We help you optimize your page for relevance to a given topic or keyword by using algorithms and data science to assist you.
Using our tool you can quickly get a list of terms and phrases used by the top 20 websites that already rank for your topic or keyword of interest. We believe that our version of the TF-IDF algorithm is the way to go in getting you the best list of terms and phrases to include in your copy to boost your rankings and be up there next to the top in the ranks.
Often when writing content, you are focused on the task at hand and write using ideas that follow a natural progression. For SEO the focus is also on writing high quality topically relevant content. Using our tool you can get a list of terms and phrases beforehand, so you know you haven’t missed any essential subtopic or related topic for the topic you are targeting.
Compare your use of the keyword and other terms with your competitors to ensure that you are not overusing keywords. Keyword stuffing is viewed negatively by Google, and you may get penalized for it.
Even if your focus is not content right now, you can use our tool to figure out all the best semantically related keywords in relation to the main keywords you are targeting. These keywords go well beyond "People also ask" and "Searches related" provided by Google.
Quickly figure out what you are missing that they are targeting. This may even help you uncover some keywords and boost your rankings in an off-page context too.
All computations are run on our servers, not your machine.
Run analysis on two words. Coming soon: three word analysis
Choose from a list of countries we support to get the relevant keywords for your location.
TF-IDF is a measure of relevance, unlike keyword density which is a measure of frequency. It is a measure of how closely related any content is to what the user is actually searching for.
TF-IDF is an old, well known algorithm in Information Retrieval. We believe that TF-IDF in its basic form is not usable at all. For anyone to effectively use it, they would require to be able to index all of the sites that make up the internet.
The algorithm we use is a TF-IDF variation at heart, but we have used other information retrieval principles, added a proprietary method of weighting and refined it to be a better substitute than base TF/WDF IDF algorithms.
We use it to try to figure out how Google calculates which websites should rank for a particular keyword based on their content.
We do this by essentially reverse engineering the process. We take the top 20 websites that already rank for the keyword and figure out their TF-IDF scores for that keyword and then go ahead and get all the statistically important terms and phrases that are found in their content.
Our algorithm weeds out some words and phrases and cleans up the data and then generates a list of phrases that are sorted by their TF-IDF scores.
Once the analysis is complete, we provide you with a clear list of terms you have missed in your content, terms that need improvement and terms that you have overused and may lead to a penalty.
For a simple overview of TF-IDF and how to use it, please see our article
For a more in-depth version, see our article on
We give you recommendations on where your scores should be. We clearly point out terms you may have missed entirely and terms that need improvement and how to achieve that.
We currently support English. We are actively working on supporting many other languages and will be releasing support for German and other user requested languages shortly.
If there is a particular language of interest to you, please send us an email at email@example.com.
We get ranking data for all countries that Google supports. Simply enter the country of choice when running the analysis.
Yes absolutely! Select none as an option instead of URL or content and you can run TF-IDF analysis for your target keyword and get the list of all important terms related to that keyword.
We think this will help you get a list before you even start writing content, so you can make sure not to miss any important category or sub-category.
For content analysis we recommend a minimum of 400 words. In our in house tests, content analysis below this threshold was not very useful.
Alternately if you have less than 400 words, you can select none as an option instead of content and do a TF-IDF analysis on competitors content to get a list of important terms.
This may help you get more ideas for more content and then you can do further content analysis after you've crossed about 400 words.
Based on our in house tests we found that one-word analysis doesn’t really contain enough context to be truly useful, to be truly actionable.
Let's say as an example the keyword we are focusing on is "dog food." In a one-word analysis the score for "dog" may be very different than the score for "food." This may lead you to incorrectly conclude that dog is more important than food as neither of the words has any context.
When writing content, one-word terms are not very useful as they have no context.
In addition, if you were using this for finding other keywords, one word keywords aren't very useful as ranking for them is very difficult.