A Machine Learning Python-Based Search Engine Optimization Audit Software

In the present-day digital landscape, websites have increasingly relied on digital marketing practices, notably search engine optimization (SEO), as a vital component in promoting sustainable growth. The traffic a website receives directly determines its development and success. As such, website own...

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Published inInformatics (Basel) Vol. 10; no. 3; p. 68
Main Authors Roumeliotis, Konstantinos I., Tselikas, Nikolaos D.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.09.2023
Subjects
Algorithms
Audits
Competition
Internet marketing
Keywords
Machine learning
machine learning SEO
Methods
Nonprofit organizations
Optimization
Python (Programming language)
python SEO tool
Ranking
Ratings & rankings
Search engine optimization
Search engines
Semantic web
SEO techniques
Software
Source code
Websites
Greece
Online AccessGet full text
ISSN2227-9709
2227-9709
DOI10.3390/informatics10030068

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Abstract In the present-day digital landscape, websites have increasingly relied on digital marketing practices, notably search engine optimization (SEO), as a vital component in promoting sustainable growth. The traffic a website receives directly determines its development and success. As such, website owners frequently engage the services of SEO experts to enhance their website’s visibility and increase traffic. These specialists employ premium SEO audit tools that crawl the website’s source code to identify structural changes necessary to comply with specific ranking criteria, commonly called SEO factors. Working collaboratively with developers, SEO specialists implement technical changes to the source code and await the results. The cost of purchasing premium SEO audit tools or hiring an SEO specialist typically ranges in the thousands of dollars per year. Against this backdrop, this research endeavors to provide an open-source Python-based Machine Learning SEO software tool to the general public, catering to the needs of both website owners and SEO specialists. The tool analyzes the top-ranking websites for a given search term, assessing their on-page and off-page SEO strategies, and provides recommendations to enhance a website’s performance to surpass its competition. The tool yields remarkable results, boosting average daily organic traffic from 10 to 143 visitors.
AbstractList In the present-day digital landscape, websites have increasingly relied on digital marketing practices, notably search engine optimization (SEO), as a vital component in promoting sustainable growth. The traffic a website receives directly determines its development and success. As such, website owners frequently engage the services of SEO experts to enhance their website’s visibility and increase traffic. These specialists employ premium SEO audit tools that crawl the website’s source code to identify structural changes necessary to comply with specific ranking criteria, commonly called SEO factors. Working collaboratively with developers, SEO specialists implement technical changes to the source code and await the results. The cost of purchasing premium SEO audit tools or hiring an SEO specialist typically ranges in the thousands of dollars per year. Against this backdrop, this research endeavors to provide an open-source Python-based Machine Learning SEO software tool to the general public, catering to the needs of both website owners and SEO specialists. The tool analyzes the top-ranking websites for a given search term, assessing their on-page and off-page SEO strategies, and provides recommendations to enhance a website’s performance to surpass its competition. The tool yields remarkable results, boosting average daily organic traffic from 10 to 143 visitors.
Audience Academic
Author Tselikas, Nikolaos D.
Roumeliotis, Konstantinos I.
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SubjectTerms Algorithms
Audits
Competition
Internet marketing
Keywords
Machine learning
machine learning SEO
Methods
Nonprofit organizations
Optimization
Python (Programming language)
python SEO tool
Ranking
Ratings & rankings
Search engine optimization
Search engines
Semantic web
SEO techniques
Software
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Title A Machine Learning Python-Based Search Engine Optimization Audit Software
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