TF*IDF AnalysisYour Pro Tool for Content Optimization by seobility
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The TF-IDF analysis gives you valuable insights into the text optimization of good ranked websites. Identify important terms and keywords that are of high relevance to search engine ranking for specific search terms and compare your own content with your competitors.
Practical use cases of the TF-IDF analysis:
1. Research of vital terms/keywords for a topic/a search query
If you want to get a good overview of potential keywords or terms for a topic, the TF-IDF analysis can be useful in two different ways. On the one hand, the analysis of the keywords with the highest average TF-IDF values helps to find out what terms most websites consistently use to describe the topic. On the other hand, you can use these terms to determine the highest absolute TF-IDF values, the unique features of specific sites and their most important keywords. By combining these, you can build a comprehensive research base, e.g. to create content or optimize an existing website.
2. Competition analysis
The TF-IDF analysis is a perfect tool for taking a closer look at your competitors high-ranking content. If you are wondering what exactly sets your competitor’s website apart from your own site or want to find out why your competitor ranks higher, you should carry out a detailed analysis of the competitor’s relevant search terms and results. This information can help you to adjust and optimize your own content accordingly.
3. Optimization of new or existing texts
Apart from the topic and keyword research itself, you can also use the TF-IDF tool to directly optimize your content. Enter your website’s URL in addition to the search term and check your site’s values for the respective terms. Of course, you do not have to reach a mention or a high TF-IDF value for all terms to make your site count as well optimized. Instead, focus on the vital terms and on finding out what topics and keywords will make sense, and check if your content is optimized for these. A good optimization value for a keyword should be above the average TF-IDF value (calculated based on all search results that use that keyword), and below the maximum TF-IDF value for that keyword. As you know, overuse or excessive use of a term could be regarded as keyword stuffing or spamming, so you should only exploit or even exceed that maximum value in individual cases.
Optimizing your site becomes even easier as there is a text editor available for you that you can use to change the text of the URL you entered or to enter completely new text and update the analysis. In this way, you do not have to create or modify a site first to check your content’s TF-IDF optimization; you can start optimizing immediately.
4. Suitable content and search terms for a TF-IDF analysis
TF-IDF optimization might not be suitable for every search term. Only if one of the following characteristics applies to the search terms, a TF-IDF optimization will make sense:
- Results for the query intent "information"
- Special topics and niche topics (Long tail)
- Primarily "text-heavy" results with longer text content
- Search terms leading to search results that are similar in content ("car" vs "buy car")
The following search requests / search results are less suitable for TF-IDF optimization:
- Very general search terms (for example: news, car, vouchers)
- Search terms on current events (elections, refugee crisis)
- Search terms with high competition (in these cases, other criteria such user signals, the website’s authority, backlinks etc. tend to play a more important role)
- Search terms that deliver very different kinds of results
Theory and relevance for search engine optimization
The formula for the calculation of TF-IDF was initially utilized in information technology to assign weighting factors to words in a text collection or library. In search engine optimization, this formula is used to optimize sites for specific search terms, creating unique content. TF-IDF is not an exact science to better understand the search engine rank of specific content, it is rather a tool for a number of use cases.