Customer Relationship Management

Assignment Sample on CSI-7-DMA Customer Relationship Management

Introduction

The significance of customer relationship management helps in implementing relationships with customers by arranging customer segmentation and satisfaction rate. The purpose of this study is to analyse business problems with respect to customer relationship management while incorporating big data analytics programs. This study explores strategic management and data mining approaches with respect to customer relationship management.

Identified business problems

The article “Big Data-enabled Customer Relationship Management: A holistic approach” explains about the critical success factors with respect to CRM and big data programs. Authors of this article are Pierluigi Zerbino, Davide Aloini, Riccardo Dulmin and Valeria Mininno who belong from University of Pisa (Zerbino et al. 2018). Authors have presented their views on ad-hoc classification framework through which big data enabled programs related to CRM can be maintained properly. From this article, it has been identified that due to clustering and classification technique issues in the CRM process can decrease efficiency in the big data environment due to which behavioural data sources of specific activities cannot be executed properly. Due to this issue, service providers cannot understand specific requirements of performance management and also fail to understand actual expectations of customers. Therefore, satisfaction and engagement rate of customers cannot be maintained properly. It can slow the process of sustainable development within an organisation in terms of big data operations.

Due to clustering and classification technique issues in the CRM process, service providers have failed to maintain macro environmental factors properly. According to Zerbino et al. (2018), due to this issue, service operators cannot engage creative ideas within business operations that can slow the process of development. It can also decrease data validation and also decrease the sequence in data processing operations that can decrease the efficiency in sustainable development within organisations while using big data. Moreover, this issue can also decrease the motivation factors for employees to give their effective performance to meet all expectations of customers.

Explaining data mining methodology

Data mining methodology helps in identifying specific tools and techniques to gather specific data and requirements through which quality enhancement can be maintained properly. For this article, a theoretical or secondary data collection method has been used to gather required information related to journals of CRM processes. As influenced by Zerbino et al. (2018), through this data collection method, data mining and data processing operations can be executed properly that can improve the sequential results while conducting this study. Through a sequence structure of data mining methodology, specific information related classification, literature review; content and critical analysis can be maintained successfully. Through this information, positive and negative aspects of data collection and content analysis can be acknowledged properly. Clustering and classification technique issues can allow organisations to develop the structure of CRM processes through which customer segmentation and customer expectations can be arranged properly. It can decrease issues due to which sequence in data validation can be maintained properly. Through this procedure, data adequacy and data relevancy can be developed according to the expectations without any challenges through this article.

Discussing data pre-processing

Data processing plays a crucial role in arranging data sequence through which clarity and validation operations can be organised properly. According to this article, CRM processes and CRM approaches can allow in understanding requirements and other specifications of customers. Using big data applications, issues regarding CRM processes can be identified properly due to which service providers can make sustainable decisions in developing CRM processes. It can improve the sequence of data validation through which clustering and classification related issues can be identified properly. Hence, service providers can develop their performance management with respect to the situation to avoid this issue and develop a sustainable environment regarding CRM activities. As opined by Zerbino et al. (2018), using big data applications, CRM activities would be organised properly that can maintain the quality in data segmentation through which sustainable criteria can be organised through which specific requirements and other CRM processes can be maintained properly. On the other hand, through effective CRM processes, maintenance and building activities can be organised due to which sequence in strategic, technological and capability operations can be modified as per requirements. In this way, complications in sustainable factors can be maintained properly due to which cross functional activities can be arranged successfully.

Summary of results

From this article, it has been identified that service providers of organisations can incorporate strategic perspectives and incorporate technological advancement processes to maintain the fundamental inputs. It can allow in arranging sub processes of CRM activities through which customer relationships can be arranged properly that can decrease validation processes through which classification framework can be developed without any issues. As followed by Zerbino et al. (2018), theoretical foundation of CRM processes can allow in creating a sustainable feature through which issues with CRM activities can be avoided within organisations. It can decrease issues with CRM processes through which sequential results can be maintained through which different touch points of CRM operations can be maintained properly. In this way, sequential outcomes can be maintained properly that can slow the process of development. Therefore, the managing director of an organisation is expected to make appropriate choices in critical success factors through which development in CRM processes can be maintained adequately. Through this procedure, evaluation and monitoring activities can be synchronised through which issues with CRM processes can be avoided properly.

Evaluation of main approaches

Strategic planning helps in creating CRM strategies through which infrastructure of data management operations related to customers can be maintained properly. Using information technology and big data, service providers can store adequate information in a structured manner to maintain customer data management processes. As proposed by Zerbino et al. (2018), through the usage of change management processes, service providers can introduce creative ideas within their business to develop employability skills. Therefore, complexities in CRM processes can be avoided due to which sequential results can be maintained that can also improve resource management processes. Customer data management and knowledge management processes can be developed through functional processes that would be modified according to expectations.

Conclusion

From the above study, it has been understood that CRM processes can allow in implementing a sustainable environment through which sequential results can be gathered according to requirements. It can help in analysing issues with CRM processes through which service providers can make appropriate decisions in incorporating strategies to deal with any challenges regarding CRM.

Bibliography

Anshari, M., Almunawar, M.N., Lim, S.A. and Al-Mudimigh, A., (2019). Customer relationship management and big data enabled: Personalization & customization of services. Applied Computing and Informatics, 15(2), pp.94-101.

Demo, G., Watanabe, E.A.D.M., Chauvet, D.C.V. and Rozzett, K., (2017). Customer relationship management scale for the B2C market: A cross-cultural comparison. RAM. Revista de Administração Mackenzie, 18(3), pp.42-69.

Dewnarain, S., Ramkissoon, H. and Mavondo, F., (2019). Social customer relationship management: An integrated conceptual framework. Journal of Hospitality Marketing & Management, 28(2), pp.172-188.

Guha, S., Harrigan, P. and Soutar, G., (2018). Linking social media to customer relationship management (CRM): A qualitative study on SMEs. Journal of Small Business & Entrepreneurship, 30(3), pp.193-214.

Sánchez-Gutiérrez, J., Cabanelas, P., Lampón, J.F. and González-Alvarado, T.E., (2019). The impact on competitiveness of customer value creation through relationship capabilities and marketing innovation. Journal of Business & Industrial Marketing.

Zerbino, P., Aloini, D., Dulmin, R. and Mininno, V., (2018). Big Data-enabled customer relationship management: A holistic approach. Information Processing & Management, 54(5), pp.818-846.

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