Management of Social Media and Digital Marketing with Ai

Introduction: Advancements in digital marketing have provided diverse implications of AI in different business models. Therefore, this empirical analysis focuses on analysing the incorporation of AI in the management of Social Media and Digital Marketing. In addition, through a quantitative analysis objective of the study were met, and reliable results were delivered. Literature Review: For a better comprehension of the topic past literature was critically analysed and indigenous opinions were formulated. In addition, all the past literature was cited appropriately in the literature review portion. Methodology: For analysing the implication of AI in managing digital marketing primary data was collected through a qualitative analysis all the factors were analysed. Moreover, a survey population of 65 was chosen and they were surveyed using a questionnaire with 13 questions. Findings: A thorough examination of the linear regression table is provided in the empirical analysis results section. The study also included a descriptive analysis of the association in order to understand the nature and outliers of the data. Discussion: A thorough explanation of the findings is provided in the study's discussion section. Furthermore, a thorough discussion of the findings was provided in the study. Conclusion: Overall analysis is summarised with the findings of the study thus a brief discussion is provided in the conclusion.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-02-18
DOI
https://doi.org/10.52783/jisem.v10i11s.1596
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Management of Social Media and Digital Marketing with Ai

Suraj Sharma
Journal of Information Systems Engineering & Management
Big Data and Business Intelligence
article

Management of Social Media and Digital Marketing with Ai

Suraj Sharma
article en

Abstract

Introduction: Advancements in digital marketing have provided diverse implications of AI in different business models. Therefore, this empirical analysis focuses on analysing the incorporation of AI in the management of Social Media and Digital Marketing. In addition, through a quantitative analysis objective of the study were met, and reliable results were delivered. Literature Review: For a better comprehension of the topic past literature was critically analysed and indigenous opinions were formulated. In addition, all the past literature was cited appropriately in the literature review portion. Methodology: For analysing the implication of AI in managing digital marketing primary data was collected through a qualitative analysis all the factors were analysed. Moreover, a survey population of 65 was chosen and they were surveyed using a questionnaire with 13 questions. Findings: A thorough examination of the linear regression table is provided in the empirical analysis results section. The study also included a descriptive analysis of the association in order to understand the nature and outliers of the data. Discussion: A thorough explanation of the findings is provided in the study's discussion section. Furthermore, a thorough discussion of the findings was provided in the study. Conclusion: Overall analysis is summarised with the findings of the study thus a brief discussion is provided in the conclusion.

Journal of Information Systems Engineering & ManagementVol. 10(11s)
Openalex Percentile: Top 96%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.