In this post, we review the customer segmentation research article, “Customer segmentation issues and strategies for an automobile dealership with two clustering techniques” (2015) by authors from Taiwan: Chih-Fong Tsai from National Central University, Ya-Han Hu from National Chung Cheng University, and Yu-Hsin Lu from Feng Chia University.
The Business Case for Segmentation
The authors identified problems encountered by companies during the customer segmentation process and discussed the same in the context of customer relationship management based on a case study of a Taiwanese automobile dealer. From their literature review, they found that for customer segmentation, most of the studies adopted clustering techniques in isolation, with no parallel analysis of customer transactions and satisfaction. Other studies were found to be limited to one clustering method only that led to inaccurate results and incomplete marketing strategies.
Measuring customer satisfaction and identifying the types of customers based on the same during the customer segmentation process has risen as a critical idea for modern marketers, especially those from the automobile dealership industry and similar domains where customer preferences change frequently. Previous studies demonstrate that desirable outcomes can be obtained by using the clustering techniques for customer segmentation to develop marketing strategies that may lead to increased marketing effectiveness (Knox et al, 2003).
Although studies have demonstrated successful customer segmentation based on clustering techniques for many real-life applications, there are only a few studies around the clustering of customers specifically in the automobile industry (Liang, 2010). Most automobile businesses prioritize product sales as their key profit source, and thus, customer segmentation for such businesses is usually based on the assessment of customers’ previous purchase records as a sole segmentation criterion.
Customer Segmentation as a Solution for Competitive Advantage
Customer segmentation, in parallel with customer analysis, is a very important notion that businesses must understand if they wish to be competitive and expand. In competitive markets, achieving high customer satisfaction by analyzing customer transactions and behavior is the key to maintaining a competitive advantage (Zairi, 2000). This is because customer satisfaction has a positive impact on a business’s overall profitability. Customer segmentation in isolation, i.e., with no customer transaction and behavior analysis would cause a business potential loss in terms of customers and revenues. Firms forgoing customer segmentation will not be able to devise accurate marketing strategies based on different customer needs.
Identifying satisfied and loyal customers, as derived from the customer segmentation techniques, makes the basis of a successful business and translates into a myriad of benefits, including repeat purchases, positive word of mouth, and brand loyalty (Yang & Peterson, 2004). Furthermore, a business can make more effective and informed marketing strategies by adopting customer segmentation. Unfortunately, this idea has not been much into consideration of the previous studies as per the authors of the article.
Methods for Customer Segmentation
To solve the research problem, the authors applied two clustering techniques, identified four customer groups, and proposed custom market strategies for each group based on the segmentation findings. The end objective was to compare the outcomes of both techniques and improve customer relationship management by ensuring quality service via operationalization of the segments.
The authors have adopted this process because of the strong focus evolving in this field since customer relationship management is understood as the source of business profits. Companies could earn great returns from loyalty from decreeing transition cost, product price elasticity, and increasing repurchase patterns (Rust et al., 2004). Customer satisfaction impacts the financial performance of a business through loyalty.
To demonstrate that customer segmentation through two clustering techniques is more accurate and more in line with the goals of devising accurate marketing strategies for different kinds of customers, the authors introduce a real case study of a Taiwanese automobile dealer. They chose the automobile industry despite its recent challenges against which they propose that successful customer retention and positive word-of-mouth marketing may help increase profitability in the post-sale service market and bring a competitive edge to the business (Van den Poel & Larivie’re, 2004). Segmenting the customers into groups can help such planning.
To cluster the customers, it is significant to know the factors that trigger purchase behavior and profitability. Therefore, the authors based their study on data that includes basic customer information, new vehicle sales, maintenance services sales, and customer satisfaction data. They used two clustering techniques called k-means and EM (Expectation Maximization) to detect different groups of customers or potential consumers for automobile dealers.
Key Findings about Segmentation in Automotive Industry
The authors represented interesting findings out of their study. They defined seven important factors they used to segment their customers as per two clustering techniques applied. These factors include (1) maintenance service outsourcing satisfaction, (2) new vehicle outsourcing satisfaction, (3) maintenance service satisfaction, (4) new vehicle satisfaction, (5) transaction amount, (6) transaction frequency, and (7) quality assurance.
Application of clustering algorithms led to four customer groups defined by variables, namely satisfaction variables, service revenue, mean regular service interval, the period since the last transaction, compensation claim times, and customer complaint times.
We can summarize the findings as follows:
- Both techniques showed a customer churn problem in the case company.
- Loyal customers’ loyalty with dealers is high because of their high level of satisfaction. The marketing strategy should focus on customer retention and satisfaction as the antecedent of this retention.
- Potential customers have higher frequency for compensation and they are satisfied with the service provided. The marketing strategy should focus on increasing their
- VIP customers pay the most but are not satisfied with the service. The marketing strategy should be based on their purchasing behavior trends and feedback.
- Churn customers pay the least and have the highest number of complaints and degree of dissatisfaction. The marketing strategy should focus on membership and relationship management to mitigate churn.
The findings from the study show that customer segmentation is a significant and necessary element to consider to devise an effective customer relationship strategy and serve different customer groups in efficient and cost-effective ways. At the same time, it establishes the fact that customer segmentation should not rely on basic customer information only; rather it must consider customer satisfaction variables, too. The clustering techniques used in the study aimed to divide customers accurately into four groups based on well-defined characteristics as well as the defined factors that can affect customer satisfaction. The study thus postulates that automobile dealers should focus on retention marketing strategies that aim to increase customer satisfaction among all these groups.
Future Research Ideas on Customer Segmentation
The current study and the previous studies related to the context of customer segmentation, and especially in the context of automobile dealers, bear significant implications for future work. The future work suggested by the authors include inclusion of customer satisfaction data in market segmentation studies, implementation and tracking of proposed marketing strategies in a said case, and implementation of the proposed strategies at other similar companies to check validity.
Implications for Practitioners Working with Customer Segmentation
Practitioners, including marketers and research analysts, can have a valuable foundation in the shape of this study, for their future research strategy and marketing projects. They can benefit by knowing how their customers perceive their service quality and recognizing the way of how to determine the level of service quality. Hence, the practitioners can use the precise data gathered in their plans and strategies.
Some of the measures as proposed by the authors include discounts on vehicle maintenance services for loyal customers, assigning a technician for potential customer’s vehicle maintenance, providing upgraded service to VIP customers, and applying relationship management strategies for churn customers to take them on board again.
Businesses could segment and target their customers based on such strategies and obtain more revenues from customer loyalty. Long-term customer relationships can be established for the customers whose loyalty is related to satisfaction to a great extent, while new services can be designed for the customers whose loyalty is autonomous of satisfaction (Wang & Zhao, 2003).
To increase customer satisfaction and avoid customer churn, businesses should keenly focus on customer segmentation and catering to the distinct customers’ needs to enhance value creation activities. Such studies and experiments, where these elements are taken into account, would help practitioners better understand different service quality dimensions which impact the overall service customer satisfaction and loyalty. They can help businesses better allocate their resources to deliver better service to the customers. Hence, analyzing and measuring the customer loyalty and satisfaction level with service quality corresponding to their customer groups bears significant implications for the practitioners, especially in the automobile sector that has been witnessing various challenges.
References
- Zairi, M., (2000) “Managing customer satisfaction: a best practice perspective”, The TQM Magazine, Vol. 12 (6), pp.389-49
- Yang Zhilin, Peterson R T (2004). Customer perceived value, satisfaction, and loyalty: the role of switching costs. Psychology & Marketing, 21(10): 799–822
- Rust R T, Lemon K N, Zeithaml V A (2004). Return on marketing: using customer equity to focus marketing strategy. Journal of Marketing, (68): 109–128
- Van Den Poel, D. & B. Larivie’re. (2004) Customer attrition analysis for financial services using proportional hazard models, European Journal of Operational Research, 157, 196–217
- Wang Xia, Zhao Ping (2003). Research of the impact of customer satisfaction on loyalty in the durable goods industry. Journal of Beijing Technology and Business University Social Science, (6): 41–44 (in Chinese)
- Knox. S, Maklan. S, Payne. A, Peppard .J, Ryals. L (2003). Customer Relationship Management Butterwirth- Heinemann