Identifying customers can be difficult for any company, as customers may sometimes be willing or able to provide direct contact information or engage in conversation with representatives. However, companies need to be able to identify customers to establish trust and create meaningful relationships with them. It is especially true in certain industries, such as retail, banking, and healthcare, which have unique challenges in identifying customers. In this essay, we will explore the difficulties associated with identifying customers in the retail, banking, and healthcare industries and the methods that companies in each sector use to identify their customers.
Identifying customers in the retail industry can be difficult because shoppers often need to interact with store personnel directly. To identify customers, retailers must rely on other methods, such as loyalty programs, customer surveys, and data analysis (Zhang et al., 2021). The retail industry is a great example of an industry where customers talk to representatives infrequently. Retailers must rely on data and analytics to identify customers. It includes tracking customer purchases and preferences in order to build a better understanding of their customer base. Technology such as loyalty programs and RFID tracking to track customer activity and help retailers better target their marketing and promotions (Zhang et al., 2021). Additionally, retailers can use social media to gain insights into customer behavior and engage and interact with customers.
Identifying customers in the banking industry can be difficult because customers often need to interact with bank personnel directly. The banking industry also has its unique challenges when it comes to identifying customers. Banks must take additional steps to ensure the safety and security of their customers’ data. One way that banks can identify customers is through account numbers (Biesialska et al., 2021). Account numbers allow the company to track customer transactions and provide customer service and technical support. Therefore, the account numbers can track customer information and all the important elements required in a systematic and logical (Zhang et al., 2021). In addition to the traditional methods of identifying customers, such as verifying identity documents, banks must also use more advanced technologies, such as biometric and two-factor authentication. Banks must also use sophisticated data analytics to detect fraudulent activity and protect their customers’ data.
Identifying customers in the healthcare industry can be difficult because patients often need to interact with healthcare providers directly. One way that healthcare providers can identify patients is through patient identification numbers. Patient identification numbers allow the company to track patient information and provide medical history and test results (Majd et al., 2021). Additionally, patient identification numbers can track patient preferences and behaviors, which can be used to tailor healthcare plans and treatments to individual patients. Healthcare providers must ensure that they are dealing with the right patient in order to ensure the accuracy of their medical records and to protect patient privacy (Biesialska et al., 2021). Healthcare providers must use a combination of methods to identify patients, such as visual identification, biometric authentication, and electronic patient record systems. Additionally, healthcare providers must use data analytics and machine learning to ensure that patient data is secure and to detect any fraudulent activity.
In conclusion, each industry has its own unique challenges when it comes to identifying customers. Retailers must rely on data and analytics to identify customers, banks must use sophisticated data analytics and biometric authentication. Healthcare providers must use a combination of methods to identify patients and ensure the accuracy of their medical records. By understanding the difficulties associated with each industry, companies can develop better strategies for identifying their customers and protecting their data. As a result it contributes to the positive feedback in the technological setting.
References
Zhang, Y., Zhang, M., Li, J., Liu, G., Yang, M. M., & Liu, S. (2021). A bibliometric review of a decade of research: Big data in business research–setting a research agenda. Journal of Business Research, 131, 374-390. https://doi.org/10.1016/j.jbusres.2020.11.004
Majd, Z., Mohan, A., Paranjpe, R., & Abughosh, S. M. (2021). Identifying adherent patients to newly initiated statins using previous adherence to chronic medications. Journal of Managed Care & Specialty Pharmacy, 27(2), 186-197.
Biesialska, K., Franch, X., & Muntés-Mulero, V. (2021). Big Data analytics in Agile software development: A systematic mapping study. Information and Software Technology, 132, 106448. https://doi.org/10.1016/j.infsof.2020.106448
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