In the last two years, we have seen a tremendous increase in the number of web applications that put a focus on the meaning of content. Typically, these types of applications allow the user to search for content that is related to an interest, theme, or hobby – a practice that was initially popularized by Pinterest . In fact, according to HubSpot Blogs research, 66% of consumers have used an online platform to “research something they’re interested in, find products or services they might like, or look for a vacation spot.’”
These types of applications generally aim to provide the user with the ability to explore content based on a pre-selected topic or interest. In the case of Pinterest, this could be fashion, food, design, travel, or anything else.
Despite the growth of this trend, many companies have struggled to define [SEO] how to rank content within their applications. Because semantic search is becoming such a prevalent concept, this has led to a substantial rise in the demand for custom SEO companies. When it comes to SEO, content is typically associated with keywords and page titles. However, in a semantic web application, content is often associated with concepts and phrases that have meaning beyond the words that are used to describe it.
When you add a semantic twist to the traditional SEO model, you start to see a problem. How do I find relevant content when none of the words that I use to describe it are actually found in its text?
Thankfully, there is a technical solution to this problem that is known as “core clustering.” Core clustering is a way of structuring content so that it is easy to find relevant text should you type in a keyword or search phrase. Once you have core clustered your content, you can easily implement a semantic search algorithm that will help search engines like Google find your content even when none of the terms that you use to describe it are present in its text.
Let’s take a look at how this technical solution works in practice.
How Does It Work?
The basic idea behind core clustering is to structure your content in such a way that it can be easily understood and connected to relevant external data. For example, if I were to search for “luxury shoes”, I would expect to see a list of blog posts that are associated with that search term. But if I were to enter the same search query into Pinterest, the platform would understand that my interest is “shoes” and would offer a number of luxury brands and styles that I can explore based on my interests.
When you core cluster your content in this way, it becomes possible to implement a semantic search algorithm. The basic idea behind a semantic search algorithm is to interpret the words that you use to describe your content as queries and to connect that content to external data. For example, suppose that I were to search for “luxury shoes”, a semantic search engine would understand that I meant to search for a specific pair of shoes, not just “shoes” in general. It would then connect my search query to a list of relevant blog posts and companies that it finds using a sophisticated matchmaking algorithm.
Why Should You Try It?
One of the problems with traditional search engines is that they are not configured to understand the meaning behind your keywords and phrases. Because they are focused on the words themselves, they will typically return a number of unconnected results that have very little to do with what you were actually looking for. For example, if I were to search for “luxury shoes”, I would expect to see a number of unrelated results such as “shoe exhibitions”, “retro shoes”, and “shoes and jewelry” coupled with a few brands like Gucci and Jimmy Choo. If you have a look at the screenshot above, you will see a number of completely irrelevant results that the search engine returned for my query. This is why most SEO experts will tell you to avoid using keywords in your content’s text. Instead, you should incorporate them into the title and into the metadata that you add to your content.
But in the real world, we often don’t have the luxury of crafting an amazing title and a unique set of keywords for every piece of content. That is why core clustering is such a useful tool. By structuring your content in a way that is easily searchable, you can provide Google and other search engines with the right information even when you don’t use the keywords that they are looking for. It is a technical solution to the problem of “content overload” that many traditional search engines suffer from.
An Evolving Trend
This is not a new problem by any means. In fact, Google has been aware of the “semantic gap” for a long time. Essentially, the issue is that although they have advanced significantly since their inception, most modern day search engines are still not configured to understand the content that they are retrieving. This problem is exacerbated by the sheer volume of content that we have in today’s society. In the last two years, we have seen a massive increase in the number of blogs, websites, and articles that are published on a daily basis. Many of these publications are geared towards informing the reader about a particular subject matter, while others are just designed to increase the platform’s page views.
Even if you are just providing your readers with regular content, you are still responsible for ensuring that it is easily searchable. By using semantic clustering, you can provide the words in your content with meaning and let the search engines do the rest.
To give you an idea of how this technical solution can benefit your business, here are a few important points to keep in mind:
Attracting The Right Audience
One of the main challenges that startups and small businesses face is attracting the right audience. In today’s world, content is everywhere, and it is difficult to ensure that your content is being discovered by the right people. While social media platforms like Twitter and Facebook allow your content to be seen by a massive audience, they are not always the best tool for connecting with potential customers. If you want to attract the right people to your business, you should consider exploring the world of core clustering. Even if you have only a handful of blog posts, you can use this technical solution to structure your content and allow the search engines to draw in the right audience for your business.
As mentioned above, many companies have had to struggle with the problem of content overload. The sheer volume of articles and blog posts published on a regular basis has made it difficult for traditional search engines to keep up. Because of this, they have had to evolve to fit this new reality. But with the development of semantic search, it is now possible to have a much more meaningful interaction with search engines. Even if you do not use any keywords or phrases in your content’s text, you can still ensure that your content is easily found based on the topics that you choose to cover. This is because every piece of content that you create will have an associated “meaning” based on the concepts and themes that you choose to cover.
Boost Your Rankings In The Right Way
Another problem that many businesses face is how to properly optimize their SEO strategy for the best possible results. The fact that SEO is an “evolving” field means that the techniques that you use to rank content will change over time. But because there is no single “perfect” recipe for SEO, this can make it quite difficult to determine the “best” approach for your own business.
Luckily, with the development of semantic search, it is now possible to have a much more defined relationship with your search engine. You can incorporate keywords and phrases into the content itself while also defining the “conceptual meaning” of each piece of written material that you create. This will then allow you to track the success of your SEO strategy on a much more granular level.
Considering all of the above, it is quite clear that semantic clustering is an “evolving” trend that is here to stay. Even if you do not currently use any of the above-mentioned tools, you should consider taking the time to understand their purpose and how they can help your business. Just as the development of the internet led to the rise of new forms of media, the rise of semantic search will lead to many changes in the way that we interact with content.
What is an example of semantic clustering?
Semantic clustering is an SEO technique used to group together related keywords and topics on a website. An example of semantic clustering would be a website that sells outdoor gear and uses multiple keywords and topics related to camping, hiking, and backpacking.
Here's an example of how semantic clustering might work for a camping website:
Cluster 1: Camping Gear
- Sleeping bags
- Camp stoves
- Camp chairs
Cluster 2: Hiking Gear
- Hiking boots
- Trekking poles
- GPS devices
- Water bottles
Cluster 3: Backpacking Gear
- Lightweight tents
- Ultralight sleeping bags
- Camping cookware
- Hydration systems
- Portable water filters
By grouping related keywords and topics together in a semantic cluster, the website can create a more organized and user-friendly structure that is also more optimized for search engines. This can help users find what they are looking for more easily and improve the website's search engine rankings for relevant keywords.
What are the types of semantics?
Semantics is the study of meaning in language. There are several types of semantics, including:
1. Lexical semantics: This type of semantics focuses on the meaning of individual words and how they are used in context.
2. Compositional semantics: This type of semantics looks at how words are combined to create meaning in larger phrases and sentences.
3. Distributional semantics: This type of semantics looks at the statistical patterns of word use in language to understand their meaning.
4. Cognitive semantics: This type of semantics focuses on how people understand and conceptualize meaning in language based on their own experiences and knowledge.
5. Formal semantics: This type of semantics uses logical and mathematical models to analyze and represent meaning in language.
6. Pragmatics: This type of semantics looks at how context, social cues, and other non-linguistic factors influence the meaning of language.
These different types of semantics can be used together to provide a more complete understanding of the meaning of language in different contexts.