The Impact of AI Technology in Digital Marketing: A Case Study of Nike
Project Proposal: The Impact of AI Technology in Digital Marketing: A Case Study of Nike
The proposal must cover the main sections of the project:
i. Overall industry background and discussion of relevant marketing trends.
ii. Research problem and objectives to be addressed.
iii. Scope of the Study: Identification and definition of marketing concepts and terms, identification of the
marketing area and the usefulness of the topic.
iv. Literature review, including discussion of relevant marketing theory.
v. Methodology, specifying a plan to collect data to meet the stated objectives.
vi. Timetable/schedule,
vii. Indicative Bibliography
The Impact of AI Technology in Digital Marketing: A Case Study of Nike
Introduction
In recent years, artificial intelligence (AI) technology has emerged as a powerful tool in various industries, including digital marketing. AI technology has the potential to revolutionize the way companies interact with their customers, analyze data, and optimize their marketing strategies. This project proposal aims to investigate the impact of AI technology in digital marketing, with a specific focus on Nike, one of the world’s leading sports footwear and apparel brands.
I. Overall Industry Background and Discussion of Relevant Marketing Trends
To understand the context in which AI technology is impacting digital marketing, it is essential to examine the overall industry background and identify relevant marketing trends. The digital marketing landscape has evolved significantly with the rise of social media, mobile devices, and e-commerce platforms. Companies are increasingly adopting data-driven strategies to target their customers effectively and deliver personalized experiences.
II. Research Problem and Objectives to be Addressed
The research problem of this study is to analyze the impact of AI technology on Nike’s digital marketing efforts. The objectives of the research include:
Assessing how Nike utilizes AI technology in its digital marketing campaigns.
Analyzing the effectiveness of AI-powered personalization in enhancing customer engagement and conversion rates.
Examining the challenges and limitations faced by Nike in implementing AI technology in digital marketing.
Providing recommendations for Nike to optimize its AI-driven digital marketing strategies.
III. Scope of the Study
This study will focus on identifying and defining key marketing concepts and terms related to AI technology in digital marketing. It will explore how Nike leverages AI technology to enhance customer experiences, improve targeting capabilities, and optimize its marketing campaigns. The study will also investigate the usefulness of AI technology in the specific context of Nike’s digital marketing efforts.
IV. Literature Review
The literature review section will provide a comprehensive analysis of relevant marketing theory and scholarly research related to AI technology in digital marketing. It will explore the advancements in AI technology, such as machine learning, natural language processing, and predictive analytics, and their applications in digital marketing. The review will also discuss case studies and empirical studies that highlight the impact of AI technology on companies’ marketing strategies and customer experiences.
V. Methodology
To meet the stated objectives, a mixed-method research approach will be employed. The primary data collection will involve conducting interviews with key stakeholders at Nike, including marketing executives and data analysts, to gain insights into their utilization of AI technology in digital marketing. Additionally, quantitative data will be collected through surveys distributed to Nike’s customers to assess their perception of AI-driven personalization and its impact on their purchasing decisions.
VI. Timetable/Schedule
The project timeline is as follows:
Literature Review: 2 weeks
Data Collection (Interviews and Surveys): 4 weeks
Data Analysis: 3 weeks
Report Writing: 2 weeks
Finalizing the Project: 1 week
VII. Indicative Bibliography
Chaffey, D., & Ellis-Chadwick, F. (2019). Digital Marketing: Strategy, Implementation and Practice.
Liang, T.-P., Ho, Y.-T., Li, Y.-W., & Turban, E. (2020). What Drives Purchase Intention in Mobile Commerce? A Multilevel Analysis. Information & Management, 57(4), 103168.
Marr, B. (2018). Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems.
Nambisan, S., & Baron, R. A. (2019). Entrepreneurship in Innovation Ecosystems: Entrepreneurs’ Self-Regulatory Processes and Their Implications for New Venture Success. Journal of Business Venturing Insights, 12(e00122).