Customer Lifetime Value as the Basis of Customer Segmentation

SUMMARY

In this article, we examine current trends in customer life-time value and customer segmentation models and identify key issues for future research. CLV-based segmentation is a segmentation approach that groups customers into meaningful segments based upon customer lifetime value and (potentially) other factors. In the article, we discuss the extent to which CLV-based segmentation meets the criteria for effective segmentation. We also identify six areas for future research: (1) models and management of “micro-segments,” (2) using CLV-based segmentation to improve the efficiency of marketing programs, (3) the need for more dynamic CLV-based segmentation models, (4) applying CLV-based customer segmentation to new products and new customers, (5) challenges associated with implementing CLV-based segmentation, and (6) the need for new models that enable firms to segment customers by response to marketing activities and CLV at different points in the customer decision process.     

“I can get no e-satisfaction”. What analytics say? Evidence using satisfaction data from e-commerce

This study mines customer satisfaction (CS) segments using almost 270 thousand responses from a CS survey which ran in 140 e-commerce stores of a European country. To achieve this, it develops and applies a business analytics (BA)-informed framework. Then, it presents examples of how one e-commerce store exploited the extracted CS segments to build automated marketing actions for its customers, ranging from social media sharing strategies for the satisfied segments, to discounts for the less satisfied. This study contributes to customer satisfaction and segmentation literature. The extracted insights can be utilized to support decision making, ranging from targeted advertising for specific customer segments, to benchmarking for companies in similar industries.     

Segmentation based on customer profitability — retrospective analysis of retail bank customer bases

Segmentation continues to be an important marketing concept also in a relationship marketing context. Relationship marketing is, however, more interested in enhancing the existing customer relationships and this generates a need for a better understanding of the existing customer base. The paper argues that “retrospective” or historical analyses, that facilitate the calculation of customer relationship profitability, form an excellent starting point for segmentation of customer bases. Such segmentation is shown to be a strong analytical instrument as a basis for formulating marketing strategies. By using empirical data collected from two extensive case studies of retail banks in the Nordic countries the paper illustrates different ways of segmenting customer bases.     

Using Information as a Basis for Segmentation and Relationship Marketing: A Longitudinal Case Study of a Leading Financial Services Firm

An important concern for service businesses is how to develop an appropriate segmentation and relationship marketing strategy that is tied to the value contribution of the customer base. This article presents a case study of the relationship marketing strategy for a division of a leading, worldwide financial services provider. The case firm segments customers into three tiers, using a framework similar to the one established by Berry and Parasuraman. Potential revenue from the customer is the primary segmentation variable used to assign customers to one of the three tiers, while the customer service response is tailored for each tier based upon customer information capabilities and needs. Although information is normally thought of as a supplemental service, rather than a core service, this case study shows how information is central to providing effective customer service and is a key to relationship marketing. The study also demonstrates how social and structural bonds can be used to refocus a customer's thinking from a cost perspective to a value perspective.     

Managing Complaints to Improve Customer Profitability

In this study, the authors aim to understand whether, to what extent, and under what circumstances, organizational responses to customer complaints improve customer profitability. To do so, they build upon the congruence approach and propose a contingency framework in which the effectiveness of three organizational responses to customer complaints (timeliness, compensation and communications) in improving customer profitability is contingent upon the strength of the relationship and the type of failure. The framework is tested empirically in the financial services industry applying latent class techniques to longitudinal data for a sample of complaining customers. The results reveal that: (1) different complaint-handling initiatives affect customer profitability differently for each of the four segments of complaining customers that are obtained; (2) these heterogeneous responses to complaint handling are explained by differences in the orientation of the relationship and in the failure context; and (3) complaint-handling initiatives are more (less) effective at improving customer profitability when the benefits they offer strongly (poorly) match the benefits sought by customers in each segment to recover from the failure. These results contribute to a better theoretical understanding of customers’ heterogeneous responses to complaint handling and offer managerial recommendations to allocate marketing resources across alternative complaint-handling strategies to improve profitability.     

How Online Consumer Segments Differ in Long-term Marketing Effectiveness

Online commerce gives companies not only a growing global sales platform, but also powerful consumers enjoying 24/7 availability, choice proliferation and the power to opt in and out permission-based communication. Unfortunately, our knowledge is limited on long-term marketing effectiveness in this space and on how it differs across customer segments. Managers appear overwhelmed by the combination of rich online data on hundreds of thousands of customers and the typical aggregate-level data on offline marketing spending.This paper is the first to investigate the long-term impact of coupon promotions, TV, radio, print, and Internet advertising across customer segments for a major digital music provider with over 500,000 customers. We first segment customers and subsequently analyze how these segments respond in the long run to different marketing activities when purchasing music downloads. Our findings reveal that the effectiveness of marketing differs across segments, while standard segmentation approaches fail to identify the most valuable catches in a sea of consumers. In contrast to empirical generalizations on consumer packaged goods, heavy users of digital music products are least sensitive to price and most sensitive to TV advertising and to multiple touch points. Light users, the majority of consumers, are price sensitive and tend to opt out of targeted communication. Our research enables managers in the digital media space to target high-value customer segments with the most effective actions.     

Customer Personal Features as Determinants of the Formation Process of Corporate Social Responsibility Perceptions

The authors of this paper introduce three customer demographic features (age, gender, and educational level) and three psychological traits (support, collectivism, and novelty seeking) as moderators in a classic model to better explain the formation process of corporate social responsibility (CSR) perceptions. The results of the paper can assist CSR and marketing practitioners in better segmenting the market in order to adapt their CSR and communication strategies and make them more effective. The authors test a causal model that allows them to anticipate CSR perceptions based on customer evaluations of (1) the congruence between the company and its CSR strategy, (2) the motivations of the company to implement CSR activities, and (3) the corporate credibility in developing CSR programs. Results suggest that customer psychological features are more effective for marketing segmentation than demographic features because they explain more differences among customers in the formation of CSR perceptions. CSR support and novelty seeking are the most valuable characteristics that can be applied to marketing segmentation.     

A deep hybrid learning model for customer repurchase behavior

Smartphones have become an integral part of our daily lives, which has led to the rapid growth of the smartphone market. As the global smartphone market tends to remain stable, retaining existing customers has become a challenge for smartphone manufacturers. This study investigates whether a deep hybrid learning approach with various customer-oriented types of data can be useful in exploring customer repurchase behavior of same-brand smartphones. Considering data from more than 74,000 customers, the proposed deep learning approach showed a prediction accuracy higher than 90%. Based on the results of deep hybrid learning models, we aim to provide better understanding on customer behavior, such that it could be used as valuable assets for innovating future marketing strategies.     

A data mining approach for segmentation-based importance-performance analysis (SOM–BPNN–IPA): a new framework for developing customer retention strategies

Importance-performance analysis (IPA) is a simple but effective means of assisting practitioners in prioritizing service attributes when attempting to enhance service quality and customer satisfaction. The purpose of this study was to demonstrate how IPA can be used with market segmentation to develop customer retention strategies for different market segments. For this purpose, a new framework have been proposed that uses self-organizing maps for customers’ segmentation and back-propagation neural network (BPNN) for implicity drive the importance of service attributes based on their effect on customers’ loyalty in each segment. Then, individual IPA matrixes are developed for each market segment. Also, an example case is presented to demonstrate the implementation and application of the proposed framework. The results of the proposed framework compared with a conventional BPNN-IPA approach indicated that it can increase reliability and applicability of IPA results.     

Reactions of the jilted consumer

Differential promotion strategies are a vital relationship marketing tool that is advantageous to both the company and the targeted customer. However, a differential approach means some customers do not fare as well as others. The customers who get the lesser deals are the focus of this study. How does a customer react when they learn another customer received a better deal? How should the provider respond when this imbalance is obvious to the customer? Fairness theory is utilized to address these research questions. The study includes an experiment featuring hypothetical scenarios. MANOVA results reveal that a proactive, upfront strategic response can mitigate the negative effects of differential promotion strategies in terms of fairness perceptions and behavioral outcomes.     

Development of Value Stream Mapping from L’Oreal’s Artwork Process

ABSTRACT

This research develops value stream mapping (VSM) for L’Oreal’s artwork process, to eliminate waste, reduce lead-time, and identify stages that should be automated, which makes the process less prone to human error and more responsive to fulfilling B2B (B2B) customer requirements. Additionally, amendments frequently occur slowing down the artwork process. In this context, VSM is applied to L’Oreal’s artwork process to reduce lead-time, human error, and missed deadlines.

This practitioner note uses data from L’Oreal’s artwork tracker from 2018 to 2019, which is manually tracked by the launch team. The service level agreement and task time data has been collected from 12 employees representing the launch, factory, and marketing teams working on the artwork process. Qualitative feedback was also obtained from nine employees to validate the VSM for L’Oreal’s artwork process.

VSM identified stages that should be streamlined and automated in L’Oreal’s artwork process, which makes the process more efficient and responsive to the changing scope of the artworks. Fifty percent of the stages have been eliminated from the manual artwork process, resulting in a reduced lead-time of 10.5 days and a reduction of 28% time spent on the process. This allows the artwork process to be more agile to the requirements of B2B customers. Moreover, the proposed VSM shows a 73% increase in value added time for a renovation and a 75% increase in value added time for new product developments (NPD).

VSM has been used within many functions in a business, such as operations and supply chain management, however, its application within marketing has not been extensively explored. This practitioner note attempts to fill this gap by applying VSM to L’Oreal’s artwork process (AP). Moreover, this research extends the understanding of the concept and application of VSM within the context of lean in a marketing process. VSM has successfully identified the inefficiencies in the artwork process and highlighted the stages in the process that should be removed or automated thereby, making the process responsive and agile to meet the changing requirements of B2B customers.

VSM has been successfully applied to L’Oreal’s artwork process that resulted in a significant reduction in the total number of stages in the proposed process by eliminating non-value added activities. Efficiency gained through the application of VSM will lead to increased B2B customer satisfaction, reduced lead-time, and reduction in human errors and missed deadlines.

VSM has been specifically designed, developed, and analyzed for L’Oreal’s artwork process, in order to make the process more efficient and responsive to B2B customers' requirements.     

Evaluating discounts as a dimension of customer behavior analysis

Today, increased competition between organizations has led them to seek a better understanding of customer behavior through identifying valuable customers. Customers’ expectations about the price and quality of products and services play an important role in their selection process. In online businesses, competition and price differences between suppliers is high, so discounts will attract different customers. As a result, discounts and the frequency and amount of purchases can lead to better understanding of customer behavior. Customer segmentation and analysis is essential for identifying groups of customers. Hence, this study uses a model based on RFM called RdFdMd, in which d is the level of discount used to analyze customer purchase behavior and the importance of discounts on customers’ purchasing behavior and organizational profitability. The CRISP-DM and k-mean algorithm were used for clustering. The results indicate that using the R_dF_dM_d model achieves better customer clustering and valuation, and discounts were identified as an important criterion for customer purchases.     

Uncertainty representation and risk management for direct segmented marketing

ABSTRACT

Mining for truly responsive customers has become an integral part of customer portfolio management, and, combined with operational tactics to reach these customers, requires an integrated approach to meeting customer needs that often involves the application of concepts from traditionally distinct fields: marketing, statistics, and operations research. This article brings such concepts together to address customer value and revenue maximisation as well as risk minimisation for direct marketing decision-making problems under uncertainty. We focus on customer lift optimisation given the uncertainty associated with lift estimation models, and develop risk management and operational tools for the multiple treatment (recommendation) problem using stochastic and robust optimisation techniques. Results from numerical experiments are presented to illustrate the effect of incorporating uncertainty on the performance of recommendation models.     

Market orientation and customer-based corporate brand equity (CBCBE): a dyadic study of Indian B2B firms

The relationship between market orientation (MO) and one of its most important consequences – firm performance – has received considerable attention in marketing research. Performance has been largely judged through financial or objective measures. This paper connects assimilation of MO in firms with corporate brand performance since academics have not used judgmental or market-based measures in assessing performance. We have introduced customer-based corporate brand equity to obtain a rounded idea of firm performance. This is achieved through a dyadic study, instead of self-assessment, wherein the marketing chiefs of B2B firms and their respective organisational customers are surveyed to gauge the effects of incorporating MO. We have shown that corporate brand performance is enhanced significantly in the presence of organisational innovativeness. From a practitioner’s perspective, the study details the organisational actions to be taken to assimilate MO and how those can be exploited to enhance corporate brand performance.     

A Stakeholder Perspective on Relationship Marketing

Abstract

This paper proposes a broad framework of relationship marketing using the stakeholder approach. Drawing from Peck et al. (1999) framework and proposing several modifications, the authors identify the following relational groups-supplier markets, customer markets (channels), customer markets (end users), competitor markets, external influence markets, and internal markets. The growing importance of strategic alliances is reflected in all constituent groups as well as in a proposed modification of the Berry and Parasuraman (1991) levels of relationships. This paper also re-examines the strategic role of the traditional marketing mix strategies (namely, product, price, place, and promotion) in the new relationship paradigm. Finally, implementation strategies for the stakeholder markets, in general, and customer markets, in particular, are proposed. Several propositions are derived throughout the paper, many of which can be fertile areas for future research investigations.     

Integration of Multiple Sales Channels with Web-Based Technology–A Case of the Pharmaceutical Industry

ABSTRACT

Channel-centric selling approach is considered a competitive advantage when web-based technologies, such as the Internet, call centers, and database marketing, have emerged. A basic starting point is building corporate Internet Presence Sites (IPSs). The study attempts to answer the fundamental question of how effective IPSs are in reaching target customers and how they are integrated in multi-channel strategies for customer contact. In order to attain homogeneity in sampling, only the pharmaceutical industry was selected. The research entailed both content analysis of IPSs and a focus group study of physicians and pharmacists, conventionally the major target customers for pharmaceutical companies. Results showed that large companies incorporate significantly more attributes related to public relations, building of user group and communities, and services to business partners; but the interviewees did not report any usage of the IPSs. To increase return on companies' hefty investment, the researchers suggested a framework for companies to integrate web-based strategies with multiple sales channel design.     

一种商业银行客户分割的多维方法——基于客户期望收益和态度的分割模型

客户分割与资源分配是企业一直在努力解决的问题,但目前,空前巨大的客户数据量使得准确进行市场细分和寻找目标市场变得复杂和难以有效实施。通过数据挖掘技术从大型数据库中抽取隐藏的预测信息,利用层次聚类分析建立了一个根据客户的多个态度维度进行客户分割的多维方法。结果表明,以这一方式产生的聚类在同质性较好并且通过参考人口学特征的差别能够获得客户细分市场的轮廓。此外,识别了四个有特色的、表明对信息服务和技术有特殊偏好的客户群。     

Relationship Intention and Length of Customer–Firm Associations in Two Emerging Markets

ABSTRACT

Despite the benefits of following a relationship marketing approach, firms should use caution when targeting customers with relationship marketing strategies as not all customers want to enter into long-term relationships. Targeting customers based on the length of customer-firm association could also be flawed as the success of doing so is disputed. This study explored relationship intention under cell phone customers in two emerging markets, namely the Philippines and South Africa. Findings show that relationship marketing strategies should only be focused on customers displaying high relationship intentions rather than, erroneously, investing in relationships with customers based on association length.     

Analysis of customer profit contribution for banks with the concept of marketing mix strategy between 4Cs and 5Ps

This paper takes the high-net-worth customers in the private wealth management division of a case study bank as the research objects, and introduces the concept of marketing mix strategy by combining the 4C (customer, cost to the customer, convenience, and communication) model and 5P (product, price, place, promotion, and people) model in the examination of the attributes of customers and financial advisors in relation to the customer profit contribution and proposes management implications for practitioners. It attempts to establish a win–win business mechanism or marketing strategy that is beneficial to both banks and consumers.     

Trialogue on Facebook pages of grocery stores: Customer engagement or customer enragement?

Abstract

The pervasiveness of social media is compelling businesses to review their way of managing customer experiences. Businesses use social media to interact and engage with customers. Several studies have studied why businesses have adopted social media. However, there is a dearth of research as to why customers interact with businesses on social media in the grocery sector. This paper aims to explore how and why customers react to corporate messages on Facebook pages of Tesco and Walmart. Netnography approach was adopted to gain an insight into the various ways customers engage with the grocery stores on its Facebook pages. This study reveals that social media empower customers, influence the relationships customers have with grocery stores and generate customer engagement. Findings also show that the social customer is both a curse and a blessing to Tesco and Walmart when they create or destroy value for the business. This paper contributes to knowledge by (1) uncovering how customers react to corporate and customer posts on corporate Facebook pages; (2) showing how value can be created and destroyed; and (3) proposing a model illustrating how the main constructs of the study are interconnected: social media, relationship marketing, customer empowerment and customer engagement.