CSR Practices in State Bank of India and its Impact on Creating Loyal Customers: A Study

2020 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Sowmya Hegde
Keyword(s):  
Loyal Customers

Enabling Customer-Centricity and Relationship Management using Net Promoter Score

2018 ◽  
Vol 9 (2) ◽  
pp. 115-126 ◽  
Author(s):  
Nicoleta Valentina Florea ◽  
Dorina Antoneta Tănăsescu ◽  
Anişoara Duică
Keyword(s):  
Relationship Marketing ◽  
Performance Indicators ◽  
Simulation Modeling ◽  
Customer Value ◽  
Future Trends ◽  
New Methods ◽  
Net Promoter Score ◽  
Net Promoter ◽  
Customer Centricity ◽  
Loyal Customers

Abstract We are in the fifth era of marketing development, that of relationship marketing, where the environment is influenced by globalization, informatization, market liberalization, and the overcapacity of production, and the focus will be not on increasing the volume of production, but on obtaining profit using relationship with profitable customers. Customer-centricity, customization, one-to-one relationship and measuring the value of each customer is an advantage in the fearless market. Organizations if they knew what customers wants would offering only those products or services they want, but to help them to know the customers’ needs better, they use models, new methods and calculation of performance indicators. One of the models which help organizations to determine the customer value and centricity is Net Promoter Score (NPS), its formula being developed by Reichheld F. in 2006. Our research is made on 10 organizations and on 150 respondents and is consisting in using NPS in order to observe customers’ perception of the analysed brands, to measure how well the brand is having satisfayed and loyal customers, and the desire for recommendation of the analysed brand. Our article is using simulation, modeling and IT programs to observe possible relationships and future trends.

Pengaruh Kepercayaan Terhadap Loyalitas Konsumen Yang Memunculkan Distrust

2019 ◽  
Vol 3 (2) ◽  
pp. 100-112
Author(s):  
Septian Wahyudi
Keyword(s):  
Research Method ◽  
Negative Impact ◽  
Consumer Confidence ◽  
Consumer Loyalty ◽  
The One ◽  
Loyal Customers

The company certainly wants to increase its sales and increase the number of its customers so that all efforts and methods are carried out, including in building consumer confidence, thus making these consumers become loyal customers or commonly referred to as customers. But on the one hand the trust built by the company actually has a negative impact, namely the emergence of distrust because the frequency of the company offers a variety of products that are sometimes not needed by consumers, this paper is made to answer these phenomena and problems in a concise manner.This research method is by analyzing criticism of several studies about trust that affect consumer loyalty which results in the absence of influence between trust in consumer loyalty.

THE MANIFESTATIONS OF CUSTOMER LOYALTY IN INDIAN LIFE INSURANCE INDUSTRY: AN EMPIRICAL EXAMINATION

2016 ◽  
Vol 12 (02) ◽  
Author(s):  
Medha Srivastava ◽  
Alok Kumar Rai
Keyword(s):  
Customer Loyalty ◽  
Life Insurance ◽  
Recent Literature ◽  
Insurance Industry ◽  
Empirical Examination ◽  
Consumption Decisions ◽  
Life Insurance Industry ◽  
Product Service ◽  
Brand Attributes ◽  
Loyal Customers

The widespread reverence for customer loyalty among marketers and businesses all across the globe is inspired from its manifestations since it’s the consumption decisions of loyal customers that leave a mammoth mark over the revenues and growth of a firm. A throng of behavioural, attitudinal and cognitive manifestations of customer loyalty are available in the literature some of which are widely acknowledged and accepted whereas others call for further inquiry. These manifestations of loyalty among customers are generally pinned down through their actions (Zeithaml et al., 1996; Jones et al., 2000) or their attitude towards the company or a particular product/ service (Javalgi and Moberg, 1997; Butcher et al., 2001). However, recent literature suggests that another outcome of loyalty is customer preferring a particular service provider to others based upon the conscious evaluation of brand attributes (Gremler and Brown, 1996; Butcher et al., 2001). The paper intends to explore and empirically test various manifestations of customer loyalty in the context of life insurance services thereby, extending the existing knowledge of customer loyalty by outlining the distinctive nature of customer loyalty outcomes and offering useful insights to the marketing practitioners in life insurance industry. The study further groups these manifestations into distinct outcome classes and empirically evaluates them by comparing and contrasting each with the other. It also aims to enrich the literature of customer loyalty by developing and validating a scale for measurement of customer loyalty outcomes with special reference to life insurance services.

The Impact of Customer Loyalty and Restaurant Sanitation Grades on Revisit Intention and the Importance of Narrative Information: The Case of New York Restaurant Sanitation Grading System

2017 ◽  
Vol 59 (3) ◽  
pp. 275-284 ◽  
Author(s):  
Min Gyung Kim ◽  
Hyunjoo Yang ◽  
Anna S. Mattila
Keyword(s):  
New York ◽  
New York City ◽  
Customer Loyalty ◽  
York City ◽  
Letter Grades ◽  
The Difference ◽  
Revisit Intentions ◽  
Using Data ◽  
The Impact ◽  
Loyal Customers

New York City launched a restaurant sanitation letter grade system in 2010. We evaluate the impact of customer loyalty on restaurant revisit intentions after exposure to a sanitation grade alone, and after exposure to a sanitation grade plus narrative information about sanitation violations (e.g., presence of rats). We use a 2 (loyalty: high or low) × 4 (sanitation grade: A, B, C, or pending) between-subjects full factorial design to test the hypotheses using data from 547 participants recruited from Amazon MTurk who reside in the New York City area. Our study yields three findings. First, loyal customers exhibit higher intentions to revisit restaurants than non-loyal customers, regardless of sanitation letter grades. Second, the difference in revisit intentions between loyal and non-loyal customers is higher when sanitation grades are poorer. Finally, loyal customers are less sensitive to narrative information about sanitation violations.

Are Repeat Buyers in Cryptomarkets Loyal Customers? Repeat Business Between Dyads of Cryptomarket Vendors and Users

2017 ◽  
Vol 61 (11) ◽  
pp. 1341-1357 ◽  
Author(s):  
David Décary-Hétu ◽  
Olivier Quessy-Doré
Keyword(s):  
Technological Innovation ◽  
Limited Size ◽  
Customer Base ◽  
Internet Markets ◽  
Loyal Customer ◽  
Loyal Customers ◽  
Over Time

Organizations involved in the sale of illicit products and services have been described as small, ephemeral, and local rather than global. Given their limited size, such organizations are often unable to attract large pools of customers, but it has been noted that organizations that manage to build a small but loyal customer base are likely to be more secure and to incur fewer risks of arrest and victimization. There has been little previous research into the loyalty of repeat buyers on Internet markets but a new technological innovation, cryptomarkets, makes it now more possible to track transactions between vendors and their customers. This article looks at the level of loyalty of cryptomarket repeat buyers by tracking their purchases over time. We find that, on average, customers make 60% of their purchases from the same vendor and that providing increased amounts of information to customers increases the loyalty of cryptomarket vendors’ customer base.

scholarly journals Applying FCM to predict the behaviour of loyal customers in the mobile telecommunications industry

2018 ◽  
Vol 28 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Ioannis Rizomyliotis ◽  
Athanasios Poulis ◽  
Giovanis Apostolos ◽  
Kleopatra Konstantoulaki ◽  
Ioannis Kostopoulos
Keyword(s):  
Telecommunications Industry ◽  
Mobile Telecommunications ◽  
Mobile Telecommunications Industry ◽  
Loyal Customers

A review of value drivers in service settings

2018 ◽  
Vol 32 (7) ◽  
pp. 850-867 ◽  
Author(s):  
Maria-Eugenia Ruiz-Molina ◽  
Martina Gallarza ◽  
Irene Gil-Saura
Keyword(s):  
Product Quality ◽  
Customer Loyalty ◽  
Perceived Value ◽  
Value Drivers ◽  
Content Type ◽  
Value Perceptions ◽  
Segmentation Approach ◽  
Emotional Value ◽  
Home Furnishing ◽  
Loyal Customers

Purpose Perceived value and customer loyalty have been studied jointly in most of services literature but mainly through SEM models. This paper aims to draw on the literature on the multidimensional richness of perceived value, to adopt a segmentation approach and explore segments of loyal consumers towards the service provider based on their value perceptions. Design/methodology/approach A survey was conducted among 460 Spanish consumers interviewed at the store exit of seven retail chains in two sectors (grocery and home furnishing). A CHAID analysis was performed on loyalty responses, through nine value dimensions (efficiency, service quality, product quality, emotional value, value for money, social value, aesthetic value, escapism and ethics). Findings Results show the existence of different groups of loyal customers based on the nine value types. Efficiency is prioritised by the most loyal customers in grocery but not for home furnishing. Emotional value and aesthetics, along with product quality determine the most loyal segments. Practical implications Retailers should focus on enhancing those value dimensions that better explain customer loyalty towards retail stores in their area of specialisation, combining not only tangible and intangible elements but also functional and emotional elements. Originality/value The paper adds to the prolific research on perceived value in services with a diachronic graphical review of value dimensions in retailing; furthermore, the range of value dimensions studied here is wider than most of previous works using dimensions of value in services.

scholarly journals Modern Market Customer Loyalty: Advertising Promotion Strategies

2019 ◽  
Vol 10 (2) ◽  
pp. 111
Author(s):  
Apri Budianto ◽  
Irma Damayanti Bastaman ◽  
Aulia Fauziyah
Keyword(s):  
Customer Loyalty ◽  
Customer Relationship ◽  
Analysis Tool ◽  
Promotion Strategy ◽  
Retail Business ◽  
Promotion Strategies ◽  
The Relationship ◽  
Simple Regression ◽  
Loyal Customers

This study is focused on the relationship between advertising promotion strategies and customer loyalty in the modern market. This study seeks to explain the advertising promotion strategy if successfully carried out by the modern market, with the hope of creating loyal customers. This research was conducted on modern market customers in Ciamis. Ciamis is one of the regions in Indonesia, which is the same as other regions there are several modern markets with a variety of character of its customers. The study is based on the statements of several experts, which explain the customer relationship with various retail business promotion strategies. The model used in this study as an analysis tool is simple regression to illustrate how the relationship between advertising promotion strategies and customer loyalty. The results obtained are that there is an influence of advertising promotion strategies on customer loyalty, with the magnitude of influence is 27.5%, while as many as 22.5% are influenced by other factors not examined in this study

scholarly journals Consumers Loyalty Indicator as a Drivers for Satisfaction

2020 ◽  
Vol 4 (1) ◽  
pp. 41-45
Author(s):  
Aram Hanna Massoudi
Keyword(s):  
Social Science ◽  
Market Share ◽  
Perceived Value ◽  
City Centre ◽  
Leading Indicators ◽  
Shopping Malls ◽  
Essential Factor ◽  
Descriptive Approach ◽  
Loyal Customers

This study focuses on understanding the leading indicators of loyalty among food and nourishments shoppers in two Syrian Malls, Cham City Centre and Massa Plaza, both located in Damascus, the capital of Syria. The research uses descriptive approach; the data were collected from a questionnaire distributed to 110 shoppers in the two shopping malls, 100 valid responses divided (50 answers from Cham City Centre, and 50 from Massa Plaza Mall). The data were analyzed using Statistical Package for Social Science to test the hypothesis. The result showed that shopper attitudes toward the store positively related to his fulfilment and loyalty. Also, shoppers call to the store is an indicator of his satisfaction and commitment towards the store. Finally, perceived value is positively related to the four loyalty indicators. The novelty of this article comes from the analysis of the four loyalty indicators as an essential factor for the sustainable customer. Loyal customers are free marketing tools that keep business running and can increase market share.

scholarly journals Introducing A Hybrid Data Mining Model to Evaluate Customer Loyalty

2016 ◽  
Vol 6 (6) ◽  
pp. 1235-1240
Author(s):  
H. Alizadeh ◽  
B. Minaei Bidgoli
Keyword(s):  
Customer Loyalty ◽  
Accurate Method ◽  
Support Vector ◽  
Similar Data ◽  
Classification Methods ◽  
Clustering Methods ◽  
K Nearest Neighbors ◽  
Step Model ◽  
Customer Classification ◽  
Loyal Customers

The main aim of this study was introducing a comprehensive model of bank customers᾽ loyalty evaluation based on the assessment and comparison of different clustering methods᾽ performance. This study also pursues the following specific objectives: a) using different clustering methods and comparing them for customer classification, b) finding the effective variables in determining the customer loyalty, and c) using different collective classification methods to increase the modeling accuracy and comparing the results with the basic methods. Since loyal customers generate more profit, this study aims at introducing a two-step model for classification of customers and their loyalty. For this purpose, various methods of clustering such as K-medoids, X-means and K-means were used, the last of which outperformed the other two through comparing with Davis-Bouldin index. Customers were clustered by using K-means and members of these four clusters were analyzed and labeled. Then, a predictive model was run based on demographic variables of customers using various classification methods such as DT (Decision Tree), ANN (Artificial Neural Networks), NB (Naive Bayes), KNN (K-Nearest Neighbors) and SVM (Support Vector Machine), as well as their bagging and boosting to predict the class of loyal customers. The results showed that the bagging-ANN was the most accurate method in predicting loyal customers. This two-stage model can be used in banks and financial institutions with similar data to identify the type of future customers.

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