Innovation of e-commerce marketing model under the background of big data and artificial intelligence

Abstract

With the advent of the era of big data and artificial intelligence, e-commerce enterprises have used a large number of advanced technologies and knowledge management methods to improve work efficiency. In the context of e-commerce, the innovation of enterprise marketing management model has become one of the important contents of the company’s business development in the e-commerce era. Focusing on the core concept of “e-commerce marketing model innovation”, this paper conducts a comprehensive and systematic research on the e-commerce marketing model innovation of enterprise e-commerce, and focuses on the two aspects of e-commerce marketing model innovation and e-commerce model performance evaluation. The purpose of this paper is to understand the importance of innovation factors in the innovation of e-commerce marketing models through questionnaires, so as to provide new ideas for the innovation path of e-commerce marketing models. This paper adopts the questionnaire survey method and data analysis method. According to the survey results, 39, 31, 33, and 35 of the respondents believe that market positioning, business strategy, marketing promotion, and operation management should be prioritized as innovative elements, among which market positioning accounts for a relatively high proportion, followed by operation management. It can be seen that most of the respondents believe that in order to innovate the marketing model of e-commerce, we must start from the aspects of market positioning, business strategy, marketing promotion, and operation management. Combined with the era background and related content of big data and artificial intelligence, this paper studies e-commerce and marketing models, so as to provide new ideas for the innovative path of e-commerce marketing models.

Keywords

Big data artificial intelligence e-commerce marketing model

1. Introduction

With the advent of the era of big data and artificial intelligence, e-commerce has become a new development model for corporate marketing. Big data and artificial intelligence technology are new trends in the development of e-commerce. In the current era, under the background of big data and intelligence, e-commerce companies have achieved good results by using Internet $+$ marketing model innovation. However, in order to further promote the innovation of e-commerce marketing models, some e-commerce industries have also begun to reform. At the same time, with the advent of the new era and meeting the different consumption needs of consumers, this requires us to reform and innovate from the e-commerce marketing model in order to meet consumer needs and better win market share for e-commerce companies to achieve profit goals.

E-commerce trade uses Internet technology to automate the purchase of raw materials, the detection of production goods, and the confirmation of sales and transportation on the Internet to realize commodity transactions in the world. E-commerce can cross time and place, realize the real-time exchange of business documents between the two parties, avoid the failure of transactions due to human or natural reasons to the greatest extent, and improve the efficiency of transactions.

At present, many scholars have carried out research on e-commerce and its related contents, and have obtained quite rich research results. For example, Lakeman et al. [1] took a quantitative survey approach to investigate the preferences of consumers using Indonesian startup e-commerce sites for online payment methods and came to the conclusion that the convenience of online payment methods is the most important factor for e-commerce startups. Paul and Nikolaev [2] pointed out that at present, e-commerce online review systems exist to manipulate consumers’ consumption behavior by fabricating product or service reviews. Alkhalifah et al. [3] believes that the technological revolution and the rapid evolution of the digital world have had a significant impact on the development and expansion of e-commerce, and pointed out that delivery services play an important role in e-commerce [4]. Therefore, this paper starts from a new perspective, combined with the background of big data and artificial intelligence, and conducts research on the innovation of e-commerce marketing model [5].

E-commerce is a business activity centered on the exchange of commodities by means of information network technology; It can also be understood as the activity of conducting transactions and related services in the form of electronic transactions on the Internet, intranets and value-added networks. Electronic, networked and informatized links. There are four operating modes that are widely used now: B2B, B2C, C2C, and O2O.

This article mainly discusses these aspects. First, the contents related to big data and artificial intelligence are expounded [6]. Then, it also discusses the innovation of e-commerce and its marketing model. In the end, this paper conducts a questionnaire survey on the “innovation of e-commerce marketing model”, and draws the corresponding survey results and analysis conclusions [7].

2. Related theoretical overview and research

2.1 Big data and artificial intelligence

With the widespread application of computer technology in various fields of society, the era of big data and intelligence has come [8]. The era of big data is an important symbol of the progress of human society, and will also become a new platform for information dissemination and processing [9]. In this process, features such as massive unstructured data and irregular features are discovered and mined [10].

Big data is the collection, analysis and processing of users’ behavior and information in the Internet field [11]. With the continuous improvement of human ability to obtain information and utilize knowledge, people have become dependent on massive data. How to serve these huge and complex unstructured resources to the society has become a topic of concern for researchers [12].

People conduct research on big data, analyze its potential value and other information and integrate it, so as to find certain rules [13]. Big data is to analyze human social activities and extract effective and potentially meaningful content and knowledge from it. In the era of big data, people analyze and process some important things by using various information [14].

At the same time, the arrival of the era of artificial intelligence has enabled people to realize human-computer interaction [15]. Humans use computers to perform automatic identification and decision-making, thereby completing a series of complex work tasks [16].

With the development of artificial intelligence technology, its application fields are becoming wider and wider, including medical, electronic technology and so on. In the field of artificial intelligence research, the relationship between big data and intelligent robots is very close and inseparable. People can predict what changes may occur in the future by analyzing these data [17].

The development of big data and artificial intelligence as a whole directly affects the future, and artificial intelligence will become the mainstream in the future development. For example, artificial intelligence will provide new opportunities for the development of smart homes. In addition, artificial intelligence combines computer, information communication and other disciplines to form a huge and complex system, and also promotes the continuous and stable development of computer industry, biomedicine and other industries [18].

2.2 Innovation of e-commerce marketing model

E-commerce refers to the commercial behavior of using Internet technology to complete the purchase and sale of goods. It is different from traditional offline shopping, which is an “online” transaction, a product of the combination of electronics and commerce.

The e-commerce model is an innovation of the e-commerce marketing model on the basis of the traditional business model. Compared with traditional commerce, e-commerce is not limited by factors such as time, space, and region, and has the advantages of efficient operation, no time and space constraints, convenient operation, and low cost. In addition, the e-commerce model has innovations in the following aspects [19].

First, under the traditional model, consumers lack a complete understanding of the product, while the e-commerce model can use the online multimedia performance to understand the product, which helps consumers fully understand the product or service before purchasing.

Second, when consumers shop online, they can easily switch between multiple websites to buy products that they are satisfied with at a lower relative price, thereby saving more time and money.

Third, due to the e-commerce model, merchants can communicate directly with consumers, and consumers can also express their opinions and suggestions on the company or dealer’s website, and the company or dealer can timely investigate the types of products and services based on consumer feedback. This interaction allows retailers to further identify user needs. At the same time, dealers can communicate at any time, and interactive communication makes the relationship between the two closers [20].

In the same market environment, the success of an e-commerce enterprise depends on the choice of its model and marketing strategy. Choosing the right marketing method can help companies achieve effective marketing effects and make them profitable.

The choice of the marketing model should be based on the consideration of the company’s own value chain, so as to design the business process, and ultimately maximize the value of the company’s production, management, sales and other business processes in all functional areas. At present, the e-commerce marketing model includes the following modes.

B2B e-commerce marketing mode is one of the most important forms of enterprise e-commerce marketing mode, that is, the exchange of products, services and information between enterprises through the Internet. Traditional business-to-business transactions often consume a lot of business resources and time, and both sales and purchases will put pressure on product costs. This type of transaction allows buyers and sellers to conduct the entire business process online, manufacturing companies create their own websites, buy raw materials and sell products online.

The B2C e-commerce marketing model is a business-to-consumer model. Many business-to-consumer transactions are done electronically. With the rapid development of online retail, there are now thousands of online outlets on the Internet to meet the multi-dimensional needs of consumers. Clearly, companies can improve the way they communicate with customers, provide customers with more choices, and provide more personalized services that cannot be achieved by traditional business methods. The structure of this marketing model is shown in Fig. 1.

Figure 1.

The structure of the marketing model.

The C2C e-commerce marketing model is an e-commerce behavior among consumers, usually using a third-party platform to determine transaction behavior. Since buyers of C2C e-commerce activities are often interested in the products and information provided by sellers, the most important marketing point of C2C e-commerce is that the products can target and attract the attention of specific consumer groups.

The e-commerce model forms a complete closed loop among consumers, enterprises and the government, and the three mutually restrict, supervise and promote each other. They are an integral part of building a complete e-commerce. For example, the government can also manage customs declaration, tax payment and other activities through electronic exchanges. This e-commerce model enables individuals to complete personal tax payment, social security payment and other activities online. At the same time, this method also improves the work efficiency of relevant government departments and service quality.

For every enterprise, every industry and even the whole economy and society, the innovation of e-commerce marketing model is of great significance. Innovation can bring huge economic benefits to a company and help it build a lasting and unique competitive advantage.

The innovation of e-commerce marketing model makes enterprises pay more attention to customer needs, pay attention to the process of customer consumption and use, and solve practical difficulties for customers. The innovation of e-commerce marketing model has broken the original boundaries, reconstructed the relationship between enterprises and customers, suppliers and industries, showing a strong breakthrough ability. Therefore, the innovation of e-commerce marketing model can quickly and comprehensively attract customers and build a strong customer base.

3. Questionnaire and research

3.1 Questionnaire design process

In order to conduct an in-depth analysis of e-commerce data in the context of artificial intelligence, this paper conducts a questionnaire survey. In this questionnaire, 80 staff members of an e-commerce enterprise in D city were selected to investigate the innovation of e-commerce marketing model under the background of big data and artificial intelligence. Then, the results of the questionnaire are sorted and analyzed, and the analysis results include the importance of the interviewee’s innovation factors in the innovation of e-commerce marketing model.

3.2 Questionnaire survey content

Investigate the importance of innovation factors in e-commerce marketing model innovation, including market positioning, business strategy, marketing promotion, operation management and so on. Some of the questionnaire questions are listed below.

Question 1: What impact does the era of big data and artificial intelligence have on the e-commerce marketing model and its innovation path?

Question 2: How important are different innovation factors in the process of e-commerce marketing model innovation?

Question 3: In the process of e-commerce marketing model innovation, which parts should be prioritized?

…

3.3 Calculation methods used in the questionnaire survey

During the questionnaire collection process, the recovered questionnaires include valid questionnaires and invalid questionnaires. A statistical analysis of the answers to each question in the questionnaire is then also required. For example, the first question has three options A, B, and C, then calculate the proportion of correct answer A in the questionnaire, then calculate the proportion of B and C options, and compare their values. The specific calculation method is shown in Eqs (1)–(3):

$\displaystyle\lambda=\alpha/\beta$ (1) $\displaystyle\theta=\min\{{\theta_{1},\theta_{2},\cdots,\theta_{n}}\}$ (2) $\displaystyle\omega=\max\{{\omega_{1},\omega_{2},\cdots,\omega_{n}}\}$ (3)

Among them, $\lambda$ is the response rate, $\alpha$ is the number of valid questionnaires recovered, and $\beta$ is the total number of questionnaires distributed. $\theta$ is the minimum degree of difference, $\omega$ is the maximum degree of difference.

4. Analysis and discussion

This questionnaire survey investigates the importance of innovation factors in the innovation of e-commerce marketing models, including market positioning, business strategies, marketing promotion, and operation management. The survey results are shown in Table 1.

Table 1
The investigation results of innovation factors

Project	Very important	Important	General	Unimportant
Market positioning	36	28	12	4
Business strategy	34	25	18	3
Marketing and promotion	31	26	16	7
Operation management	37	22	16	5

Figure 2.

The investigation results of innovation factors.

As can be seen from Fig. 2, 36, 34, 31 and 37 of the respondents believe that market positioning, business strategy, marketing promotion, and operation management should be given priority as innovation elements. Among them, market positioning accounts for a higher proportion, followed by operation management. It can be seen that most of the respondents believe that in order to innovate the marketing model of e-commerce, we must start from the aspects of market positioning, business strategy, marketing promotion, and operation management.

5. Conclusion

Entering the era of big data, all aspects of people’s lives have been profoundly affected by Internet technology, and great changes have taken place in both the way of life and the way of work. As a new type of transaction method, e-commerce plays an important role in commercial transactions. The rapid development of e-commerce has greatly impacted traditional enterprises. If traditional enterprises intend to survive in the era of rapid development of e-commerce, they must carry out strategic transformation. Only by eliminating the financial risks of e-commerce, can we maintain our original offline brick-and-mortar stores and follow the trend of online store operations.

For the high-quality development of e-commerce enterprises, it is necessary to make full use of the application of artificial intelligence technology, establish new financial risk management concepts, strengthen the construction of accounting informatization, introduce and train advanced financial management talents, and strengthen the establishment and improvement of e-commerce related laws and regulations. The level of credit risk monitoring and evaluation system to deal with new financial risks in the era of artificial intelligence.

With the development of Internet technology, big data and artificial intelligence have penetrated into the e-commerce industry, and have an increasingly important impact in the field of marketing. The e-commerce marketing model also subverts the traditional marketing model. This change not only creates a more economical and flexible environment for enterprises, but also creates huge economic benefits and unique overall competitive advantages, as well as many new business opportunities. Therefore, this paper combines the era background of big data and artificial intelligence and its related content to conduct research on e-commerce and marketing models, so as to provide new ideas for the innovative path of e-commerce marketing models.

References

Lakeman

Walter

Cleff

. The impact of payment methods and payment-related marketing communications on e-commerce retailer trust – An empirical consumer analysis of Indonesian e-commerce start-ups. Int J Electron Bus. 2021; 16(4): 352-376.

Paul

Nikolaev

. Fake review detection on online e-commerce platforms: A systematic literature review. Data Min Knowl Discov. 2021; 35(5): 1830-1881.

Alkhalifah

Alorini

Alturki

. Enhancement of e-commerce service by designing last mile delivery platform. Comput Syst Sci Eng. 2022; 42(1): 49-67.

Dafir

Lamari

Slaoui

. A survey on parallel clustering algorithms for big data. Artif Intell Rev. 2021; 54(4): 2411-2443.

Cavicchioli

Kocollari

. Learning from failure: Big data analysis for detecting the patterns of failure in innovative startups. Big Data. 2021; 9(2): 79-88.

Chakraborty

Khan

Ahmad

. Call for special issue papers: Big data-driven futuristic fabric system in societal digital transformation. Big Data. 2021; 9(4): 324-325.

Baz

Khatri

Baz

Alhakami

Agrawal

Khan

. Blockchain and artificial intelligence applications to defeat COVID-19 pandemic. Comput Syst Sci Eng. 2022; 40(2): 691-702.

Mes

Lalla-Ruiz

Voß

. Special issue on “Artificial Intelligence for Automation in Freight Transport”. Int Trans Oper Res. 2022; 29(2): 1330-1331.

Yadav

Rahman

. Measuring consumer perception of social media marketing activities in e-commerce industry: Scale development & validation. Telematics Inf. 2017; 34(7): 1294-1307.

10.

Chattopadhyay

Basu

Das

Ghosh

Murthy

LCA

. Towards effective discovery of natural communities in complex networks and implications in e-commerce. Electron Commer Res. 2021; 21(4): 917-954.

11.

Sadowski

Lewandowska-Gwarda

Pisarek-Bartoszewska

Engelseth

. A longitudinal study of e-commerce diversity in Europe. Electron Commer Res. 2021; 21(1): 169-194.

12.

Cao

. Artificial intelligence-based plant environment detection in coastal areas and B2C e-commerce network marketing. Arabian J Geosci. 2021; 14: 996.

13.

. Optimization of e-commerce logistics system based on artificial intelligence technology. J Phys: Conf Ser. 2021; 1881(3): 032062.

14.

Simkova

Smutny

. Business E-NeGotiAtion: A method using a genetic algorithm for online dispute resolution in B2B relationships. J Theor Appl Electr Commer Res. 2021; 16(5): 1186-1216.

15.

Zhang

Pee

Cui

. Artificial intelligence in e-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse. Int J Inf Manage. 2021; 57: 102304.

16.

Huang

. Legal traceability of information leakage of artificial intelligence rural e-commerce shopping guide platform based on big data. J Phys: Conf Ser. 2021; 1744(4): 042033.

17.

Khrais Laith

. Role of artificial intelligence in shaping consumer demand in e-commerce. Future Internet. 2020; 12(12): 226.

18.

Cabrera-Sanchez

Ramos-de-Luna

Carvajal-Trujillo

Villarejo-Ramos

. Online recommendation systems: Factors influencing use in e-commerce. Sustainability. 2020; 12(21): 8888.

19.

Manpreet

. Role of artificial intelligence in ecommerce. J Crit Rev. 2020; 7(16).

20.

Leung

Luk

Choy

Lam

Lee

CKM

. A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment. Int J Prod Res. 2019; 57(20): 6528-6551.