A market research technique used to measure the relative preference or importance of a set of items (e.g., product features, brand names, 市场营销 messages).
- 方法: 工程, 产品设计, 项目管理
最大差值分析(最大差值缩放)

最大差值分析(最大差值缩放)
- 敏捷方法论, 客户体验, 设计思维, 市场研究, 产品开发, 产品管理, 统计分析, 用户体验(UX), 用户界面(UI)
目标
如何使用
- 向受访者展示项目子集,要求受访者指出子集中哪个项目最好/最重要,哪个项目最差/最不重要。对不同的子集重复上述步骤。
优点
- 与简单的评级量表相比,它能更准确地衡量重要性;与对许多项目进行全面排序相比,它更便于受访者使用;它能产生区间量表分数。
缺点
- 对受访者的认知要求可能比简单的评分量表更高;需要专门的软件进行设计和分析;选择测试项目至关重要。
类别
- 客户与营销
最适合:
- 测量多个项目(如功能、优点、信息)的相对重要性或偏好性,比评分量表更有效。
MaxDiff Analysis, or Maximum Difference Scaling, is an advanced methodology particularly valuable in market research and product development across various industries such as consumer goods, technology, healthcare, and services. This technique is especially applicable in the early and middle phases of product design when determining which features or attributes resonate most with target audiences. Teams including product managers, design engineers, marketing strategists, and user experience researchers often collaborate to implement this analysis. It provides a clear framework for respondents to evaluate subsets of product attributes or features, clarifying preferences in a way that traditional rating scales may not effectively capture. This approach is valuable during product iterations and concept testing, as it can influence decisions about which features to prioritize based on quantifiable interval-scale scores derived from user preferences. By leveraging MaxDiff, companies can refine their offerings to meet user expectations while optimizing resource allocation in product development processes. As a result, the method is not only practical for identifying key differentiators in a crowded market but also aids in aligning product strategies with consumer needs. Such an evidence-based approach supports competitive positioning and enhances the likelihood of a successful product launch.
该方法的关键步骤
- Define the items to be evaluated based on research objectives.
- Design subsets of items for presentation to respondents.
- Determine the number of rounds or sets to maintain respondent engagement.
- Implement the selection mechanism for respondents to choose best and worst items.
- Analyze the preferences indicated by respondents across subsets.
- Calculate the scores to determine the relative importance of each item.
- Validate the results through statistical methods to ensure reliability and validity.
专业提示
- Utilize randomized subsets to minimize bias and ensure diverse pairwise comparisons while maintaining respondent engagement.
- Incorporate demographic or behavioral segmentation to analyze how preferences differ among various user groups, enhancing the interpretability of results.
- Balance the number of items in each subset to avoid cognitive overload, ensuring clarity and reliability in respondents' choices.
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