scholarly journals Analyzing Patients’ Values by Applying Cluster Analysis and LRFM Model in a Pediatric Dental Clinic in Taiwan

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hsin-Hung Wu ◽  
Shih-Yen Lin ◽  
Chih-Wei Liu
Keyword(s):  
Cluster Analysis ◽  
Customer Value ◽  
Marketing Strategies ◽  
Customer Relationship ◽  
Relationship Matrix ◽  
Monetary Model ◽  
Dental Clinic ◽  
Self Organizing Maps ◽  
Different Types ◽  
Customer Values

This study combines cluster analysis and LRFM (length, recency, frequency, and monetary) model in a pediatric dental clinic in Taiwan to analyze patients’ values. A two-stage approach by self-organizing maps andK-means method is applied to segment 1,462 patients into twelve clusters. The average values ofL,R, andFexcluding monetary covered by national health insurance program are computed for each cluster. In addition, customer value matrix is used to analyze customer values of twelve clusters in terms of frequency and monetary. Customer relationship matrix considering length and recency is also applied to classify different types of customers from these twelve clusters. The results show that three clusters can be classified into loyal patients withL,R, andFvalues greater than the respective averageL,R, andFvalues, while three clusters can be viewed as lost patients without any variable above the average values ofL,R, andF. When different types of patients are identified, marketing strategies can be designed to meet different patients’ needs.

An LRFM Model to Analyze Outpatient Loyalty From a Medical Center in Taiwan

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110318
Author(s):  
Shu-Hui Chao ◽  
Mu-Kuan Chen ◽  
Hsin-Hung Wu
Keyword(s):  
Medical Center ◽  
Hospital Management ◽  
Monetary Model ◽  
Self Organizing Maps ◽  
Differentiation Strategy ◽  
Care Services ◽  
Optimal Service ◽  
Different Types ◽  
And Cluster Analysis ◽  
Service Strategies

This research is intended to study the behaviors of outpatients in a medical center and constructs a set of data exploration procedures such that hospital management can deal with patient relationship management more effectively. This study adopts LRFM (length, recency, frequency, and monetary) model and cluster analysis, including self-organizing maps and K-means method, to categorize 321,908 outpatients of the medical center into 12 groups and then uses the multidimensional customer clustering philosophy to classify the outpatients. Outpatients can be categorized into five different types of groups, namely, core customer groups, potential customer groups, new customer groups, lost customer groups, and resource-consuming customer groups. In addition, seven types of outpatients based on five types of categories are identified. The similarities and differences of each group based on the patients’ characteristics are analyzed to give differentiation strategy advices for hospital management. Hospital management thus can design the optimal service strategies, provide the best care services, enhance hospital’s performance, and reduce the overall cost to establish quality relationships with outpatients.

scholarly journals A Study of Service Quality of Banks in Mumbai

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Ranjith P V
Keyword(s):  
Cluster Analysis ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Return On Investment ◽  
Customer Relationship ◽  
Customer Profitability ◽  
Efficient Manner ◽  
Different Types

<div><p><em>Service quality improves   customer relationship as far as organizations are concerned. Service quality is about areas like reliability   , empathy, assurance etc which if provided in an efficient manner improves customer profitability and organisation’s return on investment</em></p><p><em>The service given generally helps in retaining customers thereby reducing cost of retention and makes customers happy to deal with the organisation. This is required for all service organisations and it is true for banks also. The aspect of service is vital for institutions dealing with money and so the study focuses on the importance of service in customer.</em></p><p><em>Service quality of different types of banks are studied using tests lime ANOVA and K means cluster analysis to find out the effect on customer satisfaction of different variables and also to find out different customer segments based on their responses. </em></p></div>

Establishing high value markets for data-driven customer relationship management systems

Kybernetes ◽  
2019 ◽  
Vol 48 (3) ◽  
pp. 650-662 ◽  
Author(s):  
Wen-Yu Chiang
Keyword(s):  
Customer Relationship Management ◽  
Customer Value ◽  
Large Scale ◽  
Relationship Management ◽  
Customer Relationship ◽  
Data Driven ◽  
Social Commerce ◽  
Content Type ◽  
Proposed Model ◽  
Customer Values

PurposeOnline customer relationship management (CRM) is an important issue for implementing digital marketing of electronic commerce or social commerce. The purpose of this study is to establish valuable markets for discovering customer knowledge from data-driven CRM systems for enhancing growth rates of businesses. Airline or travel agency industries are online businesses in the world. Therefore, the industries in Taiwan will be an empirical case for this study.Design/methodology/approachThis research applied a procedure with an applied proposed model for establishing valuable markets from data-driven CRM systems. However, the study used a proposed customer value model (recency, frequency and monetary [RFM]; RFM model-based), the analytic hierarchy process (AHP) procedure and a proposed equation for estimating customer values.FindingsFor enhancing the data-driven CRM marketing of the industries, in this research, the market of air travelers can be partitioned into eight markets by the proposed model. As well, the markets can be ranked by the AHP procedure. Furthermore, the travelers’ customer values can be estimated by a proposed customer value equation.Originality/valueVia the applied proposed procedure, online airlines, travel agencies or other online businesses can implement the research procedure as their data-driven marketing strategy on their online large-scale or Big Data customers’ databases for enhancing sales rates.

scholarly journals Penerapan Customer Relationship Management (Crm) Dengan Menggunakan Metode Lrfm Analysis

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Nurdin Lubis
Keyword(s):  
Data Mining ◽  
Cluster Analysis ◽  
Customer Relationship Management ◽  
Customer Loyalty ◽  
Clustering Analysis ◽  
Customer Value ◽  
Relationship Management ◽  
Customer Relationship ◽  
Economic Community ◽  
Asean Economic Community

Masyarakat Ekonomi ASEAN (MEA) atau ASEAN Economic Community telah dibuka. hal ini tak hanya membuka peluang, namun menjadi tantangan pula bagi sektor industri, termasuk industri farmasi nasional. Peningkatan kemampuan industri farmasi nasional dapat dilakukan melalui riset dan peningkatan kemampuanPenelitian ini dilakukan untuk mengetahui informasi mengenai karakteristik pelanggan dari PT Phapros Tbk, sebuah perusahaan yang bergerak pada bidang farmasi. Data yang digunakan yakni data pelanggan dan data transaksi penjualan historikal. Data tersebut kemudian akan diolah dengan LRFM model (Length, Recency, Frequency, Monetary), dan dua tahapan clustering (two stage clustering) yaitu metode ward’s untuk mengetahui jumlah cluster terbaik dan algoritma k-means yang merupakan distance-based cluster analysis untuk melakukan proses operasional clustering. Setelah proses operasional clustering dilakukan, hasil cluster akan dipetakan dengan customer value matrix dan customer loyalty matrix untuk mengetahui karakteristik tiap segmen pelanggan.Hasil yang didapatkan dari studi kasus PT Phapros Tbk menunjukkan bahwa segmen atau grup pelanggan yang terbentuk semuanya memiliki perbedaan statistik yang signifikan, dan dapat dijelaskan dalam konteks strategi marketing. Oleh karena itu, penelitian ini berguna untuk menentukan strategi pengelolaan pelanggan tiap segmen.Key Words: Clustering Analysis, Customer Relationship Management, Data mining, LRFM model.

Developing Service Marketing Through Successful Involvement of Customer

2015 ◽  
Vol 2 (1) ◽  
pp. 6
Author(s):  
_______ Naveen
Keyword(s):  
Relationship Marketing ◽  
Service Marketing ◽  
Marketing Strategies ◽  
Customer Relationship ◽  
Successful Implementation ◽  
Process Automation ◽  
Customer Contact ◽  
Use Of Technology ◽  
Marketing Systems ◽  
Technological Means

Customer Relationship Management has its roots in service marketing which is based in turn on the formative work of Berry (1983) and the IMP. Its purpose is to integrate marketing, sales and service functions through business process automation, technological solutions and information resources to maximize each customer contact. In this way service marketing systems facilitate relationships among enterprises, their customers, suppliers and employees and so provide the technological means to put relationship marketing philosophy into practice. Organizations that fail to keep up with competitor’s service marketing capabilities risk being seriously disadvantaged. However, the use of technology on its own is not sufficient and firms must combine developments in IT with a philosophy that calls for the re-organisation of the entire firm around its customers. This shift will not be easily achieved. Our purpose, based on collaborative Canfield/CSC Computer Sciences Corporation studies, is to identify the pitfalls, and offer advice on the successful implementation of service marketing systems in support of relationship marketing strategies, including an audit of the organization’s readiness to proceed. 

Profiles of Citizenship Orientations Among Youth

Young ◽  
2021 ◽  
pp. 110330882110086
Author(s):  
Iana Tzankova ◽  
Gabriele Prati ◽  
Elvira Cicognani
Keyword(s):  
Cluster Analysis ◽  
Young Adults ◽  
Adolescents And Young Adults ◽  
Political Activity ◽  
Late Adolescents ◽  
Institutional Politics ◽  
Different Types ◽  
Political Activist ◽  
Low Levels ◽  
Citizenship Orientations

Prior studies revealed that low levels of youth political activity are not necessarily indicative of complete disengagement from societal affairs but could be accompanied by interest and latent involvement stemming from a standby or monitorial attitude. However, no prior study has investigated patterns of citizenship orientations including both manifest and latent engagement defined by one’s position towards institutional politics, according to different forms of participation. A questionnaire was filled out by 1,732 late adolescents and young adults in Italy (15–30 years old, M = 19.73, 60.7% female). Cluster analysis identified six profiles of citizenship orientations across different types of participatory activities (political, activist, political online and civic): active trustful, active distrustful, standby trustful, standby distrustful, unengaged trustful and unengaged distrustful. The results showed that each level of engagement—active, standby and unengaged—could be further differentiated between trustful and distrustful based on their attitude towards institutions and the electoral process.

scholarly journals Influence of Customer Relationship Management, Brand Equity, Perceived Product Quality, Perceived Price on Customer Value and Purchase Intention (Studies Philips Light Bulb in Batam)

2017 ◽  
Vol 9 (7) ◽  
pp. 122 ◽  
Author(s):  
Lukmanul Hakim ◽  
Nanis Susanti ◽  
Ujianto
Keyword(s):  
Customer Relationship Management ◽  
Brand Equity ◽  
Purchase Intention ◽  
Customer Value ◽  
Relationship Management ◽  
Perceived Quality ◽  
Customer Relationship ◽  
Light Bulb ◽  
Perceived Price

This study tried to determine and analyze the deeper understanding of the influence of customer relationship management, brand equity, perceived of product quality, perceived value and price to the customer at the customer's purchase intention Philips light bulb in Batam.The population in this study are all users (consumers) electric light bulb philips brands in the city of Batam. Testing of the model in this study, with Generalized Least Square Estimation (GLS), analysis of structural equation modeling (SEM), proportional random sampling method and software assistance Amos 22, on 240 respondents from eight times the 30 indicators the study variables. The test results indicate the model (fit) seen from the GFI, AGFI, TLI, CFI, RMSEA and CMIN / DF, each of 0915, 0901, 0949, 0953, 0063, and 1,376 are all that are in the range of expected values so that the model can be accepted.The results showed that: 1). Customer relationship management influence on customer value, it shows that with good customer relationship management program, will increase customer value. 2) Customer relationship management influence on purchase intention, it shows that with good customer relationship management program, will increase customer value. 3) Brand equity effect on customer value, it shows that with a good brand equity, will increase customer value. 4). Brand equity effect on purchase intention, it shows that with a good brand equity, will increase customer value. 5) Perceived quality of product effect on customer value, it indicates that the perceived quality of a good product, will increase customer value. 6). Perceived quality of product effect on purchase intention, this suggests that the perceived quality of a good product, will increase purchase intention. 7). Perceived price effect on customer value, it indicates that the perceived price friendly, will increase customer value. 8) Perceived price effect on purchase intention, this suggests that the perceived price friendly, will increase purchase intention. 9). Customer value effect on purchase intention, it shows that with high customer value, will raise the purchase intention.

Improving Customer Value Index and Consumption Forecasts using a Weighted RFM Model and Machine Learning Algorithms

2022 ◽  
Vol 30 (3) ◽  
pp. 0-0
Keyword(s):  
Customer Value ◽  
Marketing Strategies ◽  
Machine Learning Algorithms ◽  
Entropy Weight ◽  
Rfm Model ◽  
Consumption Data ◽  
Entropy Weight Method ◽  
Customer Profiling ◽  
Weight Method ◽  
Rmf Model

Collecting and mining customer consumption data are crucial to assess customer value and predict customer consumption behaviors. This paper proposes a new procedure, based on an improved Random Forest Model by: adding a new indicator, joining the RFMS-based method to a K-means algorithm with the Entropy Weight Method applied in computing the customer value index, classifying customers to different categories, and then constructing a consumption forecasting model whose RMSE is the smallest in all kinds of data mining models. The results show that identifying customers by this improved RMF model and customer value index facilitates customer profiling, and forecasting customer consumption enables the development of more precise marketing strategies.

VALUE CREATION AND CUSTOMER SATISFACTION OF QUICK SERVICE RESTAURANTS IN LAGOS STATE, NIGERIA

2021 ◽  
Vol 9 (1) ◽  
pp. 79-95
Author(s):  
Asikhia U. ◽  
◽  
Magaji N. ◽  
Fidelis N. ◽  
Adeniranye F. ◽  
...  
Keyword(s):  
Customer Satisfaction ◽  
Value Creation ◽  
Customer Value ◽  
Customer Relationship ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Validated Questionnaire ◽  
Lagos State ◽  
Eating Out ◽  
Quick Service

The Quick Service Restaurant (QSR) industry is one of the key contributors to the Nigerian economy; providing substantial revenues to government and sizable employment opportunities at the processing and retailing levels. Previous studies in Nigeria investigated customer value from the customer’s perspective but rarely has research sought to achieve both QSRs’ owners/managers and customers’ perspectives in a single study. Despite the increasing popularity of “eating out,” Quick Service Restaurants in Nigeria have shown a negative growth rate, with decline in total income, as it has become increasingly difficult to satisfy modern restaurant customers who seek unique experiences that are more than just consuming food. Hence, this study investigated the effect of value creation on customer satisfaction of Quick Service Restaurants in Lagos State, Nigeria. Cross-sectional survey research design was adopted. The population of the study was 799 owners/managers, accountants and customers of Quick Service Restaurants in Lagos State, Nigeria. A well-structured and validated questionnaire was used for data collection. Cronbach’s Alpha reliability coefficients for the constructs ranged from 0.72 to 0.92.The response rate was 75.8 percent. Data were analysed using descriptive and inferential statistics. Findings revealed that value creation dimensions had no significant effect on customer satisfaction (Adj. R2 = -0.011; F(6,296) = 0.450, p<0.05).The study concluded that value creation had no significant effect on customer satisfaction of Quick Service Restaurants in Lagos State, Nigeria. The study recommends that owners / managers of Quick Service Restaurants (QSRs) in Lagos State, Nigeria should go beyond transactional operations and develop customer relationship management programmes in order to enhance customer satisfaction.

Een typologie van jonge nieuwsgebruikers in een multimediaal landschap

2011 ◽  
Vol 39 (1) ◽  
Author(s):  
Anna Van Cauwenberge ◽  
Hans Beentjes ◽  
Leen d’Haenens
Keyword(s):  
Cluster Analysis ◽  
News Media ◽  
Television News ◽  
Online News ◽  
Low Countries ◽  
Low Level ◽  
News Consumption ◽  
Combined Use ◽  
Different Types ◽  
Online News Sites

A typology of young news users in the Low Countries A typology of young news users in the Low Countries This article investigates different types of young news users (15-34 years) in the Low Countries. Therefore a survey among 1200 Flemish and Dutch youngsters and adolescents was conducted, analyzing the combined use of media platforms for news consumption and time spent with these news carriers. The cluster analysis identified five types of news users: the sound and vision group, characterized by the use of mainly audiovisual news platforms, combined with online news sites; the e-news users, who give most prominence to online news sites but also rely on traditional news platforms, the all rounders, depending on a range of off- and online news channels; the traditionalists, who spent most time with offline news media; and the dabblers, a group with an overall low level of news consumption. Our results indicate that Flemish and Dutch youngsters combine online and traditional news platforms for their news gathering, giving most prominence to traditional news media, especially television news.

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