MAL7504-E Proposal Sample – Applied Artificial Intelligence and Data Analytics Capstone 2022

1.0 Introduction

1.1 Research Scope

The scope associated with the study describes the degree to how the research field will indeed be investigated within work, as well as the criteria which will be used to do it. To put it another way, the researcher has to identify whatever the research would cover and what it might concentrate on. In terms of the study subject, the major focus of this research will be on the deployment of AI technologies in the field of marketing and the sphere of advertising operations in any organization.

To accomplish so, an examination of different kinds of AI technologies in the advanced world is necessary (Fesaghandis et al. 2018). As a result, research into the efficacy and needs of various technologies in the focused domain will be assured. The study also identified effective functions and applications of the advertising process in the field of digital marketing.

As a result, the study will have a better knowledge of the potential of using different types of digital marketing. Businesses are increasingly accepting modern technologies within their existing structures, as has been observed with the advancement of technology.

Different segments associated with advertising will be identified to determine which spheres require implementing various AI technologies and their applicability to improve efficiency. The impact of AI technologies on marketing will be represented in the same way.

MAL7504-E Proposal Sample - Applied Artificial Intelligence and Data Analytics Capstone

Figure 1: Marketing Using AI


1.2 Research Rationale

The research national is considered to be the static reason for which the entire research has been conducted. The rationale represents the need and requirement associated with the research, and it also has a significant role in justifying the importance and novelty associated with the entire research. In this case, the focused research will examine the concept of intelligent marketing, in which AI technology is used in various advertising methods and marketing processes.

The transfer of human intelligence into machines, known as artificial intelligence, can improve the execution of both simple and complex tasks. The primary goal of artificial intelligence is to learn to reason and perform various tasks. Artificial intelligence, according to some researchers, is becoming more important in the age of developing technologies.

To improve marketing techniques, every organization’s advertising and marketing unit collects a large amount of data. Artificial intelligence (AI) has demonstrated its ability to efficiently manage and analyze large amounts of data (Paschen et al. 2019). As a result, this study aims to see what the implications and impacts of AI technologies are in strengthening and improving marketing strategies.

It has also been observed that traditional business approaches have given way to modern technical approaches such as e-business. Business structures are changing rapidly as technology advances, and initiatives to adopt advanced modes of technology within their expanding structure are being taken.

As a result, understanding the various functions and operational practices of AI technologies allows me to apply this technological advancement in every business sphere. This study will also begin to provide information about the use of technology in advertising based on digital marketing.


2.0 Aim and Objectives

The research’s aims and objectives play a key influence in this sphere of making decisions for every activity that must be completed to go forward with the research. It provides knowledge and a thorough comprehension of the research’s requirements to respond to the research’s stated question (Vishnoi et al. 2018).

It has also been discovered that it will create a narrative that makes a clear link between the research endeavour and the topic that inspires the discovery. While objectives are seen to be some sort of Undertaker in action that the researcher wants to put into practice within the research project, they are also thought to be some sort of Undertaker.

2.1 Aim

The study aims to see how artificial intelligence “concepts and methods” are used in the process of the “advertising and digital marketing processes” and how this concept implements improvement and advancement in business strategies.

2.2 Objectives

  • To comprehend the roles and processes of AI in the context of digital marketing.
  • To have a better knowledge of the characteristics of advertising segments where AI can be employed.
  • To discover how artificial intelligence (AI) may help enhance the advertising process in the field of marketing.
  • To recommend the most acceptable AI systems for use in the marketing sector.


3.0 Research Questions

How artificial intelligence “concepts and methods” are used in the process of the “advertising and digital marketing processes” to implement improvement and advancement in business strategies?

4.0 Literature Review

4.1 Taxonomy

In this literature review section, it will be discussed about the literatures and concepts that are published as the literature by various of researchers all over the world. For this portion a total of 12 literatures have been taken and they have been reviewed for writing this section and the name of the researchers are also citied.

Artificial Intelligence is the emerging technology in the market and by the use of this technology there can be seen development in various of sectors and marketing is one of them. So, the companies should understand the need of AI and the adaptation process of the Ai in marketing process is very important to sustain the business in the market. So the topic needs to be studied.

As the use of the AI technologies in the marketing process is new to he market so there can be some of the limitations in the literatures that are already published in this topic. So some scope of the future development can also seen in this topic and they will be also discussed in this literature review section also.

4.2 Critical Discussion

For better execution of the simple and the complex task, there can use the transfer process of human intelligence in the Machines, and this is called artificial intelligence. It can be seen that learning reasoning and executing different activities are the main objective of artificial intelligence.

In the age of developing Technologies, some of the researchers said that artificial intelligence became outdated. Where can we see three major concepts behind AI and these three major concepts are “machine learning”, “deep learning”, and “neural network” (Weber et al. 2019). By the use of these techniques, there can be seen for the development in the process of “data mining”, “neural language processing” and “driving software”.

In some terms, it can be seen that Artificial Intelligence and machine learning seem like terms that are interchangeable, but in a broad, it can be seen that is considered as the term, and the major concepts are considered as the subset of artificial intelligence. As people have seen in the movies that robots are working for humans, so from that sense, people think that AI is an automated robot (Kose et al. 2017).

There can be seen the process of adaptation artificial in those robots that are working like humans. Where can we see him in some continuous learning process and also some problem-solving process? These unique features have made artificial intelligence an important technology in the world. Sometimes it can be seen that humans can find any task as difficult or boring, but with the help of artificial intelligence, they will never feel that. A system with AI can do the same job repeatedly.

There can be a major feature in the artificial intelligence process, and that is known as data ingestion. There can be the incorporation of huge amounts of data in AI systems. This system can collect some specific data from a huge chunk of data size, and the specific data will be as the requirement of the user.

In real-life scenarios, there can be a huge amount of data in the database of the companies like “Amazon” “Facebook”, and these huge amounts of data can be impossible (Paschen et al. 2020) to handle and analyzed by humans. There can be another feature of artificial intelligence that can Store multiple information from multiple sources, and the information is about multiple people. And all these Data Collection processes are done by the system simultaneously.

Artificial intelligence systems are mainly designed for the observation and the reaction process to their surroundings. AI analyses what is happening around the environment and then takes adequate action according to the situation, and it also analyses the situations that might come up in the future or soon.

For example, it can be seen that by analyzing the historical data of some machine, an artificial intelligence system can predict the time of breakdown of that machine, and it can give the user an alert before The breakdown process.

MAL7504-E Proposal Sample - Applied Artificial Intelligence and Data Analytics Capstone

Figure 2: Benefits of AI-based marketing


In the 21st century, the researcher’s all over the world have published various literature about the enhancement of the experiences of the customer in the marketing process by the use of artificial intelligence. The researcher named Gacanin has explained some challenges that can come from anywhere, and management of these challenges is called “customer experience management (CEM)” (Weber et al. 2019).

There can be some explanation about “intelligent networks” and drivers for “critical business value”, which were based on AI. By the process of “neural Language Processing” and “chatbots of AI”, there can be seen the improvement of the customer experience in the marketing process. Making the correct decisions every time there can be seen some algorithms of artificial intelligence that will efficiently do the data processing.

There can be seen the analysis process by the artificial intelligence systems about the habits of the customer, the purchase rate of the customers, the likings and dislikes of the customers etc. By the use of the “artificial intelligence user interface (AIUI)”, there can be seen various benefits in “customer relationship management (CRM)” (Overgoor et al. 2019).

This can be seen in the conversion of “traditional retail stores” to “smart retail stores” by the use of Artificial Intelligence and IoT. In comparison with traditional retail stores, smart retail stores offer the customer an easy shopping process, and it also improves the experience of the customer in the shopping process. There can be seen major use of artificial intelligence in online business.

The researchers named Sha and Rajeswari explained artificial intelligence as a supportive machine that can be seen as a feature for tracking all the five senses of humans. As a result, it can be seen the better Association between the consumer and the brand and product and the brands in the E-Commerce business.

There can be seen in the use of artificial intelligence by marketers for the planning and strategy-making process for market activities. It is mainly used for market segmentation targeting the market and positioning the market process. Besides the STP process, for planning the strategic orientation of the business form, there can be seen the use of artificial intelligence processes.

For identifying “profitable customer segments,” there can be seen the use of “text mining” and “machine learning algorithms” of artificial intelligence in the sector like “Banking and Finance”, “art marketing”, “retail and tourism” (Miklosik et al. 2019). For narrowing down the targeted customers, there can be seen some Optimisation techniques of the machine learning process.

By the use of analytic tools that are based on artificial intelligence, it can predict The suitability of the product to the customer needs. This will ensure customer satisfaction with the product. For the better process of innovation and designs for the service of the business companies, there can be seen the use of topic modelling by the business company.

Understanding the product recommender system, there can be seen as the assignment of preference weight to every product that will help the marketers to search the product and also help in the alignment process of the marketing strategies that will help the marketer in the product management process. For exploring new processes and for personalizing the recommendation to the customers, there can be seen the use of the process called deep learning.

There can be some customized deal that is offered by Artificial Intelligence, and that can shoot the need and the preference of the customer.

Pricing is considered one of the major factors in the marketing process (Ge et al. 2018). For finalizing the final price of any product, there can be seen the use of analyzing multiple aspects of the product, and that calculation process is not an easy job. There can be some complexity in the calculation of the price of the products because there can be some real-time variation in the price, and death can be seen in the demand fluctuation of the products.

Adjusting the price of the products in real-time can be seen through the use of a “Multiarmed Bandit algorithm” of artificial intelligence (Melnychenko et al. 2019). There can be various sectors where it can be seen the frequent Changing of the prices like commerce portal, quickly adjusting the price points in the sector there can be seen the use of Bayesian inference of machine learning algorithm for matching the price of the competitor.

According to the researcher named Dekimpe, “best response pricing algorithms encapsulate customer choices, competitive strategies, and supply network to optimize dynamic pricing” (Maedche et al. 2019).

For improving customer satisfaction in a specific business, there can be seen the importance of the availability of the product and better accessibility of the product. There can be some major factors in which there can be seen the dependency of the product distribution system, and major factors are “network relationship”, “logistics”, “inventory management”, “warehousing” and “transportation” (Bruyn et al. 2020).

There can be some transportation problems in most business companies, and the nature of the problems are mainly mechanical, and these problems can arise repeatedly. There can be some adequate and sufficient solutions by the use of artificial intelligence in the place management of the product. Cobots for packaging drones for delivering and IoT for order tracking and order refilling are the main solution processes of artificial intelligence.

There can be seen the benefits of both the customers and the suppliers by the standardization and the mechanization of the distribution process. In the service context of a company, there can be opportunities for connection with the customers of the company by the use of artificial intelligence, and it is done besides the distribution Management process. For surface acting, there can be some implementation of the quotes that are emotional and that are programmed into the service robots.

Service robots can engage with the customers with greetings, but to win the customer delight, there can be seen the need for human elements. Some additional opportunities can be seen in the performance and productivity of a business company by automation of the service process with the artificial intelligence process.

5.0 Research Methodology and Data Collection

In the 21st century, for improving the marketing process of any business company, there can be seen the need for artificial intelligence for the whole marketing process. There can be some major methods of artificial intelligence by which it can incorporate the artificial intelligence system in the marketing process of any business company. The three major methods are machine learning, deep learning, and neural networks.

By the incorporation of these methods in different aspects of the business process are basically in the marketing process their time is seen as an improvement and that is recorded and submitted by most of the companies in the 21st century. It can be seen the use of different techniques of machine learning for optimizing the targeted customers of the company (Aoun. 2017).

The deep learning method is used for exploring new processes of marketing and also personalizing the recommendations to the customers. Some algorithms of neural networks are used for managing the supply chain network of the business process and also adjusting the price of the products or services of the business company.

It can be seen that the base programming language for all these technologies is “Python” programming language and this programming language is vastly used for programming all the methods with the system of the marketing. So, these kinds of methods of artificial intelligence are so important for the development of the marketing process of business companies all over the world.

For the implementation of the methods for intelligent marketing, there can be seen the major need of Data Collection process for the better implementation of the artificial intelligence algorithms (Aithal, 2017). As there can be seen the incorporation of a huge set of data for the data collection process there can be seen the importance of the data collection process.

For the data collection process of the project, there can be seen the use of a mixed-method of Data Collection. It is an advanced process of systematic integration where both the qualitative and the quantitative process is being done in a single investigation process, or there can be seen the data inquiry process is being sustained. This process can be seen as a more complete and synergetic utilization of the data in a single process.

In the mixed method, both the qualitative and the quantitative data are being collected; in other terms, it can be said that both the numeric data and the word data are collected in the mixed approach of Data Collection. The data for the dissertation is mainly collected from the websites of the UK and several finance reports that are published by the companies in the UK. Some other dataset can be seen in the research papers of several researchers of the UK and from there also some of the data is being collected (Agung et al. 2019).

6.0 Dissertation Framework (Smart Art)

MAL7504-E Proposal Sample - Applied Artificial Intelligence and Data Analytics Capstone

Figure 3: Dissertation Framework

(Source: Self-Created)

7.0 Project Plan (Gantt chart)

MAL7504-E Proposal Sample - Applied Artificial Intelligence and Data Analytics Capstone

Figure 4: Project Plan

(Source: Project Libre)

MAL7504-E Proposal Sample - Applied Artificial Intelligence and Data Analytics Capstone

Figure 5: Gantt Chart

(Source: Project Libre)

8.0 Conclusion

It has been selected from the above section that artificial intelligence for the translation of human cognition into computers may be utilized to improve the performance of both the simple and the complex job associated with any business structure. The fundamental purpose associated with artificial intelligence is to learn reasoning and two diverse jobs.

Implementation of AI within the business structure always encourages advancement and improvement in the business structure and enables it to gain opportunity by adopting Technical Advancement. The artificial intelligence process includes a substantial amount of data intake. AI systems may be able to handle massive amounts of data. This system can extract specific facts from a large quantity of data and adjust it to the needs of the user.

This concentrated research has taken it with proper aims and objectives, which will enable the researcher to find out the requirements to answer the state equation associated with this research. This will also enable the researcher to gather information regarding different theories of advertisement where AI is used to stop it. It will also find out the different ways of using air in the advertisement as well as in the marketing processes.

Headings and Sub-headings

  1. Introduction

1.1 Introduction

1.2 Background of the study

1.3 Research Rationale

1.4 Research Aim

1.5 Research Objective

1.6 Research Questions

1.7 Research Hypothesis

1.8 Research Significance

1.9 Research Framework

1.10 Conclusion

  1. Literature Review

2.1 Introduction

2.2 Conceptual Framework

2.3 Concept Of Dependent and Independent Variable

2.4 Empirical Study

2.5 Factors

2.6 Literature Gap

2.8 Conclusion

  1. Methodology

3.1 Introduction

3.2 Research Philosophy

3.3 Research Approach

3.4 Research Design

3.5 Data Collection

3.6 Ethical Consideration

3.7 Research Limitation

3.8 Conclusion

  1. Data Analysis

4.1 Implementation

4.2 Testing

4.3 Evaluation

4.4 Results

4.5 Recommendation

  1. Opportunities
  2. Constraints
  3. Conclusion

7.1 Introduction

7.2 Linking with Objective

7.3 Recommendation

7.4 Future Research

7.5 Conclusion

Reference List


Reference List


Agung, N.F.A. and Darma, G.S., 2019. Opportunities and Challenges of Instagram Algorithm in Improving Competitive Advantage. International Journal of Innovative Science and Research Technology4(1), pp.743-747.

Aithal, P.S., 2019. Information Communication & Computation Technology (ICCT) as a Strategic Tool for Industry Sectors. International Journal of Applied Engineering and Management Letters (IJAEML)3(2), pp.65-80.

Aoun, J.E., 2017. Robot-proof: higher education in the age of artificial intelligence. MIT press.

De Bruyn, A., Viswanathan, V., Beh, Y.S., Brock, J.K.U. and von Wangenheim, F., 2020. Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing51, pp.91-105.

Ge, J. and Gretzel, U., 2018. Emoji rhetoric: a social media influencer perspective. Journal of Marketing Management34(15-16), pp.1272-1295.

Higgins, D. and Madai, V.I., 2020. From bit to bedside: a practical framework for artificial intelligence product development in healthcare. Advanced Intelligent Systems2(10), p.2000052.

Kose, U. and Sert, S., 2017. Improving content marketing processes with the approaches by artificial intelligence. arXiv preprint arXiv:1704.02114.

Lu, H., Li, Y., Chen, M., Kim, H. and Serikawa, S., 2018. Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications23(2), pp.368-375.

Maedche, A., Legner, C., Benlian, A., Berger, B., Gimpel, H., Hess, T., Hinz, O., Morana, S. and Söllner, M., 2019. AI-based digital assistants. Business & Information Systems Engineering61(4), pp.535-544.

Melnychenko, O., 2019. Application of artificial intelligence in control systems of economic activity. Virtual Economics2(3), pp.30-40.

Miklosik, A., Kuchta, M., Evans, N. and Zak, S., 2019. Towards the adoption of machine learning-based analytical tools in digital marketing. IEEE Access7, pp.85705-85718.

Overgoor, G., Chica, M., Rand, W. and Weishampel, A., 2019. Letting the computers take over: Using AI to solve marketing problems. California Management Review61(4), pp.156-185.

Paschen, J., Kietzmann, J. and Kietzmann, T.C., 2019. Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing.

Paschen, U., Pitt, C. and Kietzmann, J., 2020. Artificial intelligence: Building blocks and an innovation typology. Business Horizons63(2), pp.147-155.

Soltani-Fesaghandis, G. and Pooya, A., 2018. Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry. International Food and Agribusiness Management Review21(1030-2019-593), pp.847-864.

Vishnoi, S.K., Bagga, T.E.E.N.A., Sharma, A.A.R.U.S.H.I. and Wani, S.N., 2018. Artificial Intelligence enabled marketing solutions: A Review. Indian Journal Of Economics & Business, pp.167-177.

Weber, F. and Schütte, R., 2019. A domain-oriented analysis of the impact of machine learning—the case of retailing. Big Data and Cognitive Computing3(1), p.11.

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