LDA Analysis 

LDA and its benefits in SEO?                                                  

Latent Dirichlet Allocation or LDA is a Topic modeling form. In SEO LDA will help to identify relevance score of a particular keyword as well as increase a page's relevancy in google. It shows words that help Google determine how relevant the page is to a user's search query.


Ideal score for LDA

Ideal Score for LDA to have good SEO: 0.1 to 0.3
More than 0.3 it’s excellent, Within 0.1-0.3 its ideal for SEO
Less than 0.1 is bad


Work mechanism

 First we take the URL of our given campaign and scrap the whole document. Then we use LDA algorithm & calculations to compute the relevancy signals. We then correlate with the mean relevance value of competitor’s and we use conditional statement to check if the value is less or greater than the competitor’s If our value is greater than the competitor’s then no action needed else we use our code structure to suggest the missing terms which will help us to improve our score once added to the landing page.

How to use LDA in webtool? Follow below steps for help.                                      


Step 1:

Login webtool account.

Step 2:

Insert landing page & Keyword

Step 3:

Add competitor &
View Result

Fix LDA Issue

LDA measure the relevancy of a particular keyword. If the choosing keyword's relevancy is low rather than competitors relevancy score then that particular keyword need to be add properly in landing page as per suggestion. But this measurement depends on word count of a particular landing page. Its word count criteria same like cosine similarity algorithm. 
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