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مدلی برای کاهش ریزش مشتریان با استفاده از مدیریت ارتباط با مشتری مبتنی بر هوش مصنوعی در صنعت بیمه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت بازرگانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران

2 دانشیار، گروه مدیریت بازرگانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران

چکیده

مطالعه حاضر از نظر هدف یک مطالعه کاربردی-توسعه‌ای است که درصدد ارایه الگوی کاهش ریزش مشتریان با استفاده از مدیریت ارتباط با مشتری مبتنی بر هوش مصنوعی در صنعت بیمه می‌باشد. از منظر روش گردآوری داده‌ها یک پژوهش پیمایش مقطعی است. برای نیل به هدف از طرح پژوهش آمیخته اکتشافی (کیفی-کمی) استفاده شد. در بخش کیفی از روش تحلیل مضمون و در بخش کمی از روش حداقل مربعات جزئی استفاده شد. جامعه مشارکت‌کنندگان بخش کیفی شامل مدیران شرکت بیمه ایران بودند که 17 نفر با روش نمونه‌گیری هدفمند انتخاب شدند. در بخش کمی نیز جامعه آماری متشکل از مدیران و کارشناسان بیمه ایران و مدیران نمایندگی‌های بیمه ایران در استان گیلان، با روش اندازه اثر و تحلیل توان، 130 نفر به روش نمونه‌گیری خوشه‌ای-تصادفی انتخاب شدند. ابزار گردآوری داده‌ها در بخش کیفی، مصاحبه نیم‌ساختاریافته و در بخش کمی، پرسشنامه محقق‌ساخته بود . یافته‌های پژوهشی نشان داد عوامل فنی هوش مصنوعی، عوامل مدیریتی هوش مصنوعی و بازاریابی رابطه‌ای بر مدیریت ارتباط با مشتریان تاثیر می‌گذارند. مدیریت ارتباط با مشتری با اثرگذاری بر شخصی‌سازی خدمات و مشتری‌گرایی منجر به بهبود تجربه مشتریان می‌شود. این عامل خود با اثرگذاری بر وفاداری مشتریان، رضایت مشتریان و مشارکت مشتریان به کاهش ریزش مشتریان منتهی می‌گردد. بنابراین مشخص شد هوش مصنوعی یک سازه زیربنایی است که از منظر فنی و مدیریتی می‌تواند به بهبود مدیریت ارتباط با مشتری در نمایندگی‌های بیمه ایران کمک کرده و سبب کاهش رویگردانی و ریزش مشتریان شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A Model to Reduce Customer Churn Using Artificial Intelligence-Based Customer Relationship Management in the Insurance Industry

نویسندگان [English]

  • Maral Shadpour 1
  • Kambiz Shahroodi 2
  • , Narges Delafrooz 2

1 Ph.D. Student in Marketing Management, Department of Business Management, Rasht branch, Islamic Azad University, Rasht, Iran

2 Associate Prof., Department of Business Management, Rasht branch, Islamic Azad University, Rasht, Iran.

چکیده [English]

The turning away of customers is one of the main threats in the competitive insurance industry, so the use of new technological approaches such as artificial intelligence to communicate with customers and reduce their loss has become a focal issue in this industry. In terms of the purpose of this study, it is an applied-developmental study that seeks to provide a model for reducing customer churn using artificial intelligence-based customer relationship management in the insurance industry. From the point of view of the data collection method, it is a cross-sectional survey research. To achieve the goal, a mixed exploratory research design (qualitative-quantitative) was used. In the qualitative part, the theme analysis method was used, and in the quantitative part, the partial least square method was used. The community of participants of the qualitative part included the managers of Iran Insurance Company, 17 of whom were selected by purposive sampling method. In the quantitative part, the statistical population consisting of managers and experts of Iranian insurance and managers of Iranian insurance agencies in Gilan province, with the method of effect size and power analysis, 130 people were selected by cluster-random sampling method. The data collection tool in the qualitative part was semi-structured interview and in the quantitative part, researcher-made questionnaire. Research findings showed that technical factors of artificial intelligence, managerial factors of artificial intelligence and relationship marketing affect the management of relationship with customers. Customer relationship management improves customer experience by influencing service personalization and customer orientation. This factor by influencing customer loyalty, customer satisfaction and customer participation leads to the reduction of customer churn. Therefore, it was found that artificial intelligence is an infrastructure structure that, from a technical and managerial point of view, can help to improve customer relationship management in Iranian insurance agencies and reduce customer turnover and loss.

Introduction

The loss of customers is an alarming issue in the insurance service sector. In competitive and saturated markets such as the insurance industry market, customer turnover can always be expected and there are several reasons for it. This may be due to various reasons such as dissatisfaction, higher costs, low quality, lack of handling of complaints, lack of certain facilities and services, or concerns about privacy and other such issues. On the other hand, competitive prices, higher service quality, gifts, promotions, marketing campaigns, accessibility and competitors' driving activities can lead to the loss of customers. The economic value of customer retention in the insurance industry has compelled insurance companies to try to reduce the loss of their customers. In the highly competitive insurance industry, customer-oriented strategies must be set to minimize the rate of customer loss both in the short- and in the long- term. Customer churn reduction programs require large databases and big data analysis. The processing and analysis of such data to improve the ability of companies to achieve their desired goals requires the use of new technologies based on artificial intelligence (AI). The present study investigates the potential role of customer relationship management in reducing customer attrition rates in the insurance industry. The number of active companies in the insurance industry and the large number of agencies have greatly intensified the competition in this industry. In such a situation, customers have a lot of freedom in choosing, and this has increased the rate of customer churn in the industry. In such a situation, customer relationship management can be effective in reducing the loss of customers. In this regard, application of artificial intelligence can be very fruitful in understanding the needs, wishes and demands of insurance customers and providing correct, timely and pioneering responses. However, few studies have dealt with customer relationship management based on artificial intelligence in insurance market. This represents a research gap in the literature; hence there is an urgent need for further research. To address the aforementioned gap, this research presents a new framework that highlights the role of AI in reducing customer churn in the insurance industry. For model sophistication, in-depth interviews with business experts were conducted, by which the relevant variables were identified. Thematic analysis - as a robust qualitative method - was used to identify key components. For further validation, the proposed model was evaluated in the form of a survey. The main contribution of this research is to identify the key components of the application of AI in the insurance industry in terms of preventing customer churn. The authors believe that the findings of this study can have a combination of managerial and research implications because the model highlight themes and areas that have not received much attention in previous research.

Literature Review

Customer churn:
“Churn” is the equivalent of the polysemous morpheme Churn, which is composed of the two words Change, meaning change, and Turn, meaning rotation. Churn refers to the fact that a customer changes their service provider by turning away from their current service provider. According to another definition, churn or turning away refers to a customer changing service providers or a customer’s tendency to disconnect from an organization within a certain period of time (Forghani Dehnavi et al., 2022).
Customer relationship management
Customer relationship management refers to the methods, strategies, and technologies that marketing managers use to manage a company’s relationship with customers and gain more profit through customer satisfaction and loyalty (Sudirjo et al., 2024).
Artificial intelligence:
Artificial intelligence was introduced in 1950 with the study of Alan Turing, a British mathematician. Turing asked the question, “Can machines think?” After this initial question, artificial intelligence was formally proposed and defined as a new field of research at the Dartmouth Academic Conference in 1956. Then, in 1965, John McCarthy introduced the concept of artificial intelligence in its current common sense. Then came the first spring of artificial intelligence, when the field was rapidly applied in various fields (Strieth-Kalthoff et al., 2024).

Methodology:

This is an applied research carried out with inductive-analogical approach. An exploratory mixed design (qualitative-quantitative) was used to conduct the research. The participants in qualitative phase of the research included 17 experts (both university professors and market practitioners) having significant experience in the fields of technology-based marketing who were adopted by purposeful sampling using snow-ball method. Sample size was determined based on theoretical saturation during interviews.
The statistical population in the quantitative part included managers and experts of Iranian insurance and managers of Iranian insurance agencies in Gilan province. To calculate the sample size, Cohen's power analysis rule (1992) and G*Power software were used. Using the rule of power analysis, a minimum sample size of 130 people was estimated with an effect size of 0.15 and a statistical power of 80%. A cluster-random method was used for sampling in the quantitative part. Data was collected by semi-structured interviews (qualitative phase) and self-administered questionnaires. The interview included 6 primary questions and was conducted in a semi-structured manner. The research questionnaire includes 11 main constructs and 63 items with a five-point Likert scale. Qualitative data were analyzed by theme analysis method using MaxQDA 20 software. Partial least squares using Smart PLS 3 software was used for validation of the model in the quantitative phase.

Results

based on the results, 3 global themes, 11 organizing themes and 63 basic themes were obtained through axial coding.The results showed that technical and managerial factors of artificial intelligence and also relationship marketing affect customers relationship management. Customer relationship management improves customer experience by influencing service personalization and customer orientation. By influencing customer loyalty, customer satisfaction and customer participation, this factor leads to reduction of customer churn. Therefore, Iran's insurance agencies can prevent their customers churn by means of customer relationship management based on artificial intelligence capabilities.

Discussion and Conclusion

Customer relationship management is a process of collecting and integrating information for effective and targeted use. This information can be related to customers, sales, effective marketing, sensitivity and market needs. Given the strong fluctuations in demand and increased competition in the markets, many companies are trying to create a strategy that integrates all components of an organization, shares information among all users and prevents unnecessary repetition of work. This philosophy creates an environment in the organization in which information is shared so that it is available to those who need it at the right time, meaning that all employees and everything are connected and connected to each other and the departure of one person from the organization will not cause anything in the organization to fall apart. Customer relationship management is a strategy that has been implemented with the help of technology, of course, it should be noted that customer relationship management is not just a software tool that improves the performance of the company, but rather customer relationship management is a philosophy that tries to create a strategy in this direction.
Keywords: Customer Churn, Customer Relationship Management, Artificial Intelligence, Insurance Industry of the Country.
 
 


کلیدواژه‌ها [English]

  • customer churn
  • customer relationship management
  • artificial intelligence
  • insurance industry of the country
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مطالعات مدیریت کسب و کار هوشمند
دوره 13، شماره 52
تیر 1404
فایل ها
سابقه مقاله
  • تاریخ دریافت: 30 مرداد 1403
  • تاریخ بازنگری: 11 دی 1403
  • تاریخ پذیرش: 12 دی 1403
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