Quick Search:

Revolutionizing Electronics E-Commerce: Harnessing The Power Of Artificial Intelligence In E-Marketing Strategies

Dutta, Surjadeep, Arivazhagan, R, Padmini Ema, Uma ORCID: https://orcid.org/0000-0003-0780-0417 and Balasundaram, Rebecca (2024) Revolutionizing Electronics E-Commerce: Harnessing The Power Of Artificial Intelligence In E-Marketing Strategies. Migration Letters, 21 (S6). pp. 207-220.

7891-Article Text-20615-1-10-20240216-1 (002).pdf - Published Version

| Preview


AI-based marketing refers to the use of artificial intelligence (AI) technologies and techniques in various aspects of the marketing process to enhance efficiency, effectiveness, and personalization. AI-based marketing can be applied across multiple channels, including digital advertising, content creation, customer segmentation, personalized recommendations, and customer experience management. This study aims to explore the demographic profile of ecommerce electronics products industry workers, evaluate the relationship between demographic traits and their influence on E-Marketing, and pinpoint the key performance metrics that influence Artificial Intelligence in ecommerce's E-Marketing. This study was designed using the descriptive technique. The study only included participants who were familiar with E-Marketing and Artificial Intelligence as they related to the electronic product based ecommerce industries, either as working professionals or as students. Five main variables were used to build the structured questionnaire with regard to E-Marketing, including respondents' beliefs, the use of Artificial Intelligence (AI) as a powerful tool, AI implementation, a focus on content generation, and deal closure by the marketing team. An online survey that was converted into a Google form by emailing the URL was used to collect data. To collect the data, a judgmental sampling strategy was employed. Link was sent to more than 350 people and followed them continuously for getting the response. Data collection process was stopped after reaching the 175 responses. Around 14 responses were removed due to poor and incomplete responses and finally 161 responses were chosen for the purpose of data analysis. Statistical analysis was carried out using the SPSS software package, version 22. To achieve the goals of this investigation, a variety of statistical analyses, including regression analysis, chi-square analysis, ANOVA, and frequency analysis, were recommended. The study's conclusions have significant ramifications for enhancing Artificial Intelligence integration and marketing strategy adjustment in order to preserve competitive advantage in the erratic digital market.

Item Type: Article
Status: Published
Subjects: H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HF Commerce
H Social Sciences > HF Commerce > HF5410 Marketing. Distribution of products
H Social Sciences > HF Commerce > HF5428-5429.6 Retail trade
T Technology > TA Engineering (General). Civil engineering (General)
School/Department: London Campus
URI: https://ray.yorksj.ac.uk/id/eprint/9555

University Staff: Request a correction | RaY Editors: Update this record