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A rapid Kano-based approach to identify optimal user segments
Research in Engineering Design ( IF 2.3 ) Pub Date : 2018-01-12 , DOI: 10.1007/s00163-018-0282-y
Reynir Smari Atlason , Arnaldur Smari Stefansson , Miriam Wietz , Davide Giacalone

The Kano model of customer satisfaction provides product developers valuable information about if, and then how much a given functional requirement (FR) will impact customer satisfaction if implemented within a product, system or a service. A limitation of the Kano model is that it does not allow developers to visualize which combined sets of FRs would provide the highest satisfaction between different customer segments. In this paper, a stepwise method to address this shortcoming is presented. First, a traditional Kano analysis is conducted for the different segments of interest. Second, for each FR, relationship functions are integrated between x = 0 and x = 1. Third, integrals are inserted into a matrix crossing segments and FRs, where FRs with the highest sum across the chosen segments are identified. Finally, the functions of the chosen segments with the smallest interval, define the FRs appealing to the biggest target group. The proposed extension should assist product developers within to more effectively evaluate which FRs should be implemented when considering more than one combined customer segment. It shows which segments provide the highest possibility for high satisfaction of combined FRs. We demonstrate the approach in a case study involving customers’ preference for outdoor sports equipment.

中文翻译:

一种基于 Kano 的快速识别最佳用户细分的方法

客户满意度的 Kano 模型为产品开发人员提供了有价值的信息,即如果在产品、系统或服务中实施,给定的功能需求 (FR) 是否会影响客户满意度,以及影响程度。Kano 模型的一个限制是它不允许开发人员可视化哪些 FR 组合集将提供不同客户群之间的最高满意度。在本文中,提出了一种逐步解决此缺点的方法。首先,对不同的兴趣部分进行传统的卡诺分析。其次,对于每个 FR,​​在 x = 0 和 x = 1 之间对关系函数进行积分。第三,将积分插入矩阵交叉段和 FR,其中识别出所选段中总和最高的 FR。最后,具有最小间隔的所选细分市场的功能,定义了吸引最大目标群体的 FR。提议的扩展应有助于产品开发人员在考虑多个组合客户群时更有效地评估应实施哪些 FR。它显示了哪些细分为组合 FR 的高满意度提供了最高的可能性。我们在涉及客户对户外运动设备偏好的案例研究中展示了该方法。它显示了哪些细分为组合 FR 的高满意度提供了最高的可能性。我们在涉及客户对户外运动设备偏好的案例研究中展示了该方法。它显示了哪些细分为组合 FR 的高满意度提供了最高的可能性。我们在涉及客户对户外运动设备偏好的案例研究中展示了该方法。
更新日期:2018-01-12
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