The value of data-driven Customer Value Management or CVM cannot be underrated. Data and other algorithms/analytics that shape data are an imperative part of customer value management in a telecom company. With enhanced customer expectations, it is up to the ability of telecom companies to provide customers with a seamless experience and to also ensure that they help boost revenue in the process.
Mobile Social Networking Services (SNS) are an emerging trend in which individuals of similar interests communicate with one another using mobile phones. In this paper, we calculate the monetary value of customers and their networks in mobile SNS using the official data provided by a service provider. The mobile SNS enable users to create their avatars to communicate with each other via blog comments and communities. The company sells various items for these avatars such as apparel and interiors. This service generates consumer purchase history data and user network data. In previous research, the value of the customer is often estimated using the purchase history, but the network value is neglected. In the field of computer science, the value of the network is evaluated via the network structure, but not much attention is paid to the economic aspect of each node. The aim of this paper is to incorporate the social factor with the customer purchase database and calculate the monetary value of each customer and his or her network. The results of empirical analysis show that our approach is useful in finding valuable customers for marketing activities and outperforms conventional metrics such as degree centrality.
Much has been written about customer churn - predicting who, when, and why customers will stop buying, and how (or whether) to intervene. Employee churn is similar - we want to predict who, when, and why employees will terminate. In many ways, it is smarter to to focus inward on employees. For one thing, it is far easier for an company to change the operations or even the behavior of an employee, than that of a customer. As will be seen, employee churn can be massively expensive, and incremental improvements will give big results.
According to the research firm Gartner, the global value derived from AI will mark a 70% increase from 2017 which is expected to be $ 1.2 trillion this year and expected to surge up-to $3.9 trillion by 2022. One of the biggest combined sources for AI-enhanced products and services obtained by organizations from 2017 to 2022 will métier solutions that will tend to needs very well. These needs might include techniques to make customer experiences better, ways to drive new revenue streams and methods to cut costs, which can be operational or serving existing products. Companies like Google, IBM, Microsoft, Apple and Nvidia are laboriously researching to develop AI-based products and services. Start-ups from around the world are also budding up to pursue Artificial intelligence in sectors like automobiles, commerce, sales, marketing and customer relationship management.