. 

Today, Google and other search engines no longer rely primarily on keyword frequency. Instead, they interpret content through Entities—distinct people, places, concepts, and things—and their relationships, stored in Google’s Knowledge Graph and processed through advanced AI models like MUM (Multitask Unified Model). This fundamental shift means that traditional keyword research tools are, in most cases, obsolete wastes of time.

This post explains:

1. Why Entity-based SEO must replace keyword-centric SEO;
2. How to structure websites for long-term success using Entity-Driven SEO Architecture & Writing (SAW).

Why Most Keyword Research Tools Fail Since ~2022

Since the late 1990s, SEO professionals relied on keyword research tools to determine search volume, competition levels, content gaps, etc. These tools, however, suffer from critical flaws in today’s search environment:

1. They Focus on Volatile Metrics, Not Enduring Structure

• Search volume fluctuates due to seasonal trends, industry changes, or viral spikes.
• Competitor gap analysis is misleading because it only reflects current rankings, not Google’s long-term evaluation of authoritative content.
• Therefore, such keyword research invests time and money into tactics that won’t reflect a firm’s enduring SEO Architecture & Writing (SAW), wasting money and requiring frequent, costly updates (which many tool suites and firms want you to do for their, not your, benefit).  

2. They Fail to Account for Google’s Entity-Based Indexing

• Google’s Knowledge Graph links concepts based on semantic relationships, not keyword matching..
• A website’s ability to rank is determined by how well it aligns with known Entities and their connections.
• Keyword tools don’t map these relationships and instead suggest disjointed keyword clusters that fail to reflect how Google structures knowledge.

3. They Misalign Search Intent and Buyer Journeys

• Modern SEO is not just about ranking for words—it’s about serving the right intent at the right time.
• Traditional Keyword research tools, even if they distinguish informational, navigational, and transactional intent, do so under a topic (Entity) hierarchy that is out of kilter with the enduring real world of your firm.
• This can lead businesses to create content that attracts traffic temporarily at best and strays from optimum conversion paths.

Example: A law firm might create separate blog posts for “best small business lawyer” and “small business contract help,” based on keyword research tools. However, Google likely recognizes both as part of the broader Entity of ‘Business Law’, meaning one well-structured page is far more effective.

What Works Now: Entity-Based SEO

Rather than chasing volatile keyword trends, businesses should build their websites around the real-world structure of their industry. This means:

1. Identifying core market Entities related to the business.
2. Structuring content to reflect Entity relationships rather than isolated keywords.
3. Mapping buyer intent to the Entity-driven conversion funnel.

The result? A website architecture that mirrors Google’s understanding of the industry, leading to sustained rankings, improved conversions, and more efficient SEO investment.

Step 1: Build an Entity-Driven Site Architecture

Instead of organizing content around search volume, structure it around real-world topics and how they connect.

Example: A cybersecurity firm might traditionally create pages based on keyword research like:

• “Best antivirus software”
• “Endpoint security for businesses”
• “How to prevent phishing attacks”

In an Entity-based model, the site is structured around recognized topics like:

• Cybersecurity Solutions (Entity: Cybersecurity)
  • Antivirus Software (Sub-Entity)
  • Endpoint Security (Sub-Entity)
  • Phishing Protection (Sub-Entity)

This mirrors how Google categorizes knowledge, making the website more authoritative, a key ranking factor.

Step 2: Align Content with Buyer Intent

Once the core Entity or “SAW” structure is established, content should follow a logical conversion flow.

• Informational intent: Blog posts, educational guides.
• Navigational intent: Case studies, service comparison pages.
• Transactional intent: Product pages, demo requests.

Example: Instead of isolated keyword-driven content, a cybersecurity firm would structure content as follows:

1. Top-funnel: “What is endpoint security?” → Informational (Blog, Guides)
2. Mid-funnel: “Endpoint security vs. traditional antivirus” → Navigational (Comparison Pages)
3. Bottom-funnel: “Get a free endpoint security assessment” → Transactional (Product Pages, Demos)

By structuring content to reflect how users move through an Entity-structured decision process, businesses improve conversion rates while strengthening their Entity authority in Google’s eyes. And they build enduring SEO that does not need ongoing time and cost to tune.

Step 3: Validate Using Google’s Own Tools

Since Google’s Knowledge Graph is proprietary, businesses should validate their Entity structure using:

• Google Knowledge Graph Search API (to see if their brand is recognized as an Entity).
• SERP Analysis (checking related searches, Knowledge Panels, and People Also Ask to refine topics).
• Schema Markup (to explicitly define their Entity relationships for Google).

The Pragmatic Approach: Using Brand Briefs as an Entity Proxy

For smaller-budget businesses, full-scale Entity research may not be feasible. However, a strong brand strategy already defines the core market position and conversion flow—which means it can serve as a proxy for Entity-based SEO.

A well-structured brand brief naturally answers the key questions of Entity-based SEO:

• What is the business’s primary market category? (Core Entity)
• What specific problems does it solve? (Sub-Entities)
• How do customers move from awareness to purchase? (Intent flow)

After ensuring technical SEO is sound, an SEO firm can use a brand strategist’s insights to structure content in a way that aligns both with Google’s Entity model and with traditional marketing fundamentals.

Example: A business consulting firm’s brand positioning document states:

• “We help mid-sized manufacturers optimize supply chains.”
• That naturally translates into an Entity-based structure:
  • Manufacturing Consulting (Core Entity)
    • Supply Chain Optimization (Sub-Entity)
    • Lean Manufacturing Strategies (Sub-Entity)
    • Factory Workflow Automation (Sub-Entity)

Rather than spending resources on transitory keyword analysis, the firm structures its content to reflect real-world industry relationships, ensuring long-term SEO success.

Final Takeaway: Now SEO is Entity-Based and Long-Enduring

Since about 2022, traditional intensive keyword research has become obsolete as Google uses an Entity-based ranking model. Businesses should stop chasing short-term keyword fluctuations and instead:

1. Structure their websites based on core market entities.
2. Map content to logical buyer intent and conversion paths.
3. Use traditional brand strategy as a cost-effective proxy for Entity research.

By aligning SEO with real-world industry structures rather than ephemeral keyword trends, businesses can build long-enduring visibility—and, most importantly, Make Websites Make Money.

Sources, Credits, Future Posts:

Whereas I wrote the prior 5 posts in this LLM series, this post relied largely on ChatGPT’s summary of DISC’s extensive research. That research included use of ChatGPT’s superb new Deep Research module, which I and other researchers have found greatly superior to Gemini’s.

The 6-part series starting in September 2023 and concluding with this post offers to marketing managers, CEOs, and fellow SEO pros a complete practical understanding of LLM tech. Future posts will address specific sub-topics in profitable LLM integrations. Search engines have always been essentially large language models, so disciplined SEO pros are uniquely suited to guide firms in LLM adoption. I look forward to our journeys together in this brave new world.