How to Focus on Topics (Not Keywords) in Your SEO Strategy

“Keywords are dead. Topics are the new keywords.” You’ve probably heard this at least a dozen times from LinkedIn gurus with bold opinions and fuzzy logic that essentially amounts to “write more content about related things” (basically, pillars and clusters 2.0).

The truth is far less dramatic.

Keywords aren’t dead, but optimising for them one at a time is like trying to light up a galaxy one star at a time. The real shift is a change in scale and mindset: from thinking about individual queries to the whole conceptual space around them.

Here’s what that shift actually looks like and how to help search engines associate your brand with a whole subject area, not just a handful of queries.

Science News

This isn’t just a casual analogy. Modern search engines and AI systems actually map meaning so that related concepts end up close together, while distant ones are far apart.

They operate on “semantic spaces”. That is, spaces where they can discover meaning in how things relate to each other.

Keywords exist in that space as a core data set used by search systems (traditional and AI). But they’re not alone. They’re also mapped alongside documents (like your webpages), multimedia content, and more.

The technical term for all these objects within semantic search spaces is “vector embeddings”.

Example of vectors and embeddings in AI models

Source: weaviate.io

Brands exist in that same space, and search engines can strengthen their association with topics through knowledge graphs (databases of real-world entities, including brands, people, places, and concepts, along with the relationships between them).

These associations influence which brands surface across a whole topic area, not just for the specific queries they target.

keyword research and topic mapping handle this by adding individual keywords to a list one at a time and then clustering them to form a content plan.

This works well at small scales but becomes unwieldy, and eventually impossible, as your topic grows. The three-tier approach below is the next step: a more systematic way to think about topic territory, so your keyword research scales with your ambitions.

semantic SEO exercise and just looking at keyword volume, you’ll be optimizing for totally unrelated things and diluting your topical authority significantly.

query fan-out.

Sometimes, it’s not the topics themselves that are ever-growing, but a brand’s reach across multiple topics. For example, authority sites like Forbes or Hubspot cover many topical domains in their content. Or marketplaces like Amazon, Etsy, or Airbnb unlock new keyword opportunities as new products get added.

Coming back to our space analogy, these topics are like galaxies.

Image of a galaxy from NASA

Source: NASA

A small keyword list for topics like this is in the hundreds of thousands. Though in most cases, you’d be looking at covering millions of keywords in your content and SEO strategy.

At this scale, your keyword universe is vast, ever-growing, and impossible to map manually.

New queries emerge constantly. So the focus is not on mapping every keyword, but understanding the structure (patterns and clusters) that emerges from your keyword data. Then you can focus on building content that belongs within it at a structural level.

For example, Healthline currently shows up for:

  • 4.2 million keywords on Google
  • 1.1 million queries in AI Overviews
  • 395,000 prompts on ChatGPT
  • 176,000 prompts on Perplexity
  • 49,900 prompts in Gemini
  • 40,400 prompts in Copilot

Healthline's organic SEO metrics in Ahrefs' dashboard

Millions of people search for health-related answers every day. They ask questions about symptoms, conditions, treatments, medications, and vague queries they use to try to self-diagnose.

Healthline’s visibility comes from understanding these patterns rather than manually targeting individual queries. It prioritizes structural topical coverage by building a resource that search engines recognize as an authoritative home for health questions across entire medical subject areas.

For instance, it has different content pillars for health, nutrition, fitness, common conditions, and more:

Analyzing Healthline's site structure in Ahrefs' Site Explorer

The content in each pillar follows a repeatable format that ensures adequate topic coverage, even if it doesn’t squeeze in every relevant keyword (as many SEOs try to do).

Example of topic coverage in a Healthline article

By structuring content this way, Healthline can create a single page for each relevant sub-topic. For instance, it’s page about magnesium glycinate shows up for:

  • 2,500 keywords on Google
  • 473 queries in AI Overviews
  • 279 prompts on ChatGPT
  • 200 prompts on Perplexity
  • 28 prompts in Gemini
  • 86 prompts in Copilot

Search visibility metrics of Healthline's article in Ahrefs Site Explorer

The page contains about 1,000 words of content (in the main body of the article). It is impossible to include all the keywords it ranks for in the article.

In contrast, Oreate AI optimizes content for specific keywords, leading to over 60 pages that contain magnesium glycinate in the URL, each one only ranking for a handful of keywords:

Oreate AI's site structure indicating over 60 pages about magnesium glycinate

In total, Oreate AI ranks for 266 magnesium glycinate keywords across 208 pages. 200 times Healthline’s content creation efforts for a tenth of the keywords (give or take).

Sure, there are other factors at play here (like brand authority and website age). Yet, this contrast reveals how topical authority actually works.

Healthline earns more visibility per page because it has earned its authority for health-related subjects. Visibility follows a brand’s topical authority, not the other way around.

You can do the same for each content piece you publish with Ahrefs’ AI Content Helper. It helps you select a specific intent to optimize for…

Ahrefs' AI Content Helper intent analysis

… and then breaks down all the relevant sections and topics you need to include in your content, scoring your topic coverage along the way.

Ahrefs' AI Content Helper topic gap analysis and recommendations

But when it comes to knowing what content you need to create to begin with, for expansive topics, traditional keyword-by-keyword research gives way to pattern recognition across large datasets. This is where AI tools and the Ahrefs MCP start to become genuinely powerful (which we’ll get to shortly).

Key insights

When to use this approach: Your topic is vast, your audience generates an endless stream of queries, and manual keyword research can’t keep pace with the scale.

What success looks like:

  • Coverage of the major sub-topics your audience cares about, not an exhaustive list of individual queries
  • Growing keyword breadth over time as new queries and search patterns emerge
  • Authority that compounds as your website becomes the authoritative home for all topics it covers

Where many go wrong: At this scale, trying to plan and track content keyword by keyword becomes counterproductive. The goal is to build the kind of structural coverage that earns authority across your whole keyword universe.

Brands that treat expansive topics like a bigger version of Tier 1 (just more pages, more keywords) miss the point entirely. Pattern recognition and topical architecture matter far more than any individual piece of content.

Site Explorer and checking out the Organic Keywords report:

Ahrefs' Organic Keywords report

This shows you what search engines already associate with your brand and the topics you’re closely connected to.

Then, layer in what you actually know about your business:

  • What are your product and service categories?
  • What pain points do your customers come to you with?
  • Where are competitors playing, and where are the gaps?
  • What questions do customers ask at each stage of their journey?

Asking these questions often surfaces gaps. For example, you might notice that search engines have misinterpreted the topics you want to be connected to, in which case you’ll need to work on disambiguation your brand.

For example, IDEO is a product design firm known for its human-centered design philosophy. It produces physical products but ranks for terms about digital product design:

Example of IDEO ranking for "digital product design agency" keyword in Ahrefs' Keywords Explorer

You might notice similar ambiguities for your brand. Or you might notice that search engines have yet to connect you to a core product category, in which case you’ll need to focus on closing the gap.

You can also use the following filters to define and pressure-test your topic boundaries before committing to them. These are excellent if you’re starting a new brand and don’t have existing performance data to work from:

  • Topic meaning: Does your topic have one clear interpretation or multiple? e.g. “product design” splits between UX/digital and physical/industrial. Half the keyword universe may belong to a different audience entirely
  • Intent alignment: Is the intent informational, commercial, or transactional? e.g. “phone cases” is almost entirely transactional as there’s little informational content you can rank for that will actually drive relevant traffic
  • Content format capabilities: Can you actually create the type of content that ranks for this? e.g. a local plumber can’t compete for keywords dominated by directory listings or comparison sites
  • Product/service scope: Does this topic connect to something you can deliver? e.g. a personal injury law firm covering general legal advice topics that attract people with problems they can’t solve
  • ICP relevance: Does it serve your ideal customer, or just any visitor? e.g. a B2B SaaS brand ranking for generic “what is a spreadsheet” queries with high traffic, zero conversion potential
  • Business potential: Is there real return on investment, conversion likelihood, or strategic value here? e.g. a luxury brand ranking for budget-focused keywords attracts browsers, not buyers

This exercise alone will save you months of effort on the wrong topics, and in this case, it also tells you exactly which tier you’re dealing with before you write a single word.

Step 2: Choose your optimization approach

Once you’ve defined your topic territory, the next decision is how to approach it. This comes down to two things: the complexity of your topic, and your brand’s goals for owning it.

That’s exactly what the three tiers above are designed to help you decide. Go back and identify which tier your topic belongs to, then follow the approach that fits.

To put it simply:

  • Tier 1 topics need thorough, complete coverage of a small, well-defined space. The goal is to reach the plateau of topic leadership and hold it.
  • Tier 2 topics need semantic clarity before content planning. Disambiguate intent first, then build content that speaks unambiguously to your specific audience.
  • Tier 3 topics need structural coverage and pattern recognition across a large dataset. This is where AI tools become genuinely useful.

For Tier 1, you can build a list within Ahrefs Keywords Explorer. Enter your main topic(s) into the search bar and check out the matching terms report to expand your keyword list:

Performing keyword research in Ahrefs' Keywords Explorer

Then select the keywords that align with what you do and build your keyword list.

Adding keywords to a list in Ahrefs' Keywords Explorer

You’ll often come across keywords you’re unsure about.

In these cases, click on the SERP dropdown to see what types of pages already rank. You can use the AI feature to identify the dominant intent they cover. You can also perform a manual check to see if the ranking pages are similar to what you can create for your website.

Expanding search results for a keyword in Ahrefs' Keywords Explorer

If you think you can create similar content to cover the keyword and its intent, add it to your list:

For Tier 2 and especially Tier 3 topics, the Ahrefs MCP, combined with Claude, can significantly accelerate your topic-mapping process.

You can export keyword data in bulk from Keywords Explorer in CSV format or use the Ahrefs API:

Exporting a keyword list in Ahrefs

Then, ask Claude (or your preferred LLM) to cluster it into semantic groups by intent and context. Our team has consistently achieved better results with Claude than with ChatGPT, but your mileage may vary. It all depends on the models, prompts, and workflows you’re using.

You can also use the Ahrefs MCP within your preferred LLM to identify gaps. These are terms related to your topic that aren’t on your list yet.

The Ahrefs MCP use cases guide and setup docs are the best places to start if you haven’t used it before.

Ahrefs' MCP guide

A few things that consistently improve results when prompting LLMs for keyword clustering and topic mapping:

  • Give specific examples of what a good cluster looks like for your niche
  • Let the LLM decide the number of clusters rather than forcing a fixed count
  • Exclude branded terms and years from the output
  • Focus on keywords of three or more words where possible, since shorter terms cluster too broadly
  • Expand one specific cluster at a time rather than asking for everything at once

With the MCP and API, you can build and manage keyword universes containing millions of keywords. You can also find the hidden structural patterns that semantic search engines use and build your content plan around those.

Once you’ve worked through your whole keyword list, start creating content. For smaller projects, you might do this manually with the help of content editors like AI Content Helper:

Using Ahrefs' AI COntent Helper as a Content Editor for SEO content creation

For larger websites, you may build these pages out programmatically. And if you’re using a headless CMS, you can build content models for common page types to help.

Step 3: Measure your topic coverage

Individual keyword rankings tell you how one star is performing. Topic coverage tells you how much of the solar system or galaxy you own.

Track progress using metrics that reflect the bigger picture, not just position tracking for individual queries. Ahrefs Brand Radar is built for exactly this. You can use it to monitor:

  • Query breadth: How many related queries and prompts are you visible for in AI search, and is that number growing?
  • Share of Voice: What percentage of total topic visibility does your brand own?
  • Coverage expansion: Are you capturing more of the topic space over time?

Ahrefs' Brand Radar overview

It is also a great tool for topic exploration. You can see exactly what topics semantic and AI search systems associate with your brand in the Topics report:

Ahrefs' Brand Radar Topics report

You could also search for your main topic (without your brand) and explore what sub-topics are included in it by AI systems:

Searching for only a topic in Ahrefs' Brand Radar

The goal isn’t to rank #1 for every keyword (even the biggest brands don’t achieve that).

Instead, aim to own the topic space that’s most relevant to your brand and be recognized as one of the most authoritative sources for it. Watch for growth in keyword breadth and Share of Voice, including AI Share of Voice, as answer engines become an increasingly important part of how people find information.

Final thoughts

Keywords aren’t going anywhere. But the way you use them needs to change.

Stop treating them as individual ranking targets and start treating them as coordinates and signals that collectively map the topic space your brand wants to lead. The goal is to be the most trusted, deeply connected source for the topics that matter most to your audience.

Topic optimisation turns keyword research from a list-building exercise into a long-term strategy for authority.

And in a search landscape increasingly shaped by AI, the brands that own their topic galaxy (not just a handful of stars within it) are the ones that will keep winning visibility.

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