Designing a B2B Digital Marketing Implementation Model with an Emphasis on Artificial Intelligence-based Customer Relationship Management

The use of digital marketing as a communication and sales channel has led to the need and use of customer relationship management (CRM) systems based on artificial intelligence for the proper management of company information.

The purpose of this research is to design a business-to-business marketing implementation model with an emphasis on customer relationship management based on artificial intelligence

This study is a type of mixed research with a qualitative-quantitative approach, which is a survey study in terms of its purpose, application, and data collection. In the qualitative part of the data collection tool, a semi-structured interview with 18 specialists and experts in the field of business-to-business digital marketing and university professors who were selected by snowball method. The quantitative part includes a targeted sampling with 35 digital marketing experts and data gathered through a questionnaire. In the qualitative part of the data analysis method, the Grounded theory approach is used based on the Strauss and Corbin method, which is compiled using the MAXQDA software and the coding method. In the quantitative part, the validation method is based on the Kendall correlation test.

The findings of the research (6 general categories, 25 subcategories, and 173 main concepts) include presenting a model that includes causal, contextual, and intervening conditions, along with the introduction of the central phenomenon and the presentation of strategies for implementing business-to-business digital marketing and identifying its consequences.

Company managers should pay attention to factors such as customer relationship management based on artificial intelligence (analytical, collaborative, and operational) to implement digital marketing from business to business and try to weaken the inhibiting factors and strengthen the positive and influential factors.