A statistical measure of how important a keyword is in a document compared to a set of documents, used in semantic SEO.
Do you ever feel like your content should be ranking better, but Google just does not seem to know what it is truly about? I know that frustration of trying to prove your page is the expert resource, but you are struggling to find the right balance of words. I want to share a powerful concept that measures the true importance of every single word on your page. 📊
I am going to explain exactly What is Term Frequency-Inverse Document Frequency (TF-IDF)? and show you how to write content that speaks Google’s language of relevance. I will give you simple, actionable tips for balancing your keywords across every platform and industry. This strategic approach will make your pages the clear authority in your niche.
What is Term Frequency-Inverse Document Frequency (TF-IDF)?
Term Frequency-Inverse Document Frequency (TF-IDF) is an old but still relevant statistical measure that search engines use to determine how important a word is to a specific document within a collection. The Term Frequency (TF) part looks at how often a word appears in my document. The Inverse Document Frequency (IDF) part looks at how rare that word is across the entire web.
I use TF-IDF to understand which words truly define my page’s topic and set it apart from general content. A high TF-IDF score means the term is used frequently on my page and is rare across the web, signaling high relevance and unique topic focus. For example, the word “the” has a high TF but a very low IDF, so its overall score is low, meaning it is not important for defining my topic.
Impact of TF-IDF Across CMS Platforms
Since TF-IDF is all about content and not code, my focus across all platforms is on writing comprehensive, topically-rich copy.
WordPress
With WordPress, I optimize for TF-IDF by using plugins that analyze my content against competitors’ top-ranking pages for missing keywords and concepts. I ensure my articles are comprehensive, naturally including the important, less common terms. The ability to structure long-form content is key to naturally increasing the term frequency of my unique concepts.
Shopify
For my Shopify product pages, I boost the TF-IDF of my key terms by writing extremely detailed descriptions and FAQ sections. I use technical specifications and specific model numbers more often than generic words to increase my score. This precise language helps my products rank for niche buyer searches.
Wix
Wix users should focus on creating detailed content for their service pages and blog, making sure to include necessary, specific terminology. I avoid using vague language on my core pages and replace it with highly descriptive, relevant keywords that accurately define my offering. This makes the content clearer for search engines to classify.
Webflow
Webflow’s clean CMS allows me to structure my content perfectly, ensuring that the necessary unique terms are spread throughout the headings and body text. I can use the CMS to create fields for technical details, which naturally increases the frequency of my high-value terms. This organized approach aids in achieving a balanced TF-IDF score.
Custom CMS
With a custom CMS, I integrate tools that can measure the TF-IDF of a document before publication, comparing it against a benchmark. I guide writers to use the specialized vocabulary of the niche appropriately, without resorting to keyword stuffing. This data-driven approach ensures all my content is highly relevant.
TF-IDF Application in Different Industries
I use TF-IDF principles to define my authority using the most relevant and specific language in each sector.
Ecommerce
In e-commerce, I utilize TF-IDF by focusing on the unique attributes of a product, like using specific fabric blends, proprietary technology names, or model years frequently. I make sure my competitors’ core differentiating terms are covered in my product descriptions. This ensures my page is seen as uniquely relevant to the specific product.
Local Businesses
For local businesses, I increase TF-IDF by frequently using specific local landmarks, neighborhood names, and licensed terminology in my service pages. Instead of a general description, I use phrases like “licensed, insured HVAC repair serving the downtown historic district.” This unique local focus boosts my relevance.
SaaS (Software as a Service)
With SaaS, I recognize that my TF-IDF score is driven by technical concepts and specific feature terminology. I ensure that my documentation and features pages frequently use the precise vocabulary of my software and the underlying technology. This frequency signals deep expertise in a technical niche.
Blogs
For my blogs, I use TF-IDF to identify keywords that are essential to a topic but are often missed by competitors. I then weave these terms naturally into my headings and body text. This comprehensive use of related, rare terms is what makes my articles the authoritative resource.
Frequently Asked Questions
Is TF-IDF a direct Google ranking factor?
While Google does not use TF-IDF directly as a simple score, the underlying principles of frequency and document relevance are core to how all modern search engines function. It is a powerful concept to guide my content creation.
What does a high TF-IDF score mean for a term?
A high TF-IDF score means the term is highly specific to my document and is relatively uncommon across the broader web. This signals to Google that the term is very important for defining my page’s unique topic.
Is it possible to keyword stuff using TF-IDF?
Yes, if I use a unique term too often, I can still keyword stuff and hurt my content’s readability. I must use the unique terms naturally, focusing on providing value to the reader, not just pleasing the algorithm.
How does TF-IDF relate to term entropy?
TF-IDF is related to Term Entropy because the Inverse Document Frequency (IDF) component measures the term’s surprise factor across the web. The rarer the term, the higher the IDF, and the more unique information it provides.
