Python Driven Keyword Analysis for SEO Optimization

Title

Python Driven Keyword Analysis for SEO Optimization

Creator

Kanara A.P.; Kumari P.; Prathap B.R.

Description

Every word or string of words a user types into a search engine has meaning. For example, a user might search for a 'hotel' or a 'hotel in New York City.' Keywords are the standard focus of search engine optimization (SEO), which offers a useful method of gauging demand for specific queries and aiding in a better understanding of how users look for goods, services, businesses, and, eventually, solutions. Any effective SEO strategy must include keyword research, and Python is a strong language that can be used to automate and accelerate the process. This project presents a Python-based keyword research tool that works on real-time data to identify the top searches over a user-specified domain to identify trends and customer needs. It does this by utilizing multiple Python libraries and Google Autocomplete. The Google Autocomplete results for the user-specified domain are first parsed by the tool before it can function. After that, unnecessary keywords are eliminated by filtering and cleaning the results. Subsequently, the remaining keywords are arranged for search volume and domain relevancy. The tool looks for trends by comparing the current keyword rankings with previous data. Thanks to this, users can see which keywords are growing in popularity. By identifying the most commonly asked questions and issues, the tool also offers insights into the needs of its users. The tool is simple and adaptable to each user's unique requirements. It can be used to create keyword lists for content marketing, SEO, and product development, among other uses. 2024 IEEE.

Source

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024, pp. 1170-1176.

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Content marketing; Domain relevancy; Google Autocomplete; Insights; Keyword research; Product development; Python; Real-time data; Search engine optimization (SEO); Trends

Coverage

Kanara A.P., Christ (Deemed to be University), Computer Science Engineering (Specialization in Data Science), Banglore, India; Kumari P., Christ (Deemed to be University), Computer Science Engineering (Specialization in Data Science), Banglore, India; Prathap B.R., Christ (Deemed to be University), Computer Science Engineering (Specialization in Data Science), Banglore, India

Rights

Restricted Access

Relation

ISBN: 979-835038436-9

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICACCS60874.2024.10717132

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208626488&doi=10.1109%2fICACCS60874.2024.10717132&partnerID=40&md5=47f383dee48888ea46db26a9d41fb7f9