How Semantic Search Works & How to Future-Proof Your Content

Are you still stuffing keywords into your content but getting zero traction in search results?

Semantic search has completely transformed search engine optimization (SEO). If you don’t adapt, you’ll waste resources and lose ground to the competition.

I’ll break down how semantic search works, why it matters, and how to optimize your content for semantic meaning and search intent.

Key Takeaways

• If you want customers to find your content using search engines like Google and Amazon, then you have to understand semantic search.
• Longer conversational searches are growing at 1.5x the rate of short queries, and content must adapt to semantic search to rank.
• Use tactics like topic clusters, structured data, and internal linking to establish semantic relationships and build topical authority.

What Is Semantic Search?

Semantic search is a method that search engines use to analyze the meaning of a query and provide more relevant search results.

It uses artificial intelligence (AI) technologies like natural language processing (NLP) and machine learning (ML) to understand the meaning of words and phrases and the intent behind a search query.

It goes beyond traditional search technology, which uses exact keyword matches. Instead, a semantic search engine considers aspects like:

• Relationships between the words in the search query
• Location of the searcher, especially for queries with local results
• Previous searches, which offer more insight into the contextual meaning

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The result? Content that aligns with the context of the query and the user’s search intent, giving the searcher the information they want.

What’s the Difference Between Keyword Search vs Semantic Search?

Keyword search matches queries with keywords in databases or documents without taking the semantic meaning behind the search into account. Also called lexical search or text search, it’s a simpler method that’s faster to implement, but it tends to provide less relevant search results.

Semantic search goes beyond keywords to respond to the meaning and intent behind a user’s search query. It uses vector search to understand similarities and relationships, allowing for more conversational searches and tends to provide more relevant search results.

Is Google a Semantic Search Engine?

Google is one of many search engines that rely on semantic understanding. Over the course of several product launches and algorithm updates, Google has transitioned from a traditional to a semantic search experience.

• 2012: Knowledge Graph launched as Google’s database of information about entities, including people, places, and things.
• 2013: Hummingbird was a major Google algorithm update that shifted from matching keywords to using natural language to match topics.
• 2015: RankBrain was Google’s first AI-driven deep learning system designed to analyze how words connect to concepts — allowing the search engine to surface more relevant information.
• 2018: BERT, an NLP pre-training technique, allowed the search engine to understand more complex, conversational queries and provide more accurate search results.
• 2021: MUM, a generative AI tool, gives Google the power to go beyond retrieving information by synthesizing answers and generating responses.

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How Does Semantic Search Work?

Semantic search uses four core technologies to retrieve and generate information:

• NLP enables semantic search engines to interpret the meaning and intent of user queries.
• ML allows these search engines to learn from expansive datasets and improve search relevance.
• Knowledge graphs helps understand how entities are related and how concepts are connected.
• Vector embeddings turn words into mathematical representations, which help these search engines measure semantic similarity and access relevant content.

Why Semantic Search Matters

Semantic search is important for both users (your potential customers) and information providers (your business).

Increases Search Relevance

Across the board, searches are becoming more complex. In the 2024 Google Marketing Live Keynote, Philipp Schindler stated that searches containing five or more words have increased 1.5 times faster than shorter queries.

Semantic search engines can not only understand these increasingly complex queries but also provide relevant results that respond to the user’s intent. This helps searchers access the information they need more efficiently.

Improves the User Experience

We’ve all been there before. You type a simple query into a search engine, but it doesn’t give you the results you’re looking for. So you try asking the question another way. And then another way.

No one wants to try the same search five different times to get the answers they want. Since semantic search engines can deliver relevant results on the first try, they’re great at providing a good user experience.

Boosts Engagement and Conversions

The quicker semantic search offers relevant results, the faster users can view relevant answers, products, or webpages. This can lead to clicks, which can turn into conversions.

It’s the ideal scenario for businesses. Your content appears in relevant search results, driving engagement and sales for your business.

Examples of Semantic Search

There are tons of use cases for semantic search, including search engines, ecommerce sites, and enterprise search. Let me show you a few examples of how semantic search delivers more relevant search results.

Google Search

Say you’re shopping for a new pair of running shoes. If you type “running shoes” into a traditional search engine, it would suggest pages that contain those keywords without considering the larger context.

In contrast, a semantic search engine like Google might detect that you’re located in Seattle. And that you’ve been researching men’s footwear. In that case, it would suggest some high-quality lists of top running shoes and business listings for stores where you can buy them locally.

Google AI Overviews

Suppose you’re in the market for a pair of running shoes for a more specific scenario. If you type a longer query into the Google search bar, there’s a good chance the results will include an AI overview.

Instead of simply providing links, this AI search result answers your question. The overview references specific products and features and points you to helpful resources.

Amazon Search

Say you’re shopping for a planner to organize your workday.

If you search for “best planner for work” on Amazon search bar, the algorithm will understand that you’re looking for features like time blocking, hourly scheduling, and to-do lists. And if you’ve already viewed or purchased relevant products, the results will take that context into account, too.

Instacart Search

Suppose you want to stock up on snacks — but you want to keep the choices relatively healthy.

If you search for “healthy snacks” on Instacart, the search engine won’t necessarily retrieve items with “healthy” in the description. Instead, it’ll understand that you’re shopping for items with attributes like low sodium or a lack of artificial flavors.

7 Best Practices to Optimize for Semantic Search

Now that you know how semantic search works and why it’s so important for both your business and your potential customers, you need to know how to incorporate it into your SEO strategy. Here are my tried-and-true tips to leverage semantic SEO and future-proof your content.

1. Opt for Natural Language Over Keyword Stuffing

If you haven’t already, stop stuffing keywords into your content. This outdated practice involves adding keywords an excessive number of times in website content, including in titles and meta descriptions.

It creates a poor experience for website visitors. And because semantic search focuses on topics over keywords, this practice is unnecessary.

Instead, create content that sounds human. Write how your audience speaks, using conversational language.

Continue using relevant keywords in your content. But don’t shy away from using natural language versions.

For example, you don’t have to use awkward keywords like “best running shoes first marathon.” Instead, you can write “best running shoes for your first marathon.”

2. Incorporate Semantically Related Terms

Semantic search seeks to understand the broader topic of your page, not just the primary keyword.

To guide semantic search engines, incorporate related keywords, also known as latent semantic indexing (LSI) terms.

For example, if you’re writing about running shoes, you’ll likely want to include semantically related terms like:

• Footwear types, including sneakers and jogging shoes
• Shoe features like cushioning and breathability
• Sports and activities like running and marathons
• Brands like Brooks and Hoka

3. Create Topic Clusters and Pillar Pages

Keywords are still important for making your content more visible in search. But targeting a single keyword isn’t going to cut it.

Instead, you have to demonstrate your breadth of experience.

Organize your site around pillar pages and topic clusters:

• Pillar pages are comprehensive pages that cover all major aspects of a topic. Like my guide on Google Ads campaign management. It tells you everything you need to get started, but it doesn’t go into subtopics in depth.
• Topic clusters are groups of content pieces that cover a subject in depth. The pillar page typically links out to these pages, giving readers a complete set of resources on a topic. Like my articles on Google Ads quality score and keyword match types, which build on the Google Ads pillar page.

4. Build Out Your Internal Linking Strategy

Internal links are helpful for a couple reasons. They help website visitors find more relevant content on the topics they care about.

They also help establish semantic relationships. This enables search engines to understand the connections between your content — and your authority on the topic.

For example, my pillar post about Google Ads campaign management has tons of internal links (in orange) that point readers toward more in-depth resources.

5. Understand and Speak to User Intent

To improve semantic ranking for your content, you need to know what your target audience is searching for and why. In other words, you need to understand the intent behind their search.

Are they looking for a beginner-level guide to a topic? A hot take on an industry trend? Or an in-depth comparison between your solution and your top five competitors?

You don’t necessarily have to guess. SEO tools reveal search intent for keywords, breaking it into five main types:

• Informational: The user wants to learn more about a topic or answer a question.
• Commercial: The user is researching options as they consider a decision.
• Transactional: The user is ready to complete a specific action like making a purchase.
• Navigational: The user is searching for a specific website or page.
• Local: The user is seeking products or services in a certain area.

For example, people searching for “running shoes” have a local and a commercial intent. Which aligns with the search results I highlighted above.

6. Implement Structured Data

Structured data isn’t something users see on your website. Instead, it’s a standardized framework for annotating elements of your website with code so search engines can understand it better.

You can use schema markup for elements like FAQs, how-to content, reviews, videos, recipes, and much more.

It can prompt search results to show rich snippets. Like this chocolate chip cookie recipe result, which shows star ratings and recipe details.

Even when it doesn’t trigger rich snippets, it still provides semantic search engines with valuable information about your content.

7. Think Beyond Your Website: Use Social Media

To build a semantic search strategy, think beyond your website. Incorporate YouTube and other social media platforms into your approach to create additional opportunities to give searchers the information they want.

For example, my digital marketing trends YouTube video is a top video result for “digital marketing trends.”

It also appears in the “What people are saying” carousel, which features results from social media and forums.

It’s no coincidence this video already has a ton of traction less than a day after publishing. I optimized the video script, title, and description for this topic.

Next Steps to Get Started with Semantic Search

If you haven’t already implemented semantic search in your SEO strategy, now is the time to start. You can use semantic search to optimize blog posts, landing pages, and even social media content.

Use my best practices to guide your approach. In addition to keyword rankings and search impressions, pay attention to metrics like click-through rates (CTRs) and conversions — and watch your results drive business.