Role of AI for application of marketing teaching

Abstract

With the arrival of the era of artificial intelligence, based on the problems existing in the teaching process of marketing specialty, combined with the future business development trend and the core needs of enterprise operation, this paper analyzes the system reform of the practical courses of artificial intelligence and marketing specialty. With the rapid development of computer technology, intelligence has gradually become an important means to solve problems in various industries. In this paper, the modern media as a means, marketing teaching in Colleges and universities as the research background, through the establishment of the depth of marketing in Colleges and Universities Based on artificial intelligence network research learning platform, build a post-modern media communication perspective system. Based on probabilistic neural network and from the perspective of modern media marketing application system construction, the paper proves that the artificial intelligence prediction based on probabilistic neural network has good convergence, fault tolerance and data processing ability through MATLAB. Finally, this paper takes the pricing strategy in marketing as an example, and focuses on the application of artificial intelligence technology in marketing teaching from four aspects: preparation before class, implementation in class, consolidation after class and marketing teaching examination. According to the function and application of the theory of artificial intelligences in marketing teaching, we can find out that teachers must deeply understand the situation of each student’s artificial intelligences, so as to use the theory of artificial intelligences to change the traditional view of students and talents, and teach students according to their aptitude, so as to achieve better teaching effect.

Keywords

Artificial intelligence technology marketing marketing teaching creativity individualized teaching

1 Introduction

As a market-oriented marketing major, it is always in the wave of change. Economic development drives the prosperity of the market [1]. A thriving market needs smooth commodity circulation channels, which requires a large number of high-quality marketing talents. What is high-quality and high skills is also determined by the market needs [2]. Therefore, this paper chooses marketing major as the research object, also because of its particularity and representativeness. As one of the most closely related majors with the market, it is of certain significance to discuss it as the goal for the research of talent training direction and Countermeasures of such major. In short, the problem of talent training is one of the most concerned problems in Colleges and universities. It is very important to improve the quality of education and solve a series of problems such as employment. Therefore, it is of great theoretical and practical significance for college education to select this topic [3]. On the one hand, the thesis enriches the relevant theoretical basis of talent training in higher vocational colleges. Starting from the theory of human capital and labor market supply and demand, it probes into the positioning of talent training in marketing specialty, and probes into it from the dual perspectives of pedagogy and economics, so as to provide theoretical basis for the transformation of talent training in Colleges and universities to market demand [4]. On the other hand, it has a strong practical and practical significance to pay attention to the quality of employment and talent training that the marketing specialty pays attention to. It extends from the employment problem to the transformation of training objectives, and then to specific practice suggestions, which also has a strong practical significance in guiding the cultivation of marketing professionals in Colleges and universities [5].

Marketing is an important professional basic course with strong theory. It is not easy for most students who are tired of learning and have poor foundation to learn it well. Therefore, how should teachers teach, what methods and means should be adopted in teaching, and how can students’ enthusiasm for learning be fully aroused so that they can actively learn and receive good results? This is in the face of marketing teachers The first problem. Under the guidance of the theory of artificial intelligences, this study conducts an experimental study on marketing teaching activities in Colleges and universities [6]. Its main purpose is to verify whether college marketing guided by the theory of artificial intelligences can improve students’ learning attitude, to demonstrate the application effect of the theory of artificial intelligences in college marketing teaching, so that more teachers can see the impact of the theory on marketing teaching, realize the necessity of developing students’ artificial intelligences, and fully consider students in the teaching process [7]. In order to help students build up the confidence of marketing, arouse the enthusiasm of students in class, improve their learning attitude, and enhance the practical achievement of marketing.

2 The development of artificial intelligence technology and marketing teaching

2.1 Development of artificial intelligence technology in marketing

According to the data of the National Bureau of statistics, in 2018, the national marketing turnover reached 31.63 trillion yuan, including 30.61 trillion yuan for goods and services [8]. In 2018, the contribution rate of China’s service industry to GDP growth reached 59.7%. As an important part of modern service industry, the marketing service industry continues to maintain a steady growth trend, the market scale continues to expand, the market structure is further optimized, and new technologies, businesses and models continue to emerge, which has become an important driving force to promote the integration of marketing and industry [9]. In 2018, China’s marketing service industry continued to maintain steady growth, and the market scale further expanded. The annual operating revenue of the marketing service industry was 3.52 trillion yuan, an increase of 20.3% year on year. China’s marketing service industry has supported 31.63 trillion yuan of marketing transaction volume. The marketing service industry, such as transaction service, information technology service, advertising creativity, marketing logistics, intelligent marketing, consultation and training, has become increasingly diversified and specialized, and constantly promotes the innovative development of marketing [10].

With the in-depth application of big data and artificial intelligence, marketing is gradually realizing precision marketing, intelligent marketing and creating greater business value. According to AI media consulting data, in 2017, China’s Internet advertising market scale reached 30.1 billion yuan, and in 2018, it reached 350.9 billion yuan, a year-on-year increase of 16.6%; in 2020, it is expected that China’s Internet advertising market scale will reach 441.48 billion yuan, and the proportion of mobile advertising will continue to rise, known as the mainstream [11]. 76.5% of Chinese mobile Internet users said that the Internet was the main channel for them to contact with marketing advertisements, while the influence of traditional media gradually declined. With the rapid development of the marketing industry, the marketing war in the industry continues to be hot, and the information exposure rate of the marketing industry remains high among the netizens. The marketing based on big data and artificial intelligence effectively realizes personalized, precise, intelligent and interactive marketing. The three effects of big data marketing and intelligent marketing are also relatively recognized by Chinese netizens.

With the popularity of smart phones and the deep coverage of the logistics industry, the serious shortage of marketing talents began to highlight [12], among which the most popular is marketing technical service talents. As a strategic emerging industry of the country, the marketing specialty has played an important role in leading the change of business model, optimizing industrial transformation and upgrading, improving the demand for information consumption, promoting the development of modern service industry and information economy, becoming a new driving force for economic development, and providing a new space for mass entrepreneurship and innovation. As an industry application-oriented, subject integration and model innovation major, the experiment, practical training and practice teaching are the necessary teaching contents throughout the whole process of marketing undergraduate teaching. There are many employment opportunities for college graduates majoring in marketing. They can be engaged in website design, website maintenance, network editing, enterprise commodity marketing planning, customer management, marketing management, marketing activity planning and operation, market marketing system development and maintenance, etc.

2.2 Marketing technology under the background of artificial intelligence

Teachers lack practical experience and the ranks of practical teachers are not perfect. Under the background of artificial intelligence, China is in a critical period of rapid economic development and continuous innovation of the real industrial structure and production mode [13]. In the current innovation period, new requirements are put forward for posts in the industry. The demand for innovative, compound and productive talents is increasing rapidly. Teachers of marketing major are generally rich in theoretical knowledge and lack of practical experience. This leads to the fact that the teachers of marketing can’t teach the practical cases for the students, and spend most of their time on the simulation teaching software, which deviates from the progress and development of the technology of the times.

The practical curriculum system is unreasonable. The practice teaching content of marketing specialty in Colleges and universities is not systematic. Most of the practical teaching resources in the school depend on the marketing simulation trading software or the skill contest software designated by the state or province. However, because the software itself is separated from the actual business environment and the teachers themselves seldom participate in the actual operation and management of the enterprise, the students cannot feel the practical application in the actual work. There is a big gap between the requirements of the training objectives of application-oriented talents, which makes it difficult for students majoring in marketing to realize the effective docking of “Courses” and “posts", and to grow into “productivity” talents based on the global advanced application science and technology environment in combination with the business development trend.

The construction of marketing technology training platform is not strong. The practical teaching platform of marketing major in Application-oriented Undergraduate Colleges cuts the complete “marketing ecological framework” into the “scattered experiment” layout, that is, multiple single point scenes are distributed and unrelated, which can not realize the real-time update and one-way interaction of the experimental environment, and basically focuses on the domestic Internet media resources, which is not conducive to the systematic teaching of marketing major in application-oriented undergraduate colleges One belt, one road, cross border marketing technology service personnel training is also extremely harmful.

2.3 Training mode of marketing technical service talents

We will improve teachers’ practical skills and build a “double teacher” teaching staff. The application-oriented colleges and universities should actively innovate the training mode of marketing technical service talents and improve the practical skills of teachers. Regularly organize marketing professional teachers to participate in the practical activities of enterprises, improve teachers’ understanding of practical skills, and increase teachers’ working experience in enterprises. Application-oriented undergraduate colleges can also hire senior managers and professional technicians to teach in schools, promote the communication and exchange between school teachers and enterprise personnel, and improve the practical skills of teachers.

Reform the teaching system of marketing major and increase the courses of marketing technology. In order to cultivate marketing talents in line with the future business development trend and the needs of industrial enterprises, application-oriented undergraduate colleges need to strengthen cooperation with enterprises, and constantly reform the training system of marketing technical service talents. Regularly invite excellent personnel of enterprises to teach in Colleges and universities, and promote the application-oriented undergraduate colleges to better improve the teaching system of marketing. On the basis of the traditional teaching of marketing, we should increase the courses of marketing technology, cultivate the talents of marketing technology service for the core needs of enterprise operation, and build the talent training mode of education and training integration.

Build a high-level training base of digital intelligent marketing for new business marketing. Through school enterprise cooperation, we signed a strategic cooperation agreement with treasure island group, introduced the “treasure island” intelligent marketing training technology platform, and built a global, network wide, domain wide, process wide, data-based, automatic and ecological real marketing scene oriented marketing production and education integration innovative training base. Through the links of production, learning, research, teaching, learning and doing, to realize “two-way interaction, real-time update and real work scene", which will bring positive promotion to teaching optimization, application-oriented personnel training guarantee and innovation and Entrepreneurship of students [14]. This paper analyzes the requirements and specifications of professional enterprises for marketing technical service personnel, and carries out a series of cooperation around the construction of marketing digital intelligent marketing major, including the construction of curriculum resources, the construction of “double qualified” capital team, the construction of off campus practice base, etc., which can meet the needs of the construction of marketing technical service discipline in the school, while serving the local market Small and medium-sized enterprises, including export-oriented production enterprises and emerging industries such as cross-border marketing.

Insist on promoting the connection between specialty and industry, systematically design the practical training teaching system, integrate the practical training resources inside and outside the school, make full use of the advantages of network technology and digital resources, introduce the real projects of the industry, insist on the combination of teaching and practical combat, and cultivate the core mainstream media resources with solid professional foundation, proficient basic skills, strong practical ability, innovative spirit and understanding of global overseas Promotion mode, with the export-oriented enterprise digital marketing multi-channel overseas social media account management, real-time data perspective and intelligent report management capabilities of marketing senior application talents.

3 Introduction of marketing system model based on artificial intelligence technology

3.1 Neural network model

From the perspective of modern marketing teaching system, colleges and universities have made in-depth research on the learning system based on neural network, with the help of quantitative data, so as to realize the understanding of marketing system, social relations, modern rational quantification, rationality, knowledge system, values, through neural network learning and training [15]; the next step is to determine the results according to information processing, Predict the development trend, and put forward the corresponding methods: including the appropriate reform of the dynamic adjustment of the teaching methods of Ideological and political courses in Colleges and universities, the role of demonstration, the reasonable application of network media, the exemplary role of students, the harmonious construction of campus culture and other measures [16]. BP neural network is a kind of bionic algorithm, which has two main characteristics: the first is information transmission, the second is error back-propagation, there is no interaction between neurons and change the value with the genetic effect, repeated until the required error, the training meets the expected proportion range matrix.

As shown in Fig. 1 is the structure diagram of the neural network, where X₁, X₁, . . . , X_n represents the input value of forward propagation, Y₁, Y₂, . . . , Y_m represents the value of back propagation, w_ij and w_ik represent the parameters of back propagation. The back-propagation neural network represented in this figure is a nonlinear function, the independent variable is the input value of the network, and the dependent variable is the output value of the network. A function from n to m dimension is constructed. Using neural network to realize system data standardization and network intelligence, the implementation steps are as follows [17]:

Fig. 1

Structure of neural network.

Step 1: Network initialization. According to the type, the (X, Y) algorithm determines the number of nodes n, the number of hidden layer nodes L, and the number of printing layer nodes M. The connection and scale a between the type layer w_ij and the print layer w_ik neurons, the invisible layer range B, the print range and the given access rate are initialized.

Step 2: Hide layer output. According to matrix X, Y, the type of node number n is determined, and the contact connection between layer w_ij and w_ik range is used to calculate the proportion of output h of hidden layer. $H_{j} = f (\sum_{i = 1}^{n} w_{ij} x_{i} - a_{j}), j = 1, 2, . . ., l$ (1)

Step 3: Printout. The output h, B predicted by evolutionary algorithm is 0. $O_{k} = \sum_{k = 1}^{l} H_{j} w_{jk} - b_{k}, k = 1, 2, . . ., m$ (2)

Step 4: error calculation. According to the prediction of output 0 and expected output y, the prediction error e is calculated. $e_{k} = Y_{k} - O_{k}, k = 1, 2, . . ., m$ (3)

Step 5: updated scale. Based on the e-prediction error update algorithm w_ij and w_ik. Where is the learning rate.

Step 6: update scope. Update the range a, B according to the prediction error E.

Step 7: determine whether to end. If the standard is not met, return to step 2.

This neural network is a parallel algorithm based on probability theory, which has many advantages, one is classification ability and multi-dimensional processing ability [18]. PNN is a feed-forward bionic algorithm. Its theory is based on Bayes minimum risk criterion. The algorithm is developed from a radial basis and is very suitable for pattern recognition.

3.2 Model implementation

There are some problems in neural network modeling. The selection of feature vector must reflect the characteristics of the problem correctly. It is very important to contain enough information in the function. It is necessary to establish a learning system in the neural network and add the quantification of data processing, so as to realize the reasonable and quantitative understanding of social relations, modern rationality, knowledge system and values through the neural network learning and training. The next step is to predict the development trend according to the information results, and then put forward the corresponding countermeasures. The input eigenvector of bionic algorithm is social relationship, marketing strategy, knowledge system and value concept [19].

The collected 33 * 4 dimensional matrix data, before selecting multiple (such as 23) samples, is used as network training samples, and some (such as 8) samples are selected as verification samples. The input layer of neural network adopts three ratio method, and the output is the result of system simulation and recognition. The code of simulation type corresponds to Table 1.

Table 1
Corresponding coding table of simulation result type

Types of prediction Coding

Most worst 1

Ever worst 2

Common used 3

Good 4

Excellent 5

Types of prediction	Coding
Most worst	1
Ever worst	2
Common used	3
Good	4
Excellent	5

Based on the bionic algorithm of the classification and prediction model of Ideological and political culture system in Colleges and universities from the perspective of modern media, a two-layer network algorithm - Classification layer (cluster) and competition layer is established by MATLAB. PNN network creates a direct function provided by net = newpnn MATLAB (P, t, spread). As mentioned above, input vector and threshold processing are completed after input to the function [20]. Figure 2 shows the fault tolerance diagram of algorithm sample training. After loading the data, select the type of print matrix, and then convert the required classes into vectors. In this paper, the algorithm aims to train the network. If the results are consistent with the use of built-in functions, the implementation results are as follows. In the depth research of intelligent bionic algorithm, there are two factors that limit the accuracy of the algorithm. One is the number of training data, the other is the selection of s value. According to the research results [21], the more samples there are, the more types there are, the more accurate the prediction results. Through simulation and literature research, it is shown that the convergence speed of BP neural network is stable and the additional fault tolerance of samples needs to be improved. The algorithm is robust to the above problems. The prediction results are shown in Table 2.

Fig. 2

Fault tolerance diagram of algorithm sample training.

Table 2

Corresponding coding table of simulation result type

Number of predicted	Results of prediction	Actual classification	Ground-truth
1	5	5	5
2	1	1	1
3	4	4	3
4	5	5	5
5	3	3	3
6	3	3	3
7	4	4	3
8	3	3	3
9	3	3	3
10	1	1	1

4 The application of artificial intelligence technology in marketing teaching

Pricing strategy is a very important strategy in marketing 4Ps. It is a key and difficult point in marketing teaching. According to Gardner’s theory of artificial intelligences, our classroom teaching arrangement of pricing strategy includes four parts: pre class preparation, classroom implementation, after class consolidation and marketing. Figure 3 shows the application of artificial intelligence technology in marketing pricing strategy.

Fig. 3

Application of artificial intelligence technology in marketing pricing strategy.

4.1 Pre-class preparation of marketing teaching

As a teacher, he must understand the learning situation before class, and understand the basic situation of the students in the given class in detail. He can design some forms or questionnaires to investigate the intelligence of the students according to the eight intelligence situations of the students. For example, the following table can be used to let students evaluate their intelligence. The specific survey table is shown in Table 3, which shows the pre class preparation score of a marketing trainee.

Table 3
Pre class preparation information of marketing teaching based on Artificial intelligences

Intelligence Performance in life Personal use

Language rhetoric 8 6

Mathematical logic 9 8

Physical movement 7 9

music 6 8

introspection 7 7

Natural observation 8 6

interpersonal relationship 6 8

Visual space 8 9

Self evaluation 7.4

Intelligence	Performance in life	Personal use
Language rhetoric	8	6
Mathematical logic	9	8
Physical movement	7	9
music	6	8
introspection	7	7
Natural observation	8	6
interpersonal relationship	6	8
Visual space	8	9
Self evaluation	7.4

Before the test, the teacher should explain the eight kinds of intelligence and fill in the form, so that the students can fill in more targeted. In addition, teachers can also use their spare time to communicate with students, learn together, play together, etc., so as to better understand students’ artificial intelligences, and prepare a notebook to make a special record of each student’s strengths and weaknesses in the eight intelligences, so as to teach prisoners in teaching. It may take a lot of work for teachers to do so, but once teachers understand the situation of students’ intelligence, it will be very helpful to use the theory of Artificial intelligences for teaching in the future. Before class, there are also other arrangements for students. Teachers can group students according to different subjects and students’ intelligence, and then assign corresponding tasks to each group, such as: students in the group with strong language and observation intelligence can arrange them to go to the local shopping mall to investigate the pricing situation of crystal merchants and make records; students in the group with good mathematics and spatial intelligence can assume a new shopping mall They set prices for Shangjing [22]; the group of students with music intelligence can let them consider the price of goods from the rhythm and hearing; the students with better self-knowledge and intelligence can let them feel the price of different local shopping malls as consumers; the students with better interpersonal intelligence can let them do group organization and cooperation; the students with better physical intelligence can do the same Learning can make you run more to do a kind of Market Research on the price of new commodities in the near future. This arrangement is based on their own strengths and intelligence. Students are willing to do it, and it is relatively easy to do it. No matter how well they do it, as long as they do it seriously, teachers will reward their labor achievements with corresponding spirit or small gifts to improve students’ enthusiasm for learning.

4.2 Implementation of marketing teaching class

In the classroom, according to the preparations made by different intelligent groups before class, the teacher first asks the representatives of each intelligent group to make a report, reports the summary of the preparations made by each group before class, and makes a simple record on the blackboard, then organizes the students to analyze and evaluate the reports of each intelligent group. If there are different opinions, depending on the situation and time, several of them can be selected In the end, the teacher summarizes the basic knowledge of pricing strategy, the application of pricing strategy and the matters that should be paid attention to when pricing according to the students’ reports and the results of the debate. In the whole classroom teaching, the teacher only plays the role of leading and guiding, and should make full use of the characteristics of different intelligent students to guide, so that different intelligent students can participate in and give full play to, and timely encourage and appreciate their active participation, so that the whole classroom can participate in a wide range, live and orderly.

4.3 After-class consolidation of marketing teaching

Marketing is a very practical subject, and the knowledge learned in class is limited, so it is necessary to consolidate and further deepen the knowledge and practice after class. The teacher’s consolidation and assignment after class are also based on the intelligence of different students. According to the grouping situation of different intelligent students before class, we will continue to make in-depth discussion on the problems not covered in class after class and observe the pricing strategies of commodities in local shopping malls to understand the various pricing methods and applications of commodities. Finally, according to the research results of each intelligent group, a Market Research Report or summary report on commodity pricing is written by a group with better language and logical intelligence. The teacher makes a corresponding evaluation of this report, and makes a record of the usual performance of each student participating in this process, as a part of the examination results of this course. At the same time, this report will be posted in the academic report column of the class for students to study together, so that students have a sense of achievement from hard work.

4.4 Marketing test of artificial intelligence technology

Marketing test is no longer a single mode, but according to the intelligence of students. The determination of learning and achievement is not only a test paper, but also in various forms. I divide the students’ marketing scores into four aspects [23 –26]: ① preparation materials before class; ② classroom performance; ③ homework after class; ④ midterm and final examination. In the examination, the principle of “my exam, I am the master” is adopted to give the students the right of independence, less rote questions, more objective choice questions, judgment questions and case questions that fasten the current affairs. In the examination questions, we can also choose more questions reflecting different intelligence according to the different intelligence of the students, so that they can choose the questions that are suitable for themselves to do. In this way, we can learn Students do not have the same questions, not only to avoid plagiarism, but also to really test their academic performance, so as to achieve the test also Shaanxi music. Using the theory of artificial intelligences in the teaching of marketing can reflect the students as the main body, fully mobilize the initiative of students’ learning, let every student participate in the classroom, let every student get the joy of success, and improve the efficiency of the classroom. But all of these are based on the teachers’ understanding of the artificial intelligences of learning cows and the handling of teaching materials. The more clearly the teachers understand the artificial intelligences of the students they teach, the more successful their application in teaching will be. This puts forward higher requirements for our teachers, which requires teachers to be able to deeply understand the multi intelligence situation of each student, change our traditional outlook on students and talents, teach students according to their aptitude, and evaluate our students more scientifically and better. I believe that as long as we pay R, there will be a good harvest tomorrow.

5 Conclusion

The arrival of the era of artificial intelligence has brought certain opportunities and challenges for the cultivation of marketing technical service talents in Applied Undergraduate Colleges and universities, as well as higher requirements for marketing technical service talents. The Application-oriented Undergraduate Colleges and universities should perfect and optimize the curriculum setting, reform the professional teaching system, strengthen the construction of “double teacher” teaching staff, and comprehensively improve the marketing technical service ability of the marketing students through the cooperation between schools and enterprises and the integration of production and education. Based on the in-depth study of artificial intelligence network, this paper constructs the application system of marketing teaching in Colleges and universities from the perspective of post-modern media. From the perspective of postmodern media, the application system of marketing teaching is constructed to verify that the artificial intelligence based on probabilistic neural network has good convergence, fault tolerance and large data processing ability. Finally, this paper takes the pricing strategy in marketing as an example, and focuses on the application of artificial intelligence technology in marketing teaching from four aspects: preparation before class, implementation in class, consolidation after class and marketing teaching examination. The demonstration result of this paper can let more teachers see the influence of this theory on marketing teaching, realize the necessity of developing students’ artificial intelligences, fully consider students’ individual differences in the teaching process, and try to design various types of activities to adapt to different students, so as to help students build up marketing confidence, mobilize students’ enthusiasm in class, and improve the students’ learning attitude and enhance the practical achievement of marketing.

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Role of AI for application of marketing teaching –A research perspective