Keyword Clustering and Tagging Written by Ashraf on Jan. 18, 2023 in Semantic SEO. Last update on Feb. 9, 2023. Don't forget to share this post Cluster Keyword Clustering is a practice search engine optimization (SEO) professionals use to segment target search terms into groups (clusters) to optimize content for search engines. These keywords are typically chosen based on their relevance to the topic and their intent and search volume, and they are often used in the headlines, subheadings, and body text of a webpage to improve its visibility in search engine results. The goal of using keyword clusters is to improve the relevance and authority of a webpage for specific search queries. Keyword Tagging is the process of assigning keywords or phrases to a piece of content, such as a webpage, blog post, or product listing, in order to help improve its visibility in search engine results. These tags are used to describe the content and provide context for search engines. Keyword clustering and tagging are both techniques used to optimize website content for search engines. They are related but serve different purposes. Keyword tagging is often used in conjunction with keyword clustering, as the KW clusters can be used to identify the main keywords and phrases that should be tagged. keyword clustering and tagging work well with semantic modeling and topical mapping. These techniques are often used together to level up content strategy and maximize search engine optimization. When used together, semantic modeling and topical mapping can help to increase your semantic model quality, which in turn can improve the accuracy of keyword clustering and tagging. How to do keyword clustering? The process of grouping keywords into clusters does not have a one-size-fits-all approach, as the best method may vary depending on the specific website or industry. It is important to consider different options and potentially create a unique approach that works best for your needs. Nevertheless, There are several types of keyword clusters, Some standard methods for clustering keywords include Brand Based Keyword Clusters This type of cluster includes keywords related to a specific brand, company, or product. These keywords can include the brand name, product name, and other terms related to the company. here's an example of a brand-specific keyword clusters for a pet shop that sells a specific brand of pet food: Brand name: "Lucky" Pet Shop. Brand-related terms: "Lucky pet food", "Lucky Diet food", "Lucky dog food". Brand-related phrases: "Lucky Diet dog food", "Lucky Diet cat food", "Lucky Diet pet food reviews". Brand-related synonyms: "Lucky food Plan", "Lucky pet nutrition", "Lucky pet food". Product Based Keyword Clusters These keyword clusters can include the product or service name, as well as related terms and phrases. here's an example of a product-specific keyword cluster for a pet shop that sells dog food: Product name: "Organic dog food". Product-related terms: "natural dog food", "grain-free dog food", "holistic dog food". Product-related phrases: "best organic dog food", "organic dog food brands", "organic dog food ingredients". Product-related synonyms: "natural dog food", "healthy dog food", " premium dog food". Topic Based Keyword Clusters These keyword clusters can include terms related to the topic or industry, as well as related phrases and synonyms. example of a topic-specific keyword cluster: Topic name: "pet supplies". Topic-related terms: "dog food", "cat toys", "pet grooming", “pet collars” “pet coats”. Topic-related phrases: "best pet products", "pet accessories", "pet health". Topic-related synonyms: "animal supplies", "pet products", "pet care". Location Based Keyword Clusters These keyword clusters can include the location name, as well as related terms and phrases. here's an example of a location-specific keyword cluster for a pet shop located in Chicago Location name: "Chicago". Location-related terms: "Windy City", "Chi-Town", "Chicago pet store". Location-related phrases: "pet supplies in Chicago", "best pet stores in Chicago", "Chicago pet grooming". Location-related synonyms: "pet shops in Chicago", "Chicago animal supplies", "Chi-Town dog products. Semantic Based Keyword Clusters These clusters are groups of keywords that are closely related in meaning, rather than just being closely related in terms of their spelling or phrasing. These clusters are created by identifying the main topic or theme of a piece of content, and then identifying keywords and phrases that are closely related to that topic. here's an example of a semantic keyword cluster for a pet shop that focuses on providing information about pet care Main topic: "pet care". Semantic keywords: "pet grooming", "pet nutrition", "pet behavior", "pet health", "pet training". Semantic phrases: "how to groom your pet", "best pet food for dogs and cats", "how to train your dog or cat", "common pet health issues", "how to improve pet behavior". Semantic synonyms: "pet hygiene", "pet feeding", "pet well-being", "pet education". Entity Based Keyword Clusters An entity-based keyword structure is a way of organizing and grouping keywords around specific entities or concepts. These entities can be products, services, people, places, or anything else that is relevant to the content of a website. By grouping keywords around specific entities, it can help search engines understand the context of the content, and make it more likely to appear in relevant search results. Here is an example of an entity-based keyword cluster for a pet shop that specializes in selling dog food: Entity: "dog breeds", "dog food ingredients", "dog nutrition". Entity-related keywords: "Golden Retriever", "German Shepherd", "chicken meal", "brown rice", "protein". Entities-related phrases: "best dog food for Golden Retrievers", "dog breeds that need high-protein diets", "ingredients to avoid in dog food". Entities-related synonyms: "canine breeds", "dog diet", "dog food components". More types of Keyword Clusters that you can try on your own SERP-Based (Top 10) Keyword Clusters Compared to lemma-based keyword grouping, SERP-based keyword clustering produces groups of keywords that might reveal no morphological matches, but will have matches in the search results. It allows search engine professionals getting a keyword structure close to what a search engine dictates. You can try this method using Google search results. Lemma Based Keyword Clusters Lemma is a base or dictionary form of a word (without inflectional endings). In linguistics, lemmatization is a process of grouping together the different inflected forms of a word so they can be analyzed as a single item. The most effective keyword cluster techniques will typically include a combination of different types of keywords, including primary keywords, secondary keywords, and long-tail phrases and the tool I found and recommend for serving different purposes for KW clusters is chatGPT. How do you tag keywords? Keyword tagging can be done by adding keywords to the meta tags, HTML code, images, videos, audio files, social media posts, and structured data. Here is how it's done: HTML-based keyword tags Keyword tagging using HTML involves using specific HTML tags to help search engines understand the structure and content of a webpage. Here are a few examples of how to use HTML to tag keywords: Headings Use the H1, H2, H3, etc. tags to create headings and subheadings on your webpage: <h1>Lucky Pet - Quality Pet Supplies</h1> Meta tags Use the "meta" tag to include keywords in the head of your HTML document For example: <meta name="keywords" content="pet shop, pet supplies, dog food, cat food"> <meta name="Description" content="Lucky’s pet shop for pet supplies, dog food and cat food"> Note: According to Google, meta keywords is deprecated Alt tags Use the "alt" tag to describe images on your webpage. For example: <img src="dog.jpg" alt="A golden retriever puppy playing with a toy"> Anchor tags Use the "a" tag to create links on your webpage. For example: <a href="https://www.luckypet.com/dog-food" title=”healthy dog food”>Quality dog food</a> It's important to note that overusing these tags or adding keywords that don't match the content of the page can be considered as keyword stuffing, which can be penalized by search engines. Media-Based Keyword Tags Keyword tagging can be done in images, videos, and audio files by including keywords in the file name, title, alt_tag, and caption. It can also be done in social media posts by adding keywords in the post, hashtags, and bio. When done correctly, keyword tagging can help search engines understand the topic and context of the content, and make it more likely to appear in relevant search results. While most SEO professionals know the methods above, here is a new way on how to tag your keywords using structured data. Schema markup (structured data) based keyword tags To tag your keywords using structured data, you can first select the appropriate schema type. Once selected, you can then establish a relationship between your entity and the keyword using the defined term type Within the defined term, you can add your target keyword, a relevant description, and sameAs linking to a high-authority webpage that further explains the keyword. This approach can be easily created using Schemantra, it allows search engines to understand the context and relevance of your keywords, making your content more likely to appear in relevant search results. Here is a JSON-LD schema code example for a web page targetting the keywords “dog food”, “cat food” and how its done: <script type="application/ld+json" class="schemantra.com"> { "@context": "https://schema.org", "@type": "WebPage", "@id": "#home", "name": "Lucky's Pet Shop", "keywords": [ { "@context": "https://schema.org", "@type": "DefinedTerm", "@id": "#dog", "name": "Dog Food", "description": "A food specifically formulated and intended for consumption by dogs", "sameAs": "https://en.wikipedia.org/wiki/Dog_food" }, { "@context": "https://schema.org", "@type": "DefinedTerm", "@id": "#cat", "name": "Cat Food", "description": "Cat food is food for consumption by cats", "sameAs": "https://en.wikipedia.org/wiki/Cat_food" } ] } </script> To create the code above Sign in to Schemantra. In the Dashboard click “Create New” Look for the type WebPage. In the “Create Properties Page” fill in the name and @id for the WebPage. Click “Save and Add Subschema”. In the Add subschema page Look for the relation “Keywords” and click on the DefinedTerm. In the DefinedTerm Page add your keyword, description and url of high authority page. Click save. In the Dashboard click on the WebPage schema again. A snippet will pop up, click on the plus (+) sign. Add another DefinedTerm. Conclusion In summary, keyword clustering and tagging are proper SEO techniques used with semantic modeling and topical mapping as they allow search engines to identify relevant keywords, understand search intent, understand content and discover new keywords resulting in improved SEO campaigns, increased website traffic and more conversions. keyword clustering and tagging are powerful tools that can be used to gain a competitive edge in SEO and help businesses to achieve their online marketing goals.