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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/10/3/68 |
| _version_ | 1797579594900963328 |
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| author | Konstantinos I. Roumeliotis Nikolaos D. Tselikas |
| author_facet | Konstantinos I. Roumeliotis Nikolaos D. Tselikas |
| author_sort | Konstantinos I. Roumeliotis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T22:38:23Z |
| format | Article |
| id | doaj.art-9929262226ef42c286faaadaf44468c2 |
| institution | Directory Open Access Journal |
| issn | 2227-9709 |
| language | English |
| last_indexed | 2024-03-10T22:38:23Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj.art-9929262226ef42c286faaadaf44468c22023-11-19T11:13:35ZengMDPI AGInformatics2227-97092023-08-011036810.3390/informatics10030068A Machine Learning Python-Based Search Engine Optimization Audit SoftwareKonstantinos I. Roumeliotis0Nikolaos D. Tselikas1Department of Informatics and Telecommunications, University of Peloponnese, 22131 Tripoli, GreeceDepartment of Informatics and Telecommunications, University of Peloponnese, 22131 Tripoli, GreeceIn 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.https://www.mdpi.com/2227-9709/10/3/68search engine optimizationSEO techniquespython SEO toolmachine learning SEO |
| spellingShingle | Konstantinos I. Roumeliotis Nikolaos D. Tselikas A Machine Learning Python-Based Search Engine Optimization Audit Software Informatics search engine optimization SEO techniques python SEO tool machine learning SEO |
| title | A Machine Learning Python-Based Search Engine Optimization Audit Software |
| title_full | A Machine Learning Python-Based Search Engine Optimization Audit Software |
| title_fullStr | A Machine Learning Python-Based Search Engine Optimization Audit Software |
| title_full_unstemmed | A Machine Learning Python-Based Search Engine Optimization Audit Software |
| title_short | A Machine Learning Python-Based Search Engine Optimization Audit Software |
| title_sort | machine learning python based search engine optimization audit software |
| topic | search engine optimization SEO techniques python SEO tool machine learning SEO |
| url | https://www.mdpi.com/2227-9709/10/3/68 |
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