方法论:“销售和服务系统中问题和成长领域的识别:非模仿方法的优势”

IF 2.2 3区 工程技术 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
O. Gurov
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引用次数: 0

摘要

作者提出了他们的方法,销售和服务系统分析的组织与分支网络。该方法已于2023年成功测试,并证明是相关的。尽管数字化转型,特别是影响销售渠道的发展和向数字化的转变,分支网络继续在业务中发挥重要作用。经典的销售渠道和分支网络解决了众多问题。销售和服务模式的成功取决于几个因素,所有因素的成功结合可以长期发展和管理销售和服务。建议的方法使您能够经济有效地识别您的销售和服务系统的当前状态,主要挑战和增长机会,以优化您的运营模式。拟议的方法包括对高层管理人员、董事和分支机构员工的调查,对内部审计结果和销售结果的分析,以及对员工的短信调查。所得结果揭示了直接或间接影响销售结果和服务质量的主要问题。在这些数据的基础上,我们提出优化销售和服务体系的建议,并制定行动计划,以提高销售和客户服务质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodology "Identification of Problems and Growth Areas in the Sales and Service System: the advantages of a non-imitation approach"
The authors present their methodology for sales and service system analysis for organizations with a branch network. The methodology has been successfully tested in 2023 and proves to be relevant.  Despite the digital transformation, particularly affecting the development of sales channels and the move to digital, branch networks continue to play a significant role in business. Classic sales channels and the branch network solve a multitude of problems. The success of the sales and service model depends on several factors, and a successful combination of all elements allows to develop and manage sales and service in the long term. The proposed methodology enables you to cost-effectively identify the current state, key challenges and growth opportunities of your sales and service system to optimize your operating model. The proposed methodology includes surveys of top managers, directors and branch employees, analysis of internal audit results and sales results, as well as an SMS survey of employees. The results obtained reveal the main problems that directly or indirectly influence sales results and service quality. On the basis of these data, we make recommendations to optimize the sales and service system and develop an action plan to improve sales and customer service quality.
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来源期刊
CiteScore
7.40
自引率
9.50%
发文量
16
审稿时长
21 weeks
期刊介绍: The Journal of Artificial Societies and Social Simulation is an interdisciplinary journal for the exploration and understanding of social processes by means of computer simulation. Since its first issue in 1998, it has been a world-wide leading reference for readers interested in social simulation and the application of computer simulation in the social sciences. Original research papers and critical reviews on all aspects of social simulation and agent societies that fall within the journal"s objective to further the exploration and understanding of social processes by means of computer simulation are welcome.
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