scholarly journals A Frame Work for Customer Relationship Management in Nigerian Banks Using Data Analytics

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Olatayo M Olaniyan ◽  
Emeka Ojukwu ◽  
Cyril Ogude
Keyword(s):  
Customer Satisfaction ◽  
Customer Relationship Management ◽  
Management System ◽  
Data Analytics ◽  
Empirical Test ◽  
Big Data Analytics ◽  
Relationship Management ◽  
Customer Relationship ◽  
New Strategy ◽  
Using Data

One of the most crucial challenges that Nigeria banks have to face is in the jurisdiction of customers’ satisfaction. Customers’ satisfaction has become one of the most important factors of success in today’s banking industry in Nigeria. Today Nigeria banks customer’s increases every day, as it is essential for many Nigerian to have proper savings with any bank of their choice; if the performance of bank falls short of their expectations, the very survival of such bank would be difficult. In this paper, a   framework for customer relationship management for Nigeria banks using big data analytics approach was developed. Qualitative research was used to identify customer satisfaction through customer management system information publish annually.  The data were collected from complaint data for financial report 2017 from the Customer Relationship Management System for WEMA Bank Plc. The data were analyzed using excel spread sheet and later converted into CSV and ARFF file format respectively. Data were  exported into WEKA for data analytics which then generated results. The formulated hypotheses are subjected to empirical test using Logistic regression and Machine learning. This new strategy provided solution of these problems identified. Keywords: Data Analytics, Linear regression, Banking,  Customer Satisfaction

Data analytics dilemma at Alpen Hotel

2019 ◽  
Vol 9 (2) ◽  
pp. 58-63
Author(s):  
Tammy Wee ◽  
Arif Perdana ◽  
Detlev Remy
Keyword(s):  
Customer Relationship Management ◽  
Data Analytics ◽  
Data Privacy ◽  
Hospitality Industry ◽  
Service Providers ◽  
Relationship Management ◽  
Customer Relationship ◽  
Using Data ◽  
Privacy And Confidentiality

Data analytics is currently the buzzword for the hospitality industry to stay ahead of their competitors. Service providers use data analytics to ensure their brand remains relevant for customers. Using data analytics in customer relationship management is a relatively novel initiative for the hospitality industry to enhance the efforts of customer relationship management. Obtaining customers’ data (i.e. customers’ hotel stay and preferences) provides both opportunity and challenges for the hospitality industry. Data analytics helps the hospitality industry to quickly, effectively, and efficiently pursue data-driven decision-making. At the same time, acquiring relevant customers’ data is a challenge, for example, data privacy and confidentiality. This case study is based on Alpen Hotel (pseudonym), a luxury hotel in Singapore with a good standing in the hospitality industry. This case is focused on the issues they experienced in implementing data analytics as part of the hotel’s customer relationship management efforts. This case study aims to highlight data analytics dilemma at the hotel and may create an opportunity for hospitality educators to work interdisciplinary with faculties from an information systems or technology discipline. Finally, the case study may enhance knowledge and minimise the practice gap between industry and academia.

scholarly journals Investigating the Impact of Big Data Analytics on Perceived Sales Performance: The Mediating Role of Customer Relationship Management Capabilities

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Muhammad Shahbaz ◽  
Changyuan Gao ◽  
Lili Zhai ◽  
Fakhar Shahzad ◽  
Adnan Abbas ◽  
...  
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Data Analytics ◽  
Dynamic Capabilities ◽  
Big Data Analytics ◽  
Relationship Management ◽  
Sales Performance ◽  
Customer Relationship ◽  
Research Model ◽  
The Impact

A persistent question for information technology researchers and practitioners is how big data analytics (BDA) can improve sales performance. Therefore, this study proposed a research model to investigate the impact of BDA on perceived sales performance in accordance with the resource-based view (RBV) and dynamic capability theory. The 416 valid responses collected from the employees of pharmaceutical organizations were analyzed using structural equation modelling to test the proposed research model. Results indicated that the BDA and customer relationship management (CRM) capabilities shared a strong positive impact on perceived sales performance. BDA, as organizational resources, creates organizational dynamic capabilities, such as CRM capabilities. BDA and CRM capabilities can influence perceived sales performance. Furthermore, CRM capabilities have a significant mediating impact on the relationships between BDA and perceived sales performance. This study also highlighted the practical and theoretical implications of the proposed model, the research limitations, and the future research directions.

scholarly journals Impact of big data analytics on sales performance in pharmaceutical organizations: The role of customer relationship management capabilities

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250229
Author(s):  
Muhammad Shahbaz ◽  
Changyuan Gao ◽  
Lili Zhai ◽  
Fakhar Shahzad ◽  
Adeel Luqman ◽  
...  
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Relationship Management ◽  
Sales Performance ◽  
Customer Relationship ◽  
Equation Modeling ◽  
Automation System ◽  
The Impact

In this era of technology development, every business wants to equip its salesforce with a sustainable salesforce automation system to improve sales performance and customer relationship management (CRM) capabilities. This study investigates the impact of big data analytics (BDA) on CRM capabilities and the sales performance of pharmaceutical organizations. A research model was tested based on 416 valid responses collected from pharmaceutical companies through a structured questionnaire. Structural equation modeling (SEM) was employed using Smart-PLS3 to confirm the contribution of BDA to improving CRM capabilities and sales performance. The study finds that individual characteristics such as self-efficacy, playfulness, and social norms, along with organizational characteristics such as voluntariness, user involvement, user participation, and management support, are positive predictors of salesforce perception of BDA. This positive perception of BDA increased the person-technology fit in the salesforce, which ultimately increased the CRM capabilities and sales performance.

Reducing Adverse Selection through Customer Relationship Management

2005 ◽  
Vol 69 (4) ◽  
pp. 219-229 ◽  
Author(s):  
Yong Cao ◽  
Thomas S. Gruca
Keyword(s):  
Adverse Selection ◽  
Customer Relationship Management ◽  
Management System ◽  
Relationship Management ◽  
Customer Relationship ◽  
Customer Acquisition ◽  
Lifetime Value ◽  
Using Data ◽  
Number Of Customers

Adverse selection is an important problem for marketers. To reduce the chances of acquiring an unprofitable customer, companies may screen prospects who respond to a marketing offer. Prospects who respond are often not approved. At the same time, prospects who are likely to be approved are unlikely to respond to a given marketing offer. Using data from a firm's customer relationship management system, the authors show how to target prospects who are likely to respond and be approved. This approach increases the number of customers who are approved and reduces the number of applicants who may defect after being turned down. This method can be extended to new customer acquisition and more effective targeting of costly promotions to migrate customers to higher levels of lifetime value.

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