Management information system topic the impact of using generative ai on marketing effectiveness

THE IMPACT OF USING GENERATIVE AI ON MARKETING EFFECTIVENESS Minh-Duy Duong, Minh-Tuan Le, Nhat-Quang Pham, Thi-Ngoc Nhi -Tran, Truong-Vu Le Faculty of Economics HCMC University of Techn

HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND

SCORE PROJECT REPORT

SUBJECT: MANAGEMENT INFORMATION SYSTEM Group: 02 Class: MAIS430306_23_1_07 các nội dung theo yêu cầu, phân tích

(địa điểm, quá điểm nổi bật của báo cáo, nêu

THE TABLE OF ASSIGNED WORK

TABLE OF CONTENT

ABSTRACT 1

I INTRODUCTION 1

II METHOD 4

III LITERATURE REVIEW 5

IV FACTORS INFLUENCING SUCCESS IN IMPLEMENTING GENERATIVE AI IN

TABLE OF PICTURE

Picture 1: Results of the VOS data visualization software 6

Picture 2: Results of the yellow cluster 7

Picture 3: Results of the red cluster 8

Picture 4: Results of the green cluster (organization) 10

Picture 5: Results of the blue cluster (organization) 12

Picture 6: Results of the purple cluster (organization) 14 LIST OF ACRONYMS

AI (Artificial intelligence) IoT (Internet of Things)

GAN (Generative Adversarial Networks) GAI (generative artificial intelligence)

THE IMPACT OF USING GENERATIVE AI ON MARKETING EFFECTIVENESS

Minh-Duy Duong, Minh-Tuan Le, Nhat-Quang Pham, Thi-Ngoc Nhi -Tran, Truong-Vu Le

Faculty of Economics

HCMC University of Technology and Education Ho Chi Minh City, Vietnam

ABSTRACT

In order to become more competitive, several organizations have implemented generative artificial intelligence (GAI), which has recently demonstrated a strong development in a variety of industries The breakthrough in marketing effectiveness has had a favorable influence on marketing On the other hand, little focus has been placed on how GAI affects marketing initiatives This article investigates the function of generative artificial intelligence(GAI) in marketing activities with the goal of elucidating the generative artificial intelligence (GAI) aspects that affect marketing operations The impact of using GAI in marketing campaigns on business sales is analyzed and evaluated

Keyword:Generativ e artificial intelligence (GAI), marketing effectiveness, business sales

I INTRODUCTION

The advent of the Fourth Industrial Revolution has brought about tremendous advancements in technology, revolutionizing various industries and fields One area that has witnessed significant interest and investment in large-scale development is the digital transformation in banking and finance As technology continues to evolve, businesses recognize the need to adapt and implement digital strategies to stay relevant in the modern environment

In the realm of marketing, the utilization of generative artificial intelligence (AI) has had a profound impact on effectiveness Generative AI refers to the use of advanced

algorithms and machine learning techniques to generate content, such as text, images, and videos, that closely mimic human creativity This technology has enabled marketers to create compelling and personalized experiences for their target audience, leading to improved marketing outcomes

One notable contribution of generative AI is its ability to enhance content creation Marketers can leverage generative AI algorithms to automate the generation of engaging and relevant content at scale This automation saves time and resources while ensuring a consistent stream of high-quality content By generating content tailored to individual customer preferences and behavior, businesses can deliver personalized marketing campaigns that resonate with their target audience

Another significant impact of generative AI is its role in improving customer interactions and engagement Virtual assistants powered by generative AI, such as chatbots, can provide instant and personalized responses to customer inquiries, enhancing the overall customer experience These AI-powered assistants can handle repetitive tasks, answer frequently asked questions, and even provide product recommendations based on customer preferences, leading to increased customer satisfaction and loyalty

Generative AI also contributes to marketing effectiveness by optimizing marketing strategies and campaigns By analyzing large volumes of data, AI algorithms can identify patterns, trends, and customer insights that might otherwise be overlooked Marketers can leverage this information to tailor their strategies, optimize targeting, and personalize messaging, resulting in more effective marketing campaigns that yield higher conversion rates and return on investment

Despite the positive impact of generative AI on marketing effectiveness, it is important for businesses to approach its implementation thoughtfully Ethical considerations, data privacy, and transparency should be prioritized to maintain trust and ensure compliance with regulations Additionally, continuous monitoring, analysis, and refinement of AI algorithms are crucial to keep up with evolving customer preferences and market dynamics

The article's contributions:

Utilizing text mining to analyze the impact of using generative AI on marketing effectiveness as a new approach

Analyzing the factors influencing marketing effectiveness when employing generative AI from five main topic groups

Proposing solutions to enhance marketing effectiveness through the utilization of generative AI

II METHOD

A Data Description:

In this study, we utilized a dataset comprising 50 scientific research papers related to keywords such as Generative AI, Marketing, and Social Media from recent publications

B Text Information Extraction Methodology:

According to Josh et al (2002), information extraction from text is a technique that assists users in retrieving valuable information from a large volume of digital text documents on the web or a database

Lord et al suggest that text information extraction offers various methods for extracting information and knowledge from text data, such as classification, segmentation, clustering, semantic analysis, etc With the vast amount of collected data, searching for important and valuable information becomes challenging Hence, we employed text information extraction software to visualize word clouds from different datasets Terms with high frequencies were extracted from the primary text dataset In this paper, we utilized a topic model through vocabulary-based common analysis The frequency of keywords was used to generate a co-occurrence matrix and related topic clusters, enabling the analysis of connections between them The basic steps included:

1 Collecting unstructured data from scientific papers, websites, etc

2 Performing preprocessing: this step helps transform unstructured text into structured form

3 Removing unnecessary information: In this step, the analysis system eliminates irrelevant and unnecessary information Using text analysis techniques based on the probability of a keyword's occurrence, the system removes some unnecessary words like "if," "then," "so," "and," "of," "to," etc., while retaining valuable hidden information behind the data

4 Evaluating knowledge after processing and presenting the achieved results 5 Lastly, storing crucial information in the database, promoting the analysis of

current trends, thereby providing valuable societal information and ai ding global AI communities in identifying new trends and solutions

III LITERATURE REVIEW

Recent scholarly discourse has extensively examined the concept of digital transformation, revealing diverse perspectives and definitions across various studies Schwertner (2017) characterizes digital transformation as the strategic incorporation of technology to reshape processes, software, systems, and business models, with the primary goals of amplifying revenue streams, refining operational efficiency, and gaining a competitive edge Contrarily, Ebert and Duarte (2018) posit that digital transformation entails the application of disruptive technologies to bolster productivity, enhance value propositions, and contribute to societal well-being

Vial (2021) elaborates on digital transformation, defining it as a comprehensive process that seeks to enhance entities by introducing substantial changes to their attributes, leveraging information technology, computer computing, communication, and connectivity Tran Dinh Quang (2021) interprets digital transformation as a restructuring of working and production methods through the seamless integration of digital technologies into enterprise operations, thereby reshaping business models for heightened efficiency and value

Le Thi Thuy Van (2021) views digital transformation as the transition from traditional to digital business models, integrating technologies such as big data, the Internet of Things (IoT ), and cloud computing The Ministry of Marketing and Social (2019) further defines it as the strategic integration and application of digital technology to elevate the efficiency, management, capacity, and competitiveness of enterprises, consequently ushering in new values

Transitioning to the exploration of Generative AI's impact on marketing effectiveness within the digital transformation landscape, it becomes imperative to investigate how this emerging technology reshapes marketing strategies and practices As organizations increasingly turn to Generative AI for automated content creation, personalized customer interactions, and data analysis, this literature review sets the stage for examining the intersection of Generative AI and digital marketing, exploring its implications, challenges, and opportunities for organizations navigating the dynamic digital landscape

IV FACTORS INFLUENCING SUCCESS IN IMPLEMENTING GENERATIVE AI IN MARKETING OPERATIONS

In this research, the VOS data visualization software is employed to analyze data collected from 50 scientific research paper s Each keyword displayed indicates its frequency in the papers, with larger sizes indicating higher occurrences Keywords are interconnected with each other through links The results of this analysis have identified five key keywords influencing the application of AI in marketing: marketing, content, intelligence, study, and ChatGPT

Picture 1: Results of the VOS data visualization software

Within the yellow color-coded group, keywords are concentrated on the application of artificial intelligence in optimizing content and images It is noticeable that the term 'content' appears prominently within the large yellow circle Furthermore, it is linked to other smaller circles containing terms such as 'image,' 'paper,' and 'field.' From this, it can be observed that these 'content' factors significantly impact the utilization of AI in marketing

Picture 2: Results of the yellow cluster

Firstly, the keyword 'content' elucidates that GAI has several influential factors in marketing activities Analyzing extensive data and gaining deep insights into consumer behavior enables the creation of highly interactive content tailored to the preferences and behaviors of customers Predicting consumer trends helps businesses approach their targets more effectively Automated optimization of content strategies based on feedback and real data is a key capability of GAI With machine learning and creativity, GAI produces unique content that captures customer attention Additionally, GAI supports the optimization of content for search engines, particularly voice search

Secondly, integrating GAI into 'image' not only optimizes advertising strategies but also enhances the user experience positively Automatically generated images can quickly reflect the intentions and messages of businesses, increasing the interaction capabilities of content across online platforms The brand is monitored and recognized promptly, aiding businesses in tracking the effectiveness of advertising strategies and brand recognition Content within images is categorized by content and context Visually appealing content enhances the user experience, strengthening brand connections

Thirdly, the keyword 'paper' is an important factor in applying GAI to marketing activities 'Paper' refers to research papers, reports, or detai led information about

products and services When using GAI, it helps improve data quality and provides reliable information for marketing strategies GAI evaluates market trends and directions effectively based on large datasets

Finally, the keyword 'field' signifies the influence in the application of artificial intelligence and its integration into marketing activities Each industry has its own characteristics, from target customers to approaches Therefore, understanding different industries accumulates data uniquely GAI can use industry data to gain a deeper understanding of customer behavior, market trends, and market access opportunities

In summary, the factors within the yellow-coded cluster offer numerous benefits for marketing activities, from increasing interaction rates to predicting trends and optimizing strategies It helps businesses gain a better understanding of their customers, creating content that connects effectively

In the red cluster, the term "ChatGPT" appears in the largest circle, indicating its frequent mention in the data Additionally, there are smaller interconnected circles such as "literature," "business," "chatbot," "organization," and "customer service." These elements play a role in the application of GAI in marketing

Picture 3: Results of the red cluster

The keyword "ChatGPT" stands out as the most prominent and influential factor ChatGPT possesses the capability to process and generate text in natural language, creating a communication experience with users that is both natural and flexible This is crucial in today's marketing landscape, where consumers seek personalized and real-time interactions The continuous 24/7 communication of ChatGPT allows businesses

to maintain a direct presence at all times By customizing feedback based on individual customer data, businesses can create a more personalized user experience The feature of automatically responding to common queries helps businesses free up resources and enhance operational efficiency Continuous adaptation and learning enable ChatGPT to evolve according to market trends and consumer behavior Additionally, ChatGPT's ability to seamlessly integrate with various communication channels, including websites, social media, and messaging apps, enhances its effectiveness

The keyword "literature" serves as a supporting factor for businesses by providing knowledge and strategies "Literature" offers a comprehensive understanding of the marketing field through research papers, books, and literary articles These resources help build a theoretical foundation and solid knowledge of the industry This is crucial for effectively applying GAI, especially when facing challenges and opportunities in the current business environment The strategic literature that GAI provides assists businesses in optimizing content strategies, customer interaction, and efficient data usage

The keyword "business" plays a defining role in business strategy, data management, and identifying target customers in an organized and efficient manner Businesses need to grasp the business context, including competitive rivals, industry characteristics, and customer needs, to optimize GAI applications Clearly defining marketing goals, target audiences, and customer interaction strategies helps deploy marketing plans in harmony with business needs The "business" factor helps identify specific customer groups to target, thus optimizing their experience and interaction with GAI Additionally, effective budget management is essential to ensure that the business has sufficient resources for GAI deployment and maintenance over time

The keyword "chatbot" contributes to flexibility, convenience, and personalized interaction for customers Chatbots provide real-time interaction capabilities with customers, creating a flexible and immediate user experience They help alleviate the workload for human staff by automating basic and repetitive tasks such as answering common questions and providing necessary information Through data learning about individuals, understanding preferences, and interaction history, chatbots can deliver customized information and solutions, enhancing the user experience