Post by account_disabled on Feb 27, 2024 7:02:51 GMT
The used the term naturally in the article. To solve this problem we turned to TFIDF. Recognizing TFIDF as a ranking factor TFIDF Term FrequencyInverse Document Frequency is a way to figure out how important a word is in a document based on how frequently it appears in it. This is a pretty standard statistical process in information retrieval. It is also one of the oldest ranking factors in Googles algorithms. Hypothesis We hypothesized that dropping the number of sales management occurrences from to and replacing it with terms that have high lexical relevance would improve rankings.
Were we right See for yourself Our organic pageviews increased from Kazakhstan Phone Number early to over in just over months. Note that no new links or link acquisition initiatives were actively inprogress during the time of this miniexperiment. Experiment timeline July th Overoptimized keyword recognized. July th Content team finished updating body copy Hs with relevant topicssynonyms. July th Updated internal anchor text to include relevant terms. July th Flushed cache resubmitted to Search Console. August th Improved from to for Sales Management August Improved from to for Sales Management The results were fast. We were able to normalize our content and see results within weeks. Well show you our exact process below.
Normalization process How did we do it The normalization process focused on identifying overoptimized terms replacing them with related words and submitting the new page to search engines. Heres how we did it . Identifying overoptimized terms We started off using Mozs onpage optimization tool to scan our page. According to Moz we shouldnt have used the target term sales management more than times.. In addition to replacing those occurrences with lexically relevant terms which we will discuss below we ran our pages through MarketMuse to assess how well weve covered relevant topics on our site. This machine learning platform scanned your pages gave back a report which told.
Were we right See for yourself Our organic pageviews increased from Kazakhstan Phone Number early to over in just over months. Note that no new links or link acquisition initiatives were actively inprogress during the time of this miniexperiment. Experiment timeline July th Overoptimized keyword recognized. July th Content team finished updating body copy Hs with relevant topicssynonyms. July th Updated internal anchor text to include relevant terms. July th Flushed cache resubmitted to Search Console. August th Improved from to for Sales Management August Improved from to for Sales Management The results were fast. We were able to normalize our content and see results within weeks. Well show you our exact process below.
Normalization process How did we do it The normalization process focused on identifying overoptimized terms replacing them with related words and submitting the new page to search engines. Heres how we did it . Identifying overoptimized terms We started off using Mozs onpage optimization tool to scan our page. According to Moz we shouldnt have used the target term sales management more than times.. In addition to replacing those occurrences with lexically relevant terms which we will discuss below we ran our pages through MarketMuse to assess how well weve covered relevant topics on our site. This machine learning platform scanned your pages gave back a report which told.