A process of communicating information amongst employees inside and outside a corporation is known as business communications. Effective business communication relates to how employees and management interact with one another to attain business goals and adhere to core company values. Its main aim is to improve company functions, break down silos, keep people informed, and correct errors (Ritter and Pedersen, 2020; Chang et al., 2018). Effective corporate communication is critical to the success and growth of any organization. Unlike everyday communication, business communication is frequently goal-oriented. It helps to keep old customers and attract new ones when it is done successfully.
It may appear that being able to concentrate on the most important consumers would be advantageous. Furthermore, many smaller businesses value all of their customers. However, every business learns that certain customers are more valuable than others. This could be attributable to a number of reasons, such as the size of their transactions and the relative ease with which they can manage their account. (Kim et al., 2020; Ballestar et al., 2019). Businesses that recognize these clients, build relationships with them, and try to bring in new customers with similar profiles are often successful (Hoyer et al., 2020; Chang et al., 2018). Knowing the clients will help the company sell more. The more one knows about them and their demands, the easier it will be to spot chance to sell them new products and tailor offers to them.
Customer retention marketing is critical to a company’s success and growth. It focuses on clients who have already established a relationship with an organization, reminding them of products and services and why they trust an organization (Cong et al., 2021). Because loyal consumers are more likely to make a purchase, a good marketing effort aimed at maintaining consumers is frequently less expensive than one aimed at attracting new customers. This could save the company’s money that can put back into the business to develop products and services or streamline procedures. Due to the differences in objectives, client retention marketing initiatives frequently require smaller costs than customer acquisition marketing campaigns (Tseng et al., 2022; Libai et al., 2020). Marketing to new clients entails introducing a product, raising brand awareness, and demonstrating the utility of an organization’s product.
Customers who are already familiar with a business’ items can design simpler customer retention marketing strategies. A business can either choose a campaign based on its resources or adjust its budget to fulfill marketing objectives (Ritter and Pedersen, 2020). A company can find context, sentiment, and behavior, as well as intent, by analyzing consumer interactions. With such attributes, the organization may perform root cause analysis and predictive modeling, as well as identify event triggers and provide reports on key indicators (Nilashi et al., 2021; Li et al., 2020). Numbers that can be counted and measured are applied to describe qualitative data. Tables and graphs are frequently used to convey it visually. As a result, while analyzing this data can help business owners make better decisions, it rarely provides insight into how to remedy an issue.
Customer analytics, which is known as customer data analysis, is the act of gathering and analyzing data from customers in order to get insights into their behavior (Provost and Fawcett, 2013). It necessitates a variety of technologies for gathering and organizing various sorts of data, as well as a methodological framework for evaluating and comprehending that data (Ghazzawi and Alharbi, 2019). Companies utilize analytics to make marketing, product development, and sales choices, among other things. Customer analytics may help business owners to make easy business decisions, including determining which advertising platform provides the highest return on investment. They may be difficult commercial decisions, such as determining the complete client experience and creating customised marketing efforts to fit.
Reference List
Ballestar, M. T., Grau-Carles, P., & Sainz, J. (2019) ‘Predicting customer quality in e-commerce social networks: a machine learning approach.’ Review of Managerial Science, 13(3), pp. 589-603.
Chang, Y., Wang, X., & Arnett, D. B. (2018) ‘Enhancing firm performance: The role of brand orientation in business-to-business marketing.’ Industrial Marketing Management, 72, pp. 17-25. Web.
Cong, P., Zhang, Z., Zhou, J., Liu, X., Liu, Y., & Wei, T. (2021) ‘Customer Adaptive Resource Provisioning for Long-Term Cloud Profit Maximization under Constrained Budget.’ IEEE Transactions on Parallel and Distributed Systems, 33(6), 1373-1392.
Ghazzawi, A., & Alharbi, B. (2019) ‘Analysis of customer complaints data using data mining techniques.’ Procedia Computer Science, 163, pp. 62-69. Web.
Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020) ‘Transforming the customer experience through new technologies.’ Journal of Interactive Marketing, 51, 57-71.
Kim, W., Kim, H., & Hwang, J. (2020) ‘Sustainable growth for the self-employed in the retail industry based on customer equity, customer satisfaction, and loyalty.’ Journal of Retailing and Consumer Services, 53, 101963. Web.
Li, H., Liu, Y., Tan, C. W., & Hu, F. (2020) ‘Comprehending customer satisfaction with hotels: Data analysis of consumer-generated reviews.’ International Journal of Contemporary Hospitality Management.
Libai, B., Bart, Y., Gensler, S., Hofacker, C. F., Kaplan, A., Kötterheinrich, K., & Kroll, E. B. (2020) ‘Brave new world? On AI and the management of customer relationships.’ Journal of Interactive Marketing, 51, 44-56.
Nilashi, M., Minaei-Bidgoli, B., Alrizq, M., Alghamdi, A., Alsulami, A. A., Samad, S., & Mohd, S. (2021) ‘An analytical approach for big social data analysis for customer decision-making in eco-friendly hotels.’ Expert Systems with Applications, 186, 115722.
Provost, F. & Fawcett, T. (2013) Data Sciences for Business: What you need to know about Data Mining and Data-Analytics Thinking, 1st edition, O’Reilly Media, Sebastopol, CA.
Ritter, T., & Pedersen, C. L. (2020) ‘Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future.’ Industrial Marketing Management, 86, 180-190. Web.
Tseng, H. T., Aghaali, N., & Hajli, N. (2022) ‘Customer agility and big data analytics in new product context.’Technological Forecasting and Social Change, 180, 121690. Web.