数字服务定价的模糊逻辑专家系统——以某移动服务提供商价格调整为例

Adeolu O. Dairo, Krisztián Szücs
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引用次数: 0

摘要

随着互联的智能设备和终端随着数字内容的不断增长,移动服务提供商的数据流量也在不断增长,移动市场的价格战正在推动流量的增长,而收入却没有相应的增长。因此,网络资本支出(CAPEX)投资、体验质量和客户体验面临巨大压力。在竞争激烈的移动市场中,只有在服务提供商拥有适当工具的情况下,战略定价才能在管理这种压力方面发挥重要作用。本文开发了一种基于模糊知识的专家定价系统,重点解决了竞争激烈的移动市场中网络流量、价格战和业务收入的挑战。它的核心在于能够在竞争激烈的移动环境中推荐与数字和数据服务相关的价格点。拟议的定价系统是在一个新兴市场的移动服务提供商的一小部分客户基础上通过试点进行的实验性评估,后来扩大到更广泛的基础。实施后,随着数据流量的减少,数据服务收入增加,总体毛利率增加,从而提高了吞吐量和网络质量,从而提高了净推荐值,从而改善了客户体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fuzzy Logic Expert System for Pricing Digital Services: The Case of Price Adjustment for a Mobile Service Provider
As connected smart devices and terminals continue to grow along with digital content, data traffic of mobile service providers is also growing, and the price war in mobile markets is driving traffic growth without a commensurable increase in revenue. As a result, network capital expenditure (CAPEX) investment, quality of experience, and customer experience are under enormous pressure. In a competitive mobile market, strategic pricing may play an essential role in managing this pressure only if appropriate tools are available for the service providers. In this paper, a fuzzy knowledge-based expert pricing system was developed with a focus on solving network traffic, price war, and business revenue challenges in a competitive mobile market. Its core lay in its ability to recommend digital- and data services-related price points within a competitive and price war mobile environment. The proposed pricing system was experimentally evaluated through a pilot conducted on a few segments of a mobile service provider’s customer base in an emerging market and later scaled up to a broader base. Upon implementation, data services revenue increased, and overall gross margin increased with a reduction in data traffic, resulting in better throughput and network quality and, consequently, better customer experience with improved net promoter score.
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