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The rise of numerous competitors and entrepreneurs which has led to a great deal of competition among businesses, compelling them to seek out new customers while retaining their existing ones. Consequently, the importance of delivering exceptional customer service has become crucial, regardless of a business's size or scale [2]. Moreover, understanding the unique needs of each customer is paramount to providing targeted support and developing personalized customer service strategies. This level of comprehension can be achieved through the implementation of a well- structured customer service framework, as different customer segments often share similar market characteristics [5]. To tackle the challenges posed by a large customer base, the integration machine learning has gained traction, surpassing traditional market analytics methods that tend to falter under such circumstances. This paper adopts the k-means clustering algorithm to address this issue [8]. The implementation of the k- Means algorithm, facilitated by the Sklearn library (refer to the Appendix), involves training a program using a dataset comprising 100 patterns and two factors

Purpose The main purpose of this conceptual paper is to identify and explain the technique of branding “Halal” as a marketing strategy to reach and capture a certain market segment (niche), particularly Muslims. Design/methodology/approach The approach of this paper is descriptive based on literature survey as well as the author’s own opinion, experience and judgment. Findings In many cases, particularly in food market, the term “Halal” is being used to attract the Muslim customers’ religious feelings rather than providing them cost-effective value products. Research limitations/implications The paper is expected to contribute to the theoretical base, as it focuses on the use of religious sentiments in marketing that is worth further research conduction. Practical implications The arguments of this paper can be used by the producers of “Halal” products in including certain features that might satisfy the demands of religious Muslims regarding food products. Social implications This paper can be contributive for the greater needs regarding societal and Islamic values. Originality/value This paper is one of the initial attempts to highlight the religious feelings to attract a specific market segment.

The purpose of this paper is to examine differences in factors affecting the probability of online and in-store purchase of telecommunications equipment in the Republic of Croatia. Online questionnaire survey conducted in September 2019 gathered responses that identified respondents’: method of telecommunications services and equipment purchase, their information gathering tools, factors affecting respondents’ telecommunications services and equipment purchasing decisions in general, and online and in-store purchasing decisions. 125 gathered responses were analysed using a binomial logistic regression. The results state that general factors incite respondents to purchase telecommunications equipment and services instore. Factors inciting online purchases are enabling factors and cause respondents to purchase telecommunications services and equipment online. Responses were further divided into subsamples depending on gender and education level. Results are consistent in tested subsamples. In the sample of male respondents, the results are consistent, while the female subsample shows does not exhibit statistically significant results. Furthermore, subsamples that allowed education level differences showed the results are supported for the subsample of respondents with higher education, and are not supported for respondents with secondary education.

인구 및 세대 구조가 변화면서 점차 대면 관계를 꺼리는 고객의 태도 변화가 정보기술의 발달과 스마트폰의 확산으로 더욱 커지고 있다. 이는 정보기술에 익숙해진 현대 고객들의 소비패턴인 효율성 및 신속성과도 부합되는 것으로, 오프라인 망 중심의 유통회사들이 판매 및 서비스 방식을 언택트로 전환하려는 움직임이 활발해지고 있다. 최근 다양한 분야에서 언택트 서비스가 활성화되고 있지만, 뷰티 제품의 경우 고객의 피부타입 및 상태에 따라 제품 선택이 쉽지 않으므로 비대면을 통해 제품을 추천하기가 쉽지 않다. 이와 관련하여 온라인 뷰티 분야에서 제품 추천을 위한 추천시스템 개발 및 추천 관련 연구들이 수행되었지만, 대부분이 설문조사 방법이나 소셜 데이터를 이용하여 추천 알고리즘을 개발한 연구들이었다. 즉, 고객의 피부타입이나 제품 선호도 등의 실제 사용자 정보를 기반으로 세그먼트를 분류한 연구는 부족하였다. 그리하여, 본 연구에서는 뷰티 분야에서의 언택트 서비스 중의 하나인 모바일 애플리케이션의 고객 정보와 검색 로그 데이터를 기반으로 머신러닝 기법의 K-prototypes 알고리즘을 이용하여 고객 세그먼트를 새롭게 분류하고, 이를 기반으로 언택트 마케팅 전략 방안을 제안한다. 본 연구는 머신러닝 기법을 이용하여 새롭게 고객 세그먼트를 분류함으로써 관련 기존 문헌의 범위를 확장하였다. 더불어, 언택트 서비스라는 새로운 소비 트렌드를 반영하여 고객 세그먼트를 분류하고, 이를 기반으로 뷰티 분야의 언택트 서비스에 활용할 수 있는 구체적인 방안을 제시했다는 실무적 의의가 있다.

After deregulation of the airline industry, revenue management has evolved from flight leg and flight segment-based inventory controls to origin and destination inventory controls. Advances in revenue management have always focused on more granular controls to maximize revenues. Revenue management of individual seats is the most granular level of inventory control by customer segment or individual customer. This paper discusses the evolution of revenue management leading up to the inventory control of individual seats.

We develop S4, a Statistically-Sound Segment Search framework that combines principled data partitioning and sound statistical testing to verify common hypotheses in retail data and return interpretable customer data segments. Our framework accommodates one-sample, two-sample, and multiple-sample testing, to provide various aggregations and comparisons of customer transactions. To control the proportion of false discoveries in multiple hypothesis testing, we enforce an FDR-controlling procedure and formulate a unified optimization problem that returns customer data segments that satisfy the test for a given significance level, maximize coverage of the input data, and are within a risk capital. We develop a greedy algorithm to explore different data partitions and test multiple hypotheses in a sound manner. Our extensive experiments on four retail data sets examine the interaction between significance, risk and coverage, and demonstrate the expressivity, usefulness, and scalability of S4 in practice.

The year 2010 is Soccer World Cup year in South Africa. From watching the press and other media it quickly becomes apparent that this event is perceived as something of a cash cow to be used (and sometimes even abused) to generate maximum profit for certain industries and its businesses. Complaints have been made about airlines and accommodation establishments hiking prices excessively. The tourism industry has been warned about the negative impact such exorbitant prices may have on tourism in the future as South Africa may no longer be considered as a value-for-money destination. The hiking of prices is based on an anticipated increase in demand for certain services and products caused by the expected influx of soccer tourists. Businesses world-wide employ different pricing strategies to try and optimize revenue. One such pricing strategy that is employed is to differentiate between citizens and foreign nationals when charging for a service or product. This strategy in the context of the tourism industry is the focus of this note. Whilst the tourist is visiting South Africa s/he may want to visit some attractions and it is often at these places that an interestingsituation can be observed. International tourists have to pay one price whereas citizens pay a reduced price. For instance, a visit to the website of the Addo Elephant National Park reveals that SANParks asks different prices – for South African citizens and residents R30 per day visit, SADC nationals R60 per day visit, and foreign visitors R130 per day visit to the Addo Elephant National Park. Similar price differentiation is employed by private businesses as well. Other jurisdictions in Africa also make use of similar customer-segment pricing strategies. The Ugandan Wildlife Authority differentiates between admission fees for foreign non-residents and East-Africans to protected areas such as Lake Mburo and the Semuliki National Park. The Consumer Protection Act 68 of 2008 (hereinafter “the CPA”), once operational, will prohibit the charging of different prices for any goods or services to any persons or category of persons on the basis of one or more of the grounds of unfair discrimination contemplated in section 9 of the Constitution of the Republic of South Africa, 1996 (the Constitution) or Chapter 2 of the Promotion of Equality and the Prevention of Unfair Discrimination Act 4 of 2000 (hereinafter “the Equality Act”), amongst others. Does this mean that suppliers of services and products to tourists who differentiate in the prices asked between citizens and non-citizens will fall foul of this provision of the CPA? This is the question this note will endeavour to answer.

They are seeing the development of internet users in Indonesia which is growing rapidly. This is the basis for the emergence of applications that can facilitate the community in doing their work. One of them is doing work in terms of finding a homestay, especially in the student segment. The phenomenon found, the information offered is incomplete and the absence of services to help move goods. This study aims to determine the consumer profile which includes perceptions and expectations for the homestay application customer segment, namely students, so that it can be a reference for creating value propositions that are relevant for homestay applications. The study uses a qualitative approach that is descriptive. Data collection techniques used include interviews, observation, and documentation. In this study, the design of a consumer profile consists of three parts, namely customer jobs, customer science, and customer gains in the Value Proposition Design taken from Alexander Osterwalder and Yves Pigneur. In this study, generated perceptions and expectations of consumers of boarding room applications, among others, requires complete information, a lot of boarding references, there are features of ratting, booking, and chat forums, as well as there are goods transport services.

Technology entrepreneurship is an emerging domain in the field of entrepreneurship and the practice-oriented method called the Lean Startup approach (LSA) has made a big impact in this area. However, many technology startups continue to have survivability issues. This study focuses on understanding the theory of entrepreneurial pivoting and its associated factors. In this study, we have collected secondary data comprising 80 tech startups to validate the different types of pivots they pursued by the companies and the factors that triggered the pivoting. The most common pivots among these were found to be customer segment pivot and customer need pivot.

Since its inception, revenue management has evolved from flight leg and flight segment based inventory controls to origin and destination inventory controls. Advances in revenue management have always focused on more granular inventory controls to maximize revenues. Revenue management of individual seats is the most granular level of inventory control by customer segment or individual customer. This chapter also summarizes all the major milestones in revenue management leading to the last frontier - the inventory control of individual seats.

Firms need to deliver high quality customer service to retain clients and improve performance. For online companies, a key customer segment is the highly technologically skilled millennials. This s...

Tujuan penelitian – to observe whether or not feasible if done online and offline sales “sambal teri” merk Tera Teri and how Business model canvas at its business model elements 9.Desain/Metodologi/Pendekatan – The data that we get for this research, namely secondary data obtained at the library, trade organizarrions, the Central Bureau of statistics “sambal teri” merk Tera Teri business is a business that generates side dishes prepared with typical consumption of Indonesia. Temuan - Financial feasibility calculation results, value NPV TeraTeri > 0, amounting to Rp 1.159.716.330 for which it can be concluded that the business is eligible to run. Payback period that is required is for 1 year 5 months 4 days.Keterbatasan penelitian - The intended customer segment by TeraTeri is anyone interested in the chili sauce and “ikan teri” in the region of DKI Jakarta and focused customer segments, namely employees who do not have much time to cook and can't cook so choose food ready consumptionOriginality/value – Customer Relationship Tera Teri activity, using social media like Instagram and Line with all customers

The paper reviews an assessment regime for its capacity to engage university learners, enabling them to design radically new business offerings. We explore the effect of the briefing approach on defining the customer/offering match. This study is framed by participatory action research, where data draws on two distinctive module deliveries: one where the design brief asks learners to generate the offering first and then shape the customer segment. The second one supplies an archetype and asks learners to define customer first and then develop the offering. Our analysis reveals that learners’ engagement with the design brief prompts an emergence of five patterns of learners’ responses, leading to conclusions that the nature of design brief elements has an impact in shaping the overall learning. Moreover, going from customer to offering appears to generate better iterations between the two, overall leading to learners’ engagement with the process not simply seeking an outcome.

The increasing number of vegetarians in Western societies constitutes an opportunity for restaurants. The aim of this chapter is to explore possible experience design strategies for plant-based restaurants targeting a customer segment that is not limited to vegetarians. Scholarly contributions about neotribes and experience design are used to investigate the case of an Italian plant-based cafe that has a broad spectrum of customers. The findings suggest that while several design strategies applied to generic restaurants are also relevant for plant-based restaurants, some peculiarities of this specific case may require additional considerations. The investigated case shows that the design strategies concerning the experience theme and the cues supporting the chosen theme, in particular food quality and atmosphere, are crucially important and require very competent human resources, including the staff working in the kitchen and in direct contact with the customers as well as professionals such as architects.

To attract and retain consumers born in the era of social networks and grown up with the smartphones requires marketing and customer relationship management to be reshaped and adapted to their needs, habits, and aspirations. Digital natives expect digital customer experience through all the stages of the customer journey. Besides the challenges common for all industries, for mobile operators this additionally means to satisfy the customer segment which has the most demanding requirements in terms of mobile network and services quality but perceive it as a commodity. This paper addresses the topic of relationship between Generation Z and mobile operators, leveraging on the survey made among post-Millennials in Serbia. It presents their preferences and expectations and outlines the most important implications this might have on mobile operator’s business.

Author(s): Barbose, Galen L; Darghouth, Naim R | Abstract: Berkeley Lab’s annualnTracking the Sunnreport summarizes installed prices and other trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2018, with preliminary trends for the first half of 2019. The analysis is based on project-level data from approximately 1.6 million systems, representing 81% of all distributed PV systems installed in the United States through the end of 2018.Key findings from this year’s report include the following:Distributed PV Systems Keep Getting Bigger, More Efficient.nMedian system sizes in 2018 grew to 6.4 kW for residential and roughly 50 kW for non-residential systems, though the spread in system sizes is also quite wide—especially for non-residential systems, with 20% larger than 200 kW. Increasing system sizes over time partly reflect a steady growth in module efficiencies, which rose a full percentage point to a median of 18.4% among systems installed in 2018. The report also details trends among other system design and project characteristics, including panel orientation, inverter loading ratios, solar-plus-storage, use of module-level power electronics, third-party ownership, and non-residential host customer segments.Installed Prices Continued to Fall through 2018 and into 2019.nThe report focuses its analysis of installed prices specifically on host-owned distributed PV systems. Among these systems national median installed prices fell year-over-year by 5-7%, depending on the specific distributed PV customer segment. Those declines are broadly in-line with trends over the past five years. National median installed prices in 2018 were $3.7/W for residential, $3.0/W for small non-residential, and $2.4/W for large non-residential systems. Considerably lower prices are observed among many systems, however.Installed Prices Vary Widely Across Projects.nFor example, among residential system installed in 2018, prices for host-owned systems ranged from $3.1/W to $4.5/W between the 20thnand 80thnpercentile levels, and prices for small and large non-residential systems varied across similarly wide ranges. The report explores sources of that pricing variability, including differences in system size, module- and inverter-type, mounting-type, location, installer, host customer-type, and new construction vs. retrofits. This year’s report also contains a multi-variate regression analysis to isolate the effects of individual pricing drivers, including characteristics of the local PV market related to market size, competition, and installer experience, among other factorsnA public version of the underlying dataset is available for downloadnat https://emp.lbl.gov/tracking-the-sun.

This note explores measures of domestic and export flows based upon the Compustat customer segment data and compares our measures with official statistics.

The customer number of Mobile Virtual Network Operators (MVNOs) is increasing in Japan, though the mobile phone market in Japan was mainly shared by three Major Mobile-Carriers (3MMC): docomo, au and SoftBank. The purpose of this study is to understand the preference for 3MMC vs. MVNOs considering the current mobile-phone market. In order to clarify the difference of the characteristics between 3MMC customers and MVNO customers, we classified these two customer segments into two customer segments: stable customers and unstable customers, respectively. Stable customers mean customers who would like to continue to use the same mobile carrier. We analyze the differences between two segments: stable 3MMC customers and stable MVNO customers on the basis of a new original survey conducted in January 2018. And we analyze the differences between iPhone users and Android phone users in each customer segment. Supervised learning models to create differential descriptions of these customer segments are constructed in order to clarify the differences between these segments

In light of the complex customer behaviour and customer journeys in omnichannel retailing, this study aims to investigate customer co-creation behaviour, customer response and customer experiential values as critical aspects of the customer journey, and examine their impact on the level of customer journey satisfaction. The results confirmed the significance of all factors, except information seeking and arousal, in all phases and exploration in the post-purchase phase, on customer journey satisfaction. For a further examination, this study classified the participants into three different segments according to their journey pattern and scrutinised whether the impact of the three predictors of customer journey satisfaction varied across customer segments. The analysis showed that customer segments were fragmented. The impact of customer co-creation behaviour, customer response and customer experiential values on customer journey satisfaction varied across the three customer segments. A heatmap highlighted the most influential factors of each customer segment. The study yielded several theoretical contributions and insights into omnichannel customers for managers.

In this study a firm in a monopoly environment is considered. The firm sells two types of perishable products using a commodity bundling practice. This study aims to find the optimal strategy of selling these products. We determine whether they should be offered separately or in a bundle, define their optimal prices and determine the initial amount of the bundle which should be made from components with limited stocks. A benefit-lost cost in a case that the customer segment does not find their desirable product is considered along with a shortage cost in a case that the customer segment selects a product or the bundle but there is not enough of it to satisfy all of the customer segment demands. In this study several different customer segments with different behaviors and reservation prices are assumed. The problem is solved using the Mixed-Integer Non-Linear Programming solver in LINGO software and a Genetic Algorithm. Finally, the superiority of obtained model and results are presented. This is the first study to locate optimal strategy of selling two types of perishable products using a commodity bundling practice. This study introduces a new mathematical optimization model based on previous gaps. Moreover, it covers the significant gaps of previous studies with respect to both practical and theoretical aspects.

Customers, increasingly, seem concerned about social and environmental issues that often affect their buying behavior and attitudes toward the quality of goods and services purchased. Despite this trend, there exists little empirical research regarding how socially responsible consumers evaluate services and service quality. In this study, we investigate the role that consumer attitudes toward social responsibility play in evaluating service quality. The results of factor analysis show that social responsibility is a salient dimension of service quality and that high socially responsible customers use the concept of social responsibility more pronouncedly than others when evaluating service quality. Our study contributes to the current literature on the evaluation of service quality by a growing customer segment and outlines implications for managers and for future research.

W niniejszym artykule seniorzy zostają przedstawieni jako nowy i odrębny segment klientów na rynku bankowości detalicznej, którym mogą się stać w niedalekiej przyszłości. To ogólne założenie prowadzi do zdefiniowania głównego celu artykułu, którym jest przeanalizowanie i identyfikacja głównych problemów związanych z ochroną seniorów na rynku bankowości deta-licznej. Rozważania umiejscowione są w temacie zrównoważonych finansów. Dochodzi się do konkluzji, że o ochronie seniorów można mówić w przypadku zwiększonej przejrzystości rynku, czytelnych umów bankowych oraz popularyzacji edukacji finansowej wśród seniorów. In the article the Author tends to present elderly as a new and separate customer segment on the retail banking in the nearest feature. This general assumption leads to define the main goal of the article as an analyse and identification main problems concerned with seniors protection on the retail banking market. The considerations are connected with the sustainable finances. Concluding, elderly protection will be possible when the market reach greater transparency, the banking agreement will be more readable and the financial education will be more popularize among the elderly segment.

The distribution industry is one of the main industries and infrastructures in every country's economy. Improving the efficiency of the distribution industry is important as an intermediary link between the manufacturer and the consumer, which has an important share of the cost. One of the factors that help this is the use of modern technologies to manage bulk sales data of customers and find important variables on their purchases' behaviours. In this study, first data mining methods are used to segment the pharmaceutical industry customers based on the RFML model and then these results are evaluated. In the following, in order to help decision-makers and marketing managers of this industry, practical suggestions are presented for each group of the customers. The results could help marketing and sales managers of this industry to have more effective planning for each customer segment and developing their future program for their visitors.

Today, brick-and-mortar retailers with integrated online shops have many alternatives to increase their customers’ shopping satisfaction: They could invest in (for the retailers) new physical store technologies (e.g., beacons or magical mirrors if not implemented up to now), new online shop technologies (e.g., visual tagging or webcams), or in new less technology-based improvement options (e.g. events or product testing). We propose an adapted Kano based stage-gate approach to support multichannel retailers confronted with such selection problems. The approach is applied to a major European sporting goods retailer. 37 improvement options are pre-selected and evaluated by current and potential customers. It can be shown that instore returns, instore services, reserve&collect, click&collect, customization, product testing, and magical mirrors are drivers of satisfaction for the current customers and should be implemented in contrast to, e.g., geofencing or beacons. The potential customers are more technology-savvy, but show similar categorizations as a current customer segment and so confirm the selection.

La investigación tiene por objetivo analizar el marketing de guerrilla aplicado a empresas del sector de equipamiento dental en el Ecuador. Se generó desde un tipo descriptiva con diseño de campo no experimental, se abordó una muestra poblacional de 123 profesionales ligados a empresas odontológicas de la provincia de Azuay - Ecuador. El marketing de guerrilla se ha convertido en la forma más económica de llamar la atención de los clientes para posteriormente poder presentar la propuesta de valor que terminará en la conversión de un prospecto a un futuro cliente. El estudio del segmento de clientes del mercado de productos odontológicos revela que las nuevas modalidades de uso incrementado de redes sociales y aplicaciones digitales para la comunicación abre una amplia gama de posibilidades para el uso de recursos de bajo costo que pueden ser empleadas por las empresas para enfocarse en el llamado marketing de guerrilla digital.

In recent years, firms launch interactive technologies to engage and communicate with their customers. Branded mobile applications (apps) are one example. In light of this trend, understanding mobile adopters' cross-platform and engagement behavior is essential in managing customer relationships. This research proposes the context complementarity hypothesis and shows that a branded app is complementary to a firm's other engagement platforms such as PC and mobile websites. PC and app users are also more likely to respond to e-mail promotional offers and have higher spending than non-users. These influences differ by customer segment and brand relationship. Specifically, low-tier customers show a more significant increase in cross-platform engagement than customers who are already loyal. On the other hand, high-spending customers that are relatively new to the firm show a higher increase in spending and promotional responses than low-tier customers. In addition to substantive insights, we conclude with managerial implications and future directions regarding branded apps, mobile and digital platforms, and customer relationship management.

The data collected from a firm’s online account enables enterprises to understand their consumers better and accordingly adjust their business processes. The development of effective customer relationship management strategies and the enhancement of consumers’ experience with customer service centers require accurate prediction of future customer telephone queries. In this paper, we leverage the collected big data from customers’ activities at a firm’s online account to estimate the likelihood that an individual customer will phone the firm’s contact centers within the next thirty days. Our predictive modeling approach has two distinguished characteristics: (i) predicting calls at an individual customer level, and (ii) incorporating the big data from online account activities, in addition to the customer’s past telephone queries. The individual-level data used in this study is from contact centers of a major U. S. insurance firm. Various classes of features specifying the customer segment, recency and frequency of customer interactions are considered. Different neural network architectures are investigated to achieve the best prediction accuracy. Out-of-sample performance analyses evince the capability of the developed model to accurately predict future policyholders’ calls at both the individual and aggregate levels.

The availability of big data collected by multichannel contact centers creates opportunities for businesses to more accurately predict future interactions with their customers. This paper presents a data-driven modeling approach to forecast the likelihood of a call arrival by an individual customer within the next thirty days, based on the multichannel data from contact centers. This model incorporates information related to the past Web activities of an individual customer to predict his future telephone queries. Our study relies on big datasets from contact centers of one of the largest U.S. insurance companies. Various characteristics related to the customer segment, recency and frequency of customer interactions, and cross-class features are considered. We find evidence that some of the recent web activities of a policyholder significantly increases the probability that the policyholder would make a telephone call in the next 30 days. In addition, recency and frequency of contacts impact the probability of the policyholder's call, for a specific set of reasons for past contacts.

We consider a retailer with limited inventory of identically priced, substitutable products. The retailer faces a market with multiple segments of customers that are heterogeneous with respect to their product preferences. Customers arrive sequentially, and the firm decides which subset of products to offer to each arriving customer depending on the customer’s preferences, the inventory levels, and the remaining time in the season. We show that it is optimal to limit the choice set of some customers (even when the products are in stock), reserving products with low inventory levels for future customers who may have a stronger preference for those products. In certain settings, we prove that it is optimal to follow a threshold policy under which a product is offered to a customer segment if its inventory level is higher than a threshold value. The thresholds are decreasing in time and increasing in the inventory levels of other products. We introduce two heuristics derived by approximating the future marginal expected revenue by the marginal value of a newsvendor function that captures the substitution dynamics between products. We test the impact of assortment customization using data from a fashion retailer. We find that the potential revenue impact of assortment customization can be significant, especially when customer heterogeneity is high and when the products’ inventory-to-demand ratios are asymmetric. Our findings suggest that assortment customization can be used as another lever for revenue maximization in addition to pricing.

Improving service quality may increase passengers' satisfaction and enhance the competitiveness of an airline in the market. Importance-performance analysis (IPA) is a simple and effective technique that can assist practitioners in prioritizing passenger attributes when taking steps to enhance service quality and customer satisfaction. However, the importance and performance attributes are not independent of each other when using self-stated importance. A revised IPA was used to measure the importance of the service attribute in this paper, which can prevent customer satisfaction from affecting the importance evaluation. Based on customer segment theory, passengers' evaluations of airline service quality are collected by a survey among business passengers, leisure passengers, high frequency flyers and low frequency flyers. The direction of an effective and appropriate action to improve service quality is proposed and is believed to be conducive for airline managers to achieve a competitive advantage.

This chapter contains techniques for planning the process architecture. For this purpose, market segments are created from four elements of the business model. For the most important market segment, its customer segment is described by uniform criteria. The customer process with the most important requirements is developed on this basis in order to derive the appropriate process architecture.

Children, youths and young adults are becoming a group of clients increasingly served by banks. Due to the lack of regular incomes and an unstable financial situation, these people are not the key customer segment for the banks. Nonetheless, they are treated as prospective clients that are expected to bring profits in the future. An offering of products and services to customers with low financial knowledge and poor experience in finance is a serious ethical concern. Such offerings may bring vital social, economic and financial benefits but also may generate substantial risks. The goal of this paper is to characterise and evaluate ethical aspects of the offering of bank products to young people. For the purpose of the work we reviewed literature and used SWOT analysis to identify the strengths, weaknesses, opportunities, and threats related to the offering of bank products and services to children, youths, and young adults and considered them in an ethical context. We also conducted a survey using CAWI technique on a group of 209 young people. Research shows that young people perceive banks and their offers as safe, and this positively affects their financial knowledge.

The target markets were defined as a basis for the definition of strategic businesses (see Sect. 7.4). Now, all of these markets are thoroughly examined. In addition, the markets that are important in view of diversification (see Chap. 14) are considered. This means that the analysis described in the following text must be carried out in parallel for several markets.

This study of the transformation of the mobile device industry examines how cross-boundary disruption (XBD) superseded the incumbents’ sustaining innovation, which helps explain the rapid rise of Apple and Google Android and the equally rapid fall of Nokia and other incumbents between 2007 and 2013. Four concatenated strategic factors limited the incumbents’ capacity to adapt: (1) incumbents’ market myopia about latent unserved needs of the high-end customer segment, (2) incumbents’ dynamic capabilities gaps for meeting these needs, (3) demand shift timing of high-end customers toward the disruptors’ radically innovative products, and (4) the rapid growth of novel ecosystems around the disruptors’ technology platforms. Graphical interpretation further elucidates these concatenated strategic factors and suggests computational implications. The paper’s qualitative, graphical and computational insights help formulate a conceptual framework of XBD-from-above, which contributes to theory development about inter-industry disruption and transformation.

Little is known about the effectiveness of casino free-play campaigns, despite hundreds of millions of dollars in annual redemptions. These costly play incentives are awarded to individual players, based largely on management’s evaluation of their historical play. Extant campaign-level research suggests these incentives may not be effective in driving spend per visit, but there has been no attempt to examine efficacy across player tiers (e.g., light, medium, and heavy users). Analysis of 365 days of performance data from a Las Vegas Strip casino produced varied results across tiers, but all tier-level findings indicated a failure to recover the face value of the free-play incentives. While no support was garnered for the house money effect, the results were consistent with the notion of loss aversion. The methodological approach outlined herein provides the means to critically evaluate free-play offers at the tier level, fast-tracking campaign optimization via more targeted revisions.

Customer churn prediction literature has been limited to modeling churn in the next (feasible) time period. On the other hand, lead time specific churn predictions can help businesses to allocate retention efforts across time, as well as customers, and identify early triggers and indicators of customer churn. We propose a dynamic churn prediction framework for generating training data from customer records, and leverage it for predicting customer churn within multiple horizons using standard classifiers. Further, we empirically evaluate the proposed approach in a case study about private banking customers in a European bank. The proposed framework includes customer observations from different time periods, and thus addresses the absolute rarity issue that is relevant for the most valuable customer segment of many companies. It also increases the sampling density in the training data and allows the models to generalize across behaviors in different time periods while incorporating the impact of the environmental drivers. As a result, this framework significantly increases the prediction accuracy across prediction horizons compared to the standard approach of one observation per customer; even when the standard approach is modified with oversampling to balance the data, or lags of customer behavior features are added as additional predictors. The proposed approach to dynamic churn prediction involves a set of independently trained horizon-specific binary classifiers that use the proposed dataset generation framework. In the absence of predictive dynamic churn models, we had to benchmark survival analysis which is used predominantly as a descriptive tool. The proposed method outperforms survival analysis in terms of predictive accuracy for all lead times, with a much lower variability. Further, unlike Cox regression, it provides horizon specific ranking of customers in terms of churn probability which allows allocation of retention efforts across customers and time periods.

Following the introduction of the well-known Bass model and its variations to model adoption of a new product, compartmental modeling has emerged, in which the adoption pattern is modeled at the level of each compartment (or customer segment). Compartmental models add spatial and psychographic segments to Bass-type models which can allow modelers to approximate the heterogeneity, clustering and communication network of customers, while retaining an analytical structure. These models have been mainly explored in the context of demand forecasting and describing customer behavior, but their suitability as a scalable modeling tool to support large scale marketing and/or operational decision making is not explored. In this paper, we propose a flexible compartmental model and assess its suitability in terms of use of data, adherence to micro-level customer behavior, and use in large scale decision making. We show the merits of the CDE model by carrying out an extensive simulation study and also estimation on data on boradband adoption. We find that compartmental models result in estimates that are drastically less biased and can predict the shape of the adoption curve significantly better than what can be achieved by the Bass model. Even though these models can be scalable to capture large number of segments, we show that these improvements can still be observed with even a small number of segments (in contrast to what has been hypothesized in the literature), and are not sensitive to errors in the underlying process of customer segmentation. Therefore, the analytical structure of compartmental models can be further explored to further support large scale marketing and operational decision making, as they do not inherit the major shortcomings of Bass-type models while they capture the effect of customer clustering and interactions. Even though the focus of this paper is on new product adoption, compartmental modeling can also be successfully utilized in diverse physical, biological, and social settings that are governed by similar dynamics.

Different shop types have different life cycles: introduction, growth, stagnation and decline. The form of supermarkets is in a stage of decline in each EU country.ÂÂÂ For customers coming to the supermarkets of Coop Co., in Szeged is typical to do their shopping every day or more times a week. Shoppers come to do mainly their daily shopping in the shops. The main reasons for choosing them were the wide range of goods and the suitable accessibility of shops. Coop has its own brand which is very popular with customers. There are customers who directly come to the shops to buy products with this brand. Shoppers would extend the range of products with Coop-brand and also would like to see longer opening hours. The customer segment involves people living close to the shops. Our questionnaire survey supports these statements.

It is becoming increasingly important for firms to know when to take steps to reduce buyers' uncertainty about products and services. This paper focuses on investments that firms can make to reduce buyers' uncertainty about taste-related product attributes. Using an analytical model, we show that firms should disclose more taste-related information when the customer segment they directly target represents a larger share of the overall market. We further show that there are practical ways by which managers can decide if such disclosure investments are financially beneficial to their firms. Specifically, we show that the variance of consumer reviews can guide such decisions. The paper's main contribution to the extant literature is to show that firms must consider the variance, but not the mean, of buyer reviews, to determine the need to invest in reducing consumer uncertainty about taste-related attributes. The papers's findings are managerially important due to the ubiquity of consumer reviews. They are novel because most of the previous literature views the mean of the review as the key indicator. Finally, they are general in their applicability since they are independent of any assumptions about heuristics that buyers may use to ascertain product quality from the reviews of previous buyers. © 2013 M.E. Sharpe, Inc. 30 2 269 299

The primary purpose of a current strategy valuation is to determine where a business is creating value, where it is destroying value, and why, under the strategy currently being pursued. It is completed at a disaggregated level, and when done at a customer segment level, provides both a starting point from which to pursue, and a datum or benchmark against which to compare, potentially higher value alternative strategies.

Paint a robust yet lean picture of an idea on a canvas to help those seeking to understand the idea and the value of the idea.

The concept of business model innovation is currently the focus of many discussions. This is for good reason, since the forthcoming Internet of things offers the possibility to shape business in new ways.

In marketing analytics, customer segmentation (clustering) divides a customer base into groups of similar individuals, while buyer targeting (classification) identifies promising customers. Both customer segmentation and buyer targeting help the business to improve marketing performances by allocating resources to the most profitable customers. Due to the heterogeneity across the customer groups, some studies have been made on combining the tasks of customer segmentation and buyer targeting for tailored marketing strategies. However, these efforts usually combine these two tasks in a simple step-by-step approach. It is still unclear how to implement these two tasks in a more integrated and optimized way, which is the research objective of this paper. Specifically, we formulate customer segmentation and buyer targeting as a unified optimization problem. Then, the customer segments are adaptively realized during the targeting optimization process. In this way, the integrated approach not only improves the buyer targeting performances but also provides a new perspective of segmentation based on the buying decision preferences of the customers. The unified customer segmentation and buyer targeting method not only quantifies the purchase tendency of a specific customer but also characterizes the buying decision behaviors at the segment level. We also develop an efficient K-Classifiers Segmentation algorithm to solve the unified optimization problem. Moreover, we show that the customer segmentation based on the buying decision preferences can also be consistent with the features on customer profiles. Finally, we have performed the extensive experiments on several real-world Business to Business (B2B) marketing data sets. The results show that our approach offers not only more accurate targeting of promising customers but also meaningful customer segmentation solutions with interpretable buying decision preferences for each customer segment.

General strategic planning may show that the served markets do not represent a basis for the further development and future success of the company. The markets of many Western European and North American companies are saturated. As new competitors from emerging markets are entering these markets, competitive intensity is high. Entry into growing markets, especially in emerging countries, represents a way to create a future for the company. This chapter shows how general strategic planning can lead to the analysis of new markets and to the planning of market entry into attractive new markets. Portfolio analysis provides a picture of the current situation. An extended version of the Ansoff matrix enables to identify growth opportunities in a systematic way. Finally, the different opportunities for growth are compared. This comparison shows that geographic diversification through the development of new markets is an attractive option.

Under the assumption that customers divided into different independent segments have heterogeneous preference on products of a product family and sensitivities to their prices, this paper proposes an ATO (Assemble-to-Order) manufacturer production and pricing model to study how the ATO manufacturer meets the heterogeneous demands of consumers from different segments by product selection and pricing. It is found that a product family ATO manufacturer would better always keep more than one type of product are available in the market to better meet customers' heterogeneous demands and provide only one flagship product to every customer segment.

As populations around the world age, brand choice behaviour by older customers becomes an increasingly important issue for marketers. This is especially the case in Japan, which has the largest older customer segment as a proportion of the population of any country. Our study measures brand choice behaviour of the older customer segment in Japan in fast-moving consumer goods categories. We employ an 11-point purchase probability scale, the Juster, to calculate brand performance measures such as penetrations, buying frequency and sole buying for three age-based customer segments. The Juster output is used as input into a mathematical model, the Dirichlet, for benchmarking the brand performance measures. The findings here reveal new insights into the brand purchase behaviour of older customers. There are more similarities than differences between the brand purchase of younger and older customers in most categories analysed here. The results have practical implications for understanding and creating appropriate marketing strategies for the older customer segment. Our study also demonstrates a novel method for analysis of brand choice data collected via a survey instrument, as compared to the traditional consumer panel data. The research framework in our study is recommended for further empirical research in other regions where demographic changes are presenting challenges to marketers, and where panel data are often not easy to obtain.

This study aimed to understand male spa-goers (a growing customer segment) in Hong Kong hotel spas by examining empirical data collected via questionnaire surveys. The results of the study indicate that the most cited reason why male spa-goers patronized a hotel spa was relaxation, and the most consumed service was body massage. The importance–performance analysis categorized 30 spa-related attributes into the four quadrants calling for hotel spa management's attention in reexamining their spa operations and features. Furthermore, five performance factors were derived: Environment, Reliability, Service Experience, Value, and Augmented Service Quality. In particular, the Environment factor was the common factor that significantly influenced male hotel spa-goers' overall satisfaction, likelihood to revisit, and likelihood to recommend. Implications are discussed.

While many offline retailers have developed informational websites that offer information on products and prices, the key question for such informational websites is whether they can increase revenues via web-to-store shopping. The current paper draws on the information search literature to specify and test hypotheses regarding the offline revenue impact of adding an informational website. Explicitly considering marketing efforts, a latent class model distinguishes consumer segments with different short-term revenue effects, while a Vector Autoregressive model on these segments reveals different long-term marketing response. We find that the offline revenue impact of the informational website critically depends on the product category and customer segment. The lower online search costs are especially beneficial for sensory products and for customers distant from the store. Moreover, offline revenues increase most for customers with high web visit frequency. We find that customers in some segments buy more and more expensive products, suggesting that online search and offline purchases are complements. In contrast, customers in a particular segment reduce their shopping trips, suggesting their online activities partially substitute for experiential shopping in the physical store. Hence, offline retailers should use specific online activities to target specific product categories and customer segments.

Sales force sizing and sales effort allocation methods vary from simplistic rules of thumb to sophisticated analytical procedures. The former methods are easy to understand and implement, but they are typically inaccurate and probably invalid. The latter procedures may provide more accurate and valid results, but they are more difficult to explain to management and require data collection and analysis that are often quite elaborate. This paper proposes a method of optimal estimation of total sales effort level and time allocation that combines the advantages of both approaches. For each customer segment, this method accounts for the so far neglected, but relevant, optimal call effort allocation between number of calls per account during a planning period and length of sales calls. A case study illustrates this method. Resume Les methodes de determination de la taille et de l'allocation des efforts de vente vont des regles empiriques les plus simples aux procedures analytiques les plus complexes. Les premieres sont faciles a comprendre et a appliquer, mais elles sont imprecises et souvent non valides. Les autres methodes peuvent donner des resultats plus exacts, mais elles sont plus difficiles a expliquer aux managers et necessitent souvent une collecte et une analyse de donnees fort laborieuses. Le present article propose une methode d'estimation optimale de la taille et de l'allocation des efforts de vente qui combine les avantages des deux approches. Pour chaque segment de la clientele, la methode rend compte de l'allocation optimale (souvent negligee, mais pertinente), de l'effort de vente entre le nombre de visites a faire a un client pendant une periode de planification et la longueur des visites. Un cas concret illustre la methode.