Machine Learning and Artificial Intelligence in Marketing Applications During COVID-19 Pandemic

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Machine Learning and Artificial Intelligence in Marketing Applications During COVID-19 Pandemic
From the Edited Volume
Edited By:
Ljupka Naumovska


Since the outbreak of the novel SARS-CoV-2, machine learning and artificial intelligence (ML/AI) have become the powerful marketing tools to mitigate economic activities during COVID-19 pandemic. The goal of ML/AI technology is to provide data and insights so that brands can understand what’s working and what’s not. This will help marketers understand and anticipate what sort of communications work and how to deliver them. Therefore, these are such promising methods employed by various marketing providers. AI uses machine learning to adapt and make changes which impact marketing in real time. The exact impact of events such as the COVID-19 pandemic is hard to predict, but AI will help us track and anticipate these circumstances, as well as provide us with the data needed to proceed. This chapter deals with recent studies that use such advanced technology to increase researchers from different perspectives, address problems and challenges by using such an algorithm to assist marketing experts in real-world issues. This chapter also discusses suggestions conveying researchers on ML/AI-based model design, marketing experts, and policymakers on few errors encountered in the current situation while tackling the current pandemic.

Keywords:  SARS-CoV-2, COVID-19, marketing impact, machine learning, artificial intelligence.


In the current pandemic situation of coronavirus, most of the countries out there within the locked-down state. To affect things, the IT sector has started operating remotely. Here will discuss “What can Digital Company neutralize COVID-19 Lockdown?”. Since the outbreak of deadly COVID-19, the entire world is fighting against it in unison. Economies have taken a beating and business is at a halt. We will formulate our marketing Plan which can help exponential growth in terms of revenue, products, and customers.

There are several disease outbreaks that invaded humanity in World history. World Health Organization (WHO), its co-operating clinicians and various national authorities round the globe fight against these pandemics so far. Since the primary Covid-19 (Coronavirus) disease case confirmed in China December 2019 Wuhan District, the outbreak continues to spread all across the planet, and on 30th January 2020 WHO declared the pandemic as a world concern of public health emergency. The novel Coronavirus (SARS-CoV-2) disease spread on quite 185 countries infecting quite 7,145,800 individuals and causing 407,067 deaths by June 09, 2020 Economic reforms and knowledge Technology together have changed the phase of Indian business. Economic reforms have set the forces like liberalization, privatization and Globalization that have unleashed competition. Information Technology (IT) has revolutionized the character of the organization, especially marketing. During this context, many business organizations have started spending huge amounts thereon and developing marketing information systems for effective deciding. It’ll be of the interest to understand the state of the art of Machine Learning &Artificial Intelligence, data science and their effectiveness.

The economic recession caused by the recent pandemic has significantly affected consumer shopping and media habits and altered firms’ marketing activities and performance. Market research over the last decades has provided insight into how economic recessions affect consumer behaviour and the way firms should adjust their marketing mix activities in response to those macro-economic contractions. During this paper, I review the related marketing literature and demonstrate that recessionary periods may provide opportunities for marketers to grow their brand’s market share with the proper marketing-mix spending management.

A great number of companies today are confronted with a continuously changing and highly competitive environment. As a result, the worth of data increases since it becomes one among the foremost valuable assets in ranking the competitive rivalry of the fashionable markets. This, in turn, involves a scientific organization and development of Machine Learning and AI which may effectively collect, process and diffuse the required information available both to the interior and external levels.

During the recent global urgency, scientists, clinicians, and healthcare experts round the globe keep it up checking out a replacement technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning (ML) and AI (AI) application on the previous epidemic encourage researchers by giving a replacement angle to fight against the novel Coronavirus outbreak. This paper aims to comprehensively review the role of AI and ML together significant method within the arena of SARS-CoV-2 and its related epidemic. Machine learning is vital due to its wide selection of applications and its incredible ability to adapt and supply solutions to complex problems efficiently, effectively and quickly. Data is that the lifeblood of all business. Data-driven decisions increasingly make the difference between maintaining with competition and falling further behind. Machine learning are often the key to unlocking the price of corporate and customer data and enacting decisions that keep an organization before the competition. Redefining customer understanding: Connecting within the time of COVID-19 because the novel coronavirus forces people into a digital-only way of life, it’s imperative for businesses to instil virtual skills with a person’s touch.

All relationships have an emotional component — which holds true for the connection between people and makes. The business’s relationship with customers is formed over time, nourished by experiences along many connected and physical touch points in their journey, grounded in expectations, and confirmed through repeated interactions.

A crisis puts both the strengths and weaknesses therein relationship under a spotlight and therefore the coronavirus pandemic isn’t just any crisis. The “locked down” countryside of the response to the present crisis — which is forcing utmost people to be physically separated from their friends, relatives, workplace, and favourite places — is requiring organizations to adapt to a digital or remote way of doing business and is dramatically altering people’s daily experiences.

This column is that the primary during a series about changing experiences during this point of great transformation and isolation, and reimagining them to worry the importance of human connection. The opposite is changing B2B customer experience: COVID-19 catalyses big changes. The pandemic is forcing companies to specialize in experiences their clients expect, while mobilizing them to accelerate product and repair innovation. The third one here the way to create a “new normal” As workplaces, customer behaviours, and economic circumstances still change in response to COVID-19, companies should specialise in three key actions. The fourth here COVID-19 means insurers should devour the pace on improving experiences. In an industry driven and sustained by trust, the pandemic has brought both challenges and opportunities for customer and employee experience, and therefore the fifth here is Media and telecommunications’ companies must reinvent customer experience in response to COVID-19. Companies that prioritize innovation and care in redesigning customer experiences are getting to be best positioned to stay.

An experience is quite an app, some extent of sale, a website. It’s a feeling that’s created at every interaction, defining and building lasting relationships, not just with customers, but with the people who work for and support your brand every day. It’s a calling card that sets you aside from the pack. Change is everywhere. These articles offer insights into the way to deliver experiences that inspire long-term confidence, loyalty, and growth. Consumer companies must take leaps, not steps. As shoppers show how quickly they will adapt to external shocks, retailers also got to radically reconfigure their business models.

Marketing managers make decisions about products, brands, advertising, promotions, price, and distribution channels, and supported deep knowledge about customers. The outcomes of selling decisions are hooked in to the behaviour of other actors like competitors, suppliers and resellers. Furthermore, uncertain factors like the general economy, the state of the financial sector and (international) political developments play a crucial role. Marketing deciding not only refers to tactical marketing mix instruments (the well-known 4Ps), but also to strategic issues, like development and innovation and future decisions with reference to positioning, segmentation, expansion, and growth.

A bird’s eye view

S.NO Author Year Findings
1 Thórisson, Bieger, Schiffel, & Garrett 2015 Artificial intelligence referring to Artificial General Intelligence can think and work like a how human can think for executing tasks.
2 Kumar et al., 2020 AI & ML applications is able to provide solutions for marketing organisations. All machine learning enterprises face common Challenges such as the need for abundant data, development of the firm’s analytic capabilities. Change management and organizational adoption.
3 Legg & hutter 2007 Artificial intelligence will encompass understanding, Self- awareness, emotional knowledge, Reasoning, Creativity and Logical thinking.
4 Wang, Zhang, Li, Zhang, & Lin. 2016 In computer vision, a convolutional Machine learning application will typically be trained on a set of pictures of identical sizes. Likewise Take, for instance, a Machine Learning tasked with predicting whether a customer is likely to click on an online banner; it requires a clearly defined and finite set of inputs, or predictors (e.g., age, gender, time of day, inferred online visitor’s interests, and features summarizing visitor’s previous behaviour). Previously used with soft computing methods for execution of all the tasks.
5 Michael Polanyi 1996 The marketing literature teaches us that an organization can only achieve successful tacit knowledge transfer through shared Experience and proximity. Consequently, marketing organizations should seek to facilitate and systematize interactions between AI and marketing stakeholders, and create an ecosystem to foster a form of “intimacy” between AI and experts (or) consumers) through two-way observation, imitation, and Practice.
6 Tantawy and George, 2016 This is another result associated with the Evolution of Internet, which has led to the concepts of Internet marketing, digital marketing, social media marketing…etc. Currently, content marketing is often used for achieving marketing purposes over especially Web platform of Internet.
7 Utku KOSE, Selcuk SERT 2017 artificial intelligence can be used in order to make everything better for content Marketing of a company. Some of them are forecasting, optimization, expert support, adaptive guidance (for customers / users), and fixing mistakes (detected along marketing process).
8 Keng Siau, Yin Yang 2017 The field of sales and marketing has been impacted by advanced technologies and this impact will magnify significantly in the near future. AI, robotics, and machine learning will undoubtedly accelerate the impact. Robots will replace sales people and marketers in the near future (if not already). Websites can update automatically based on the usage and website pages can be reformatted automatically based on eye-tracking data. With AI and machine learning, segment-of-one marketing will be possible.
9 Martínez-López & Casillas 2013 Intelligent systems have particular potentialities and strengths to support decisional situations faced by companies, especially those of a strategic nature, where good strategic intelligence is necessary.
10 Kumar, Rajan, Venkatesan… 2019 artificial intelligence (AI) in aiding personalized engagement Marketing—an approach to create, communicate, and deliver personalized offerings to customers. It proposes that consumers are ready for a new journey in which AI is a tool for Marketing.


2.1. Research Gap

From the above Literature Review it can be concluded that marketing activities are increasing in complexity at an accelerating pace during the covid-19 pandemic. Marketing activities, as a class is more difficult to model than other business communication, Market research, leads to data generation, and decision making. Many of the methods that are developed for modelling the marketing decisions are inadequate when checked with world results.

2.2. Research Problem

Since the marketing is more than selling and promoting, marketing information system is useful for the Services Industries, especially large ones in-order to get the firm to higher ranks. So the research problem is finding whether services industries in India are effectively using Machine Learning and Artificial intelligence (or) not for marketing purpose during Covid-19 pandemic.

2.3. Objectives of The Study

  1. Identifying the underlying dimensions of marketing activities with ML, AI & Data Science.
  2. ML, AI and Data Science impact on Marketing Functions.

2.4. Research Methodology

2.4.1. Type of study

  • The survey was conducted with the help of structured questionnaire.
  • The study uses a descriptive research method.

2.4.2. Sampling Method

In this study Survey method is implemented to collect the information from the respondents and distributed to the Marketing executives in Service and electronic appliance industry. The data has been collected through mail survey and personal interview method which is employed through Stratified Sampling Technique.


Table 1.

COMPONENTS Factor loadings
COMPONENT -1   Market Analytics (Analysing Marketing Opportunities)  
Uses latest S/W .738
Helps to make projections of competing products market share .663
AI & ML helps in regularly analysis and report Market research data to managers. .629
Helps to prepare long term forecast of industry sales. .605
Use to help to estimate the company’s market share. .599
Provides data can be easily used. .556
Arrange production to promotional point of scale literature. .542
Quality of information provided during service is good. .531
Helps to prepare Annual sales forecasts. .514
Provides accurate data.  
COMPONENT -2   Managing and delivering marketing strategy  
Control advertising and promotional budget. .699
Helps to prepare marketing department annual Budget .651
Helps to implement approval plans and programs .650
Helps in product differentiation .547
Coordinate activities among functional groups .539
Liaise with the advertising agency & social media .528
COMPONENT -3   Designing new marketing system and managing services  
 Is flexible to change . 770
 Is compatible with organization Transaction processing system 757
 Is demanding customer solutions with quality .693
COMPONENT –4   Product MIX  
 Helps to coordinate elimination of obselence . 726
 Analyses marketing activities. .702
COMPONENT -5   Developing new market offerings  
Coordinates for effective new product launches .788
Improves internal communication. .620
Allows individual marketing projects .539
COMPONENT -6   Market Measurement and Forecasting  
Determine value of future income streams. .617
Develops long term strategic marketing plan. .614
Helps to the organization in marketing data analysis. .560
Employ portfolio analysis in assessing performance. .524
COMPONENT- 7   Marketing information system  
Provides information to headquarters for decision making 760
Asses market size .635
COMPONENT -8   Techno functional Effectiveness of Marketing  
Helps in providing customer service levels .640
Processing speed is high .632
Used latest H/W . 532
COMPONENT 9   Measuring market segment and brand performance.  
Prepare forecasts of company sales by market segment. .570
Establish brand performance criteria .443
Extraction Method: Principal Component Analysis. 


Rotation Method: Varimax with Kaiser Normalization.

Total variance explained: 64.553%



Table 1 reveals that the first factor termed as Market analytics (Analyzing market opportunities) consists of 10 variables which are AI and ML uses latest software, it helps to make projections of competing products market share. AI & ML helps in regular analysis and providing market research report data to managers, it helps to prepare long term forecast of industry sales.AI & ML uses to help to predict the company’s market share, it arranges production to promotional point scale literature, quality of information, annual sales forecast and accurate data shown with a factor loading from 0.738 to 0.514 respectively.

The second factor is named as Managing and delivering marketing strategy consisting with following variables, AI & ML helps in controlling marketing budget, it helps in prepare marketing department annual budget, helps to implement approval plans and programs. AI & ML helps to implement in product differentiation, coordinating activities among functional groups and liaise with the advertising agency & social media. Factor loadings are from 0.699 to 0.528.

The third factor is defined as Designing new marketing system. It consists of three variables, AI & ML is flexible to change (0.770), compatible with organization transaction processing system (0.757), demanding customer solutions with quality (0.693).

The fourth factor is termed as Product mix. It consists of the following variables: AI & ML helps to eliminate older products; it helps to analyses the marketing activities with the following loads are (0.726) and (0.702)

The fifth factor is defined as Developing New Market Offerings. It consists of three variables.AI & ML coordinates for effectively launching new products, improves internal communication between the departments and within the department, and it allows individual marketing projects.

The sixth factor is explained as market measurement and forecasting. it consists the following variables determine future income streams (0.617), Develop long term strategic plan (0.614), helps to the organization in market data analysis (0.560), and its asses and employs product portfolio and measure market performance.

The factor seventh is Marketing Information System associated with two variables, AI & ML provides market information to headquarters and it helps to assess the market size.

Techno Functional effectiveness is eighth factor. It consists: AI & ML helps in providing customer service levels (.640), it uses latest hardware (.632) and its processing speed is high (.532).

The ninth factor is known as measuring the Market segment and Brand performance considering the following variables AI & ML forecast company sales by market segment    (-.577) and measuring the brand performance criteria (0.433)

Table 2.
Role on marketing during covid-19 pandemic using AI & Machine Learning  

Factors Constant. b X1 X2 X3 X4 X5 R R2 Adjusted R2 Error of model estimation
Market Analytics 3.019 0.006 0.069 *0.433 0.121 0.088 0.237 0.056 0.051 0.137
Managing and delivering marketing strategy 4.399 0.074 -0.014 -0.028 0.091 *0.201 0.161 0.026 0.028 0.096
Designing new marketing system 3.709






0.094 0.133 0.139 *0.309 












Product mix 4.435 -0.024 0.311 0.012 -0.052 *0.211 0.156 0.024 0.019 0.103
Developing new market offerings 3.925 *0.274 0.125 0.030 -0.026 0.142 0.268 0.072 0.066 0.077
Market measurement & forecasting 3.711 0.108 0.084 -.023 -.037 0.112 0.195 0.59 0.67 0.105
Marketing information systems 4.271 -0.083 *0.270 0.152 0.083 0.046 0.192 0.037 0.031 0.107
Service assurance 3.698 0.125 *0.330 0.105 -0.023 -0.001 0.270 0.073 0.067 0.091
Market and brand performance 2.786 0.025 -0.017 *0.508 0.086 -0.022 0.387 0.150 0.145 0.094


X1: Machine learning,

X2: Artificial intelligence

X3: Data science

X4: Compatibility

X5: Flexibility

*:     Predictor variables for independent factor

R:    Linear correlation

R2:   Co-efficient of determination

Examination of multiple regression analysis were evolved with predicted dynamics of Machine Learning, Artificial Intelligence and data science, compatibility and flexibility impact on marketing functions during covid-19 pandemic has shown in above table.

The component 1 Market analytics reveals that the component depends on data science than other variables.

Managing and developing marketing services are the predominant area in marketing functions. Marketing your business online can be challenging. Every business needs a different strategy and each strategy requires different marketing techniques. On top of this, each technique requires time and experience as well as skilled organization so it works as a part of the entire marketing strategy. A managed marketing approach to business promotion is a cost-effective solution that includes all the elements required to have a successful marketing strategy. Managing and developing services depends a variable on flexibility.

Designing new marketing system and managing services Savvy services marketers must recognize three new services realities: the newly empowered customer, customer coproduction, and the need to engage employees as well as depends on the variable viz; flexibility.

The Product Mix also called as Product Assortment, refers to the complete range of products that is offered for sale by the company. The right product mix is predicted during covid-19 pandemic by Artificial intelligence.

Planning and implementing a growth strategy to develop new markets and expand business before current market flattens out will not only help your business survive tough times, it could also give a considerable edge. Developing new market offering factor is predicted by Machine Learning.

Market measurement: The main aim for market measurement is to aid marketing management to understand market or sales potential which is relevant to a specific geographical area, period of time, products and market segments. Artificial intelligence and machine learning will help you to understand the market potential by studying the market share, size and growth by customer segments and products Forecasting: In today’s fluid business environment, managers need the most reliable prognostic information about emergent trends, “what if” scenarios and they need it early enough to provide ample time to prepare and react. Machine learning and Artificial Intelligence provides adaptable solutions that can be customized to either a client’s technology platform or seamlessly integrate with industry specific technology. By leveraging an understanding of business requirements, industry challenges, and macroeconomic factors—and applying advanced statistical and econometric techniques—we are able to establish an appropriate forecasting framework, execute on the collection and analysis of the latest prognostic data, and rapidly reassess go-forward conditions as new inputs become available.

AI and marketing functionalities are evolving at the speed of a blink. And AI technologies revitalizing old ideas to enhance the systems in marketing functionalities to perform optimized operations. AI is the stepping stone for the marketing industry to transform their systems into intelligent ones for scaling marketing functionalities. Automation and optimization are the core functionalities of AI in Marketing.

Today’s network operators are undergoing vast digital transformations to help shape their roadmaps for future innovation. That includes transforming existing communication networks to more virtualised environments and preparing for 5G. Assuring quality of existing and future services becomes both more challenging and more critical to these operators as the competition heats up. Customers demand affordable and excellent quality on-demand, ready for anything they want to do—both at the business and residential level. That makes service quality in today’s world a challenge. Leveraging the latest advancements in Machine Learning and Artificial Intelligence, will become imperative for today’s operators to continuously assure their networks in a dynamic environment. Choosing the right service assurance solution to adapt to these needs is critical. Optimising and managing complex marketing problems with Artificial Intelligence and Machine Learning

Today’s AI driven service assurance solutions are offering predictive analytics tools, and invaluable business and network intelligence to its users. Spotting problems before they occur saves significant time and resources that both improve customer experience and prevent or reduce expensive down time.

Increasing demand for automated services, intelligent responses, smarter solutions and rapid data analysis have paved way for Artificial Intelligence to be a part of every business sector. Customers today get personally involved in the entire buying process. They want the right product at the right time. With multiple options and sellers, customers can easily leave switch sellers. To help in retaining customers, AI allows marketers to create personal experiences by identifying customer needs, segregating them and giving them appropriate options to choose from. This will also allow marketers to attract new customers and generate more leads because by using AI-enabled tools marketers can now push the right content to the right customer at the right time.

Measuring Market segment performance: the process of categorizing large volumes of customers/consumers into different groups. The customers who are grouped together show some similar characteristics like gender, preferences, age, location, ethnicity etc. This grouped data is further used to send targeted marketing campaigns through personalized messaging. Artificial Intelligence further helps in dividing these groups into individual buying personas depending upon past behaviours of the customers. This means by knowing the customer better, marketers can send more relevant messages to the customer, which in turn increases the response rates and overall profits. Personalized messaging gives the buyer a personal touch as he/she thinks that the product is being specifically sold to him/her and feels like buying it.


Machine learning methods are powerful tools for data mining with large noisy databases and give researchers the opportunity to gain new insights into consumer behaviour and to improve the performance of marketing operations. To model consumer responses to direct marketing, this study proposes Bayesian networks learned by evolutionary programming. Using a large direct marketing data set. As consumer expectations grow for more personalized, relevant, and assistive experiences, machine learning is becoming an invaluable tool to help meet those demands. It’s helping marketers create smarter customer segmentations, deliver more relevant creative campaigns, and measure performance more effectively.

Technological advancements have revolutionized the way businesses plan and execute their strategies. Technology has been able to help businesses learn more about their target audience far beyond what they thought possible. Bringing forth both benefits and big changes, technology such as artificial intelligence has become a game changer for marketers and marketing strategies. Marketers are using what is known as artificial intelligence marketing. AI Marketing is a method created to gather, analyse, and store consumer data to help anticipate consumer trends and execute the appropriate strategies to garner the right consumers. Artificial intelligence brings forth many benefits and changes when incorporated in marketing.

According to a study of 100 Senior Marketers done by, “55% of companies are either currently implementing or actively investigating some form of AI initiative,” demonstrating their confidence in AI. AI, the marketing strategy will become more effective. Effective marketing strategies tend to show the right content to the right person at the right time through the appropriate communication channel. The use of artificial intelligence marketing allows marketers to reach potential customers and give them easy access to make purchases. Another benefit is the efficiency that AI contributes to marketing. AI’s high capacity to gather large amounts of data and analyse it in a short period of time, helps businesses save time and money.


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