Management approaches in the field of smart
Hosein Rahimi kolour; Rahim Mohammad khani
Abstract
The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising ...
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The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising and sales, professionals now have the tools to completely redefine the current understanding of branding, marketing, advertising and sales. The growing popularity of the Internet and the increased use of mobile devices are generating massive amounts of consumer data that feed artificial intelligence-based systems. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. In the qualitative part, the tools for collecting information were library and articles review, interviews, and in the quantitative part, questionnaires. In the qualitative part of the data analysis method, using the theme analysis that was compiled with MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. According to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales. The findings of the research can have important results for marketers and activists in the field of advertising and sales. Among the consequences of the application of artificial intelligence and machine learning, we can mention things such as understanding, recognizing and revealing consumer needs and desires, classifying target advertisements, intelligent evolution of commercial advertisements, innovation in sales, development of sales channels, and optimization of the fields of using artificial intelligence in advertising agencies Keywords:: artificial intelligence, machine learning, big data, advertising and salesIntroductionMost of the research on the use of artificial intelligence and machine learning in advertising and sales has been done in the last four years. The gap between AI research, the application of AI and machine learning in advertising and sales is still significant. Theoretical findings still need to be supported by real tools and software solutions. In the academic context, most researchers either focus on describing one or two of the newest solutions available on the market or mention very generalized application areas and focus on AI as a phenomenon and the main object of study. There is little research on the results of the general implementation of artificial intelligence in advertising and sales and the results of the implementation of specific artificial intelligence tools. Studies have been conducted on the applications and challenges of the application of artificial intelligence and machine learning in marketing, international marketing and marketing strategies. The innovation of the current study is that despite the exponential development of artificial intelligence and related technologies, its emerging application in various production environments, none of the previous studies have addressed the consequences and results of the application of artificial intelligence and machine learning in a qualitative manner in advertising and sales; Therefore, to cover the issues raised above, we intend to answer the following research question. What areas of artificial intelligence and machine learning are used in advertising and sales? What are the existing solutions based on artificial intelligence and related technologies such as machine learning in the field of advertising and sales development and optimization? Literature ReviewArtificial intelligence is a computer science technology that teaches computers to understand and imitate human communication and behavior. Today, around the world, artificial intelligence has become a hot topic in many sciences and public discussions in society; Because it seems to expand and challenge human cognitive capacity. It is obvious that artificial intelligence will become an integral part of every business organization worldwide in the long run. One of the definitions of artificial intelligence is to teach computers to learn, reason and adapt (Bardo Eritav et al., 2020). Artificial intelligence is supposed to simulate human intelligence in order to support or even expand human abilities (Ote, 2019). In other definitions, the possession of machines with rational and human thinking and action has been emphasized (Berry Hill et al., 2019; Zahouri et al. Moghadam, 2020). Machine learning (ML) is a process that uses observations or data, such as direct experience or instruction, to recognize patterns in data without human intervention, allowing you to make better decisions in the future. The goal of ML is to enable computers to learn automatically "on their own," without human intervention or assistance, so that systems can adjust their actions accordingly. Today, most AI applications use ML in marketing activities, from personalizing product offers to helping discover the most successful advertising channels, estimating churn rates or customer lifetime value, and creating superior customer groups (Tiwari et al., 2021; Shissel et al., 2020). Compared to traditional advertising production, artificial intelligence technology has increased the effectiveness of advertising production and marketing, and has made brand marketing more humane, accurate and effective, and has improved the effectiveness of advertising communications and information call rates. Advertising production using artificial intelligence technology can categorize, combine information sources, quickly generate new ideas, and implement intelligent marketing (Deng et al., 2019). MethodologyThis research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The tools of data collection in the qualitative part of the library review were articles and semi-structured interviews with 18 managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. The method of data analysis in the qualitative section, using theme analysis, which was compiled with MAXQDA software and using the coding method. In the quantitative part, purposeful sampling with 35 digital marketing experts and information gathering through a questionnaire, the analysis method was based on Kendall's correlation test. ResultsAccording to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales. The findings of the research can have important results for marketers and activists in the field of advertising and sales. Among the consequences of the application of artificial intelligence and machine learning, we can mention things such as understanding, recognizing and revealing consumer needs and desires, classifying target advertisements, intelligent evolution of commercial advertisements, innovation in sales, development of sales channels and optimization of the fields of using artificial intelligence in advertising agencies. Discussion and ConclusionThe rapid development of modern technology, especially artificial intelligence, has led to the creation of powerful solutions to take advertising and sales to a whole new level. With the increased use of social media and the Internet, the amount of data available on customer behavior and customer communication is immense. Although research on the use of artificial intelligence and related technologies is still limited due to the novelty of the topic, this paper reviews existing research on innovation, the use of social media with AI, machine learning, and big data capabilities to provide opportunities to increase advertising effectiveness and Sales have been linked. Using artificial intelligence, it is possible to gain a clearer view of consumer behavior on social media that leads to brand preferences. Artificial intelligence-based systems that work in digital marketing environments focus on machine learning and big data techniques and use data-driven marketing strategies to guide and collect customer knowledge data and evaluate activity performance; Therefore, by using systems based on artificial intelligence and machine learning, facilitate decision-making processes, understanding user behavior and responses, innovation strategies, sales forecasting, understanding social network strategies, customer orientation and optimization of activities and strategic advertising planning in digital environments.Advertising and sales systems based on artificial intelligence can add value to the business, as well as turn the application of artificial intelligence and machine learning in advertising and sales into a sustainable strategy that can guide the steps a company takes to succeed in its marketing strategies, such as content analysis and optimization. social; performance analysis and media selection; Budget analysis and optimization; Identifying and evaluating target groups; Predicting reactions; monitoring the competition, it needs to realize; Therefore, the application and new uses of advertising and sales system based on artificial intelligence seem necessary for companies
Management approaches in the field of smart
Ghasem Zarei; Rahim Mohammad khani
Abstract
AbstractThe convergence of information technology, media and communication has changed consumer behavior in terms of searching, obtaining, processing and responding to company information or services. A company's ability to plan, implement and manage digital marketing to increase its competitiveness ...
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AbstractThe convergence of information technology, media and communication has changed consumer behavior in terms of searching, obtaining, processing and responding to company information or services. A company's ability to plan, implement and manage digital marketing to increase its competitiveness in the eyes of consumers is called digital marketing capability. The purpose of this research is to design a model for improving marketing capabilities by emphasizing the indicators of using digital marketing in industrial companies. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing of industrial companies and university professors who were selected using the snowball sampling method. In the qualitative part, the data collection tool was an interview, and in the quantitative part, a questionnaire was used to identify the categories, and a semi-structured interview was used, and a questionnaire was used to validate the model. In the qualitative part of the data analysis method, the Grounded theory approach was based on the Strauss and Corbin method, which was compiled using MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test.IntroductionThe availability of digital technologies for a growing number of companies offers new opportunities in terms of market and consumer research and analysis, as well as communicating with customers throughout the consumer life cycle and building brand awareness and loyalty. On the other hand, changes in consumer preferences and lifestyles, including the increase in time spent by consumers worldwide on digital media and their expectation of a highly personalized approach, make manufacturers' shift to digital tools a necessary condition for survival. Digital marketing strategies have been studied, however, research focused on the understanding and application of digital marketing usage indicators in digital marketing has not been analyzed and the novelty of the current study is that despite the exponential development of digital technologies and its emerging application in Unlike marketing, none of the previous studies have addressed the indicators of using digital marketing. The purpose of this study is to identify the factors influencing the improvement of digital marketing capability and to analyze a company's digital marketing usage index (DMUI) and to plan strategies derived from these indicators, as well as to identify the motivating, contextual and intervening factors to improve the digital marketing capability of industrial companies. Literature ReviewThe term digital marketing refers to almost all marketing activities that take place online. It is a collective term that includes all digital communication and advertising channels that businesses can use to communicate with existing and potential customers (Alexander, 2017) A company's ability to plan, implement and manage digital marketing is known as its digital marketing capability. It refers to a company's ability to use the Internet and other information technologies to facilitate deep customer interactions. Through these interactions, customers have access to the company's resources and information, and the company learns more about its customers. The processes, structures and skills that a company needs to succeed in the digital age are also defined as digital marketing capabilities (Chaffey, 2016). Digital transformation is a process of change that leverages technology and digital capabilities to create added value through business models, operational processes and customer experiences (Markanian, 2020). Therefore, digital transformation aims to improve entities by making significant changes in their characteristics through a combination of It is from information technology, computing, communication and connection (Viyal, 2019). Innovation Ecosystem Readiness is a measure of ecosystem readiness to accept innovation. Ecosystem interactions affect the adoption rate of organizational innovations (Wang, 2020).Adoption of digital marketing: shows the extent of use of digital marketing technology in the organization. Companies that are able to use digital marketing technology effectively tend to have higher levels of digital marketing capabilities (Wang, 2020). MethodologyThis research is a type of mixed exploratory research with a qualitative and quantitative approach, which is practical in terms of its goal. The method of data collection is, in the qualitative part, interviews, review of library documents, articles, and in the quantitative part, a questionnaire (survey). The statistical population of the research was managers and experts in the field of digital marketing of industrial companies and university professors who were selected using the snowball sampling method. In the qualitative part, the data collection tool was an interview, and in the quantitative part, a questionnaire was used to identify the categories, and a semi-structured interview was used, and a questionnaire was used to validate the model. In the qualitative part of the data analysis method, the grounded theory approach was based on the Strauss and Corbin method, which was compiled using MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. Results In this research, in order to meaningfully interpret the effective factors in improving digital marketing capabilities, personal views and personal experiences of experts, senior marketing managers in the digital field of industrial companies and university professors have been examined. Data collection was done through in-depth and semi-structured interviews with 18 people from the mentioned statistical community. It should be noted that the interview with the 13th person led to theoretical saturation and after that almost all the information and data were repeated, but for more certainty and the possibility of obtaining new data, we continued the interview until the 18th person. The interviews started in a semi-structured way by asking questions about the effective factors in improving the digital marketing capability, and the subsequent questions were designed based on the answers of the interviewees during the interview session, although certain frameworks were considered before the interview. The interview lasted approximately 40 minutes to an hour. The method of sampling in this research is judgmental (theoretical) and the interviewees were selected randomly during the research. Discussion and ConclusionThe results of the research showed that management factors in industrial companies can influence the promotion of digital marketing capability. The knowledge and expertise of the manager about the up-to-date science of marketing, the manager's belief in customer orientation, good thinking and risk-taking, creativity, management's confidence in the existence of expert human resources, financial and time resources for electronic marketing, management's enthusiastic desire to use existing and up-to-date technologies, use And having successful and related experiences in this field and ensuring the intention and decision of the management to invest in the development of digital marketing, can be considered as very important factors in the field of management. The company's strategies in terms of being customer-oriented, having clear visions for digital marketing and using communication and information technologies are very important for development in this field. Although a company's digital marketing capabilities can be achieved through one of the channels of digital marketing adoption, digital transformation, or innovation ecosystem readiness, digital marketing is about more than technology adoption. It is also about strategies for integrating technology into business processes. Digital transformation is the main driver of increasing digital marketing capabilities. Companies can enhance the role of managerial innovation, organizational readiness and perceived usefulness to improve their innovation ecosystem readiness. In addition, businesses must master changing and re-engineering new business models to accomplish digital transformation. Finally, in addition to implementing digital marketing through websites, social media, mobile marketing, and content marketing, the company should emphasize the importance of digital analytics, digital CRM, digital advertising, and display advertising.Although a company's digital marketing capabilities can be achieved through one of the channels of digital marketing adoption, digital transformation, or innovation ecosystem readiness, digital marketing is about more than technology adoption. It is also about strategies for integrating technology into business processes. Digital transformation is the main driver of increasing digital marketing capabilities. Companies can enhance the role of managerial innovation, organizational readiness and perceived usefulness to improve their innovation ecosystem readiness. In addition, businesses must master changing and re-engineering new business models to accomplish digital transformation. Finally, in addition to implementing digital marketing through websites, social media, mobile marketing, and content marketing, the company should emphasize the importance of digital analytics, digital CRM, digital advertising, and display advertising.Keywords: digital marketing, digital market capability, digital marketing index, industrial companies.
