一种统计市场调研技术,用于确定人们对构成单个产品或服务的不同属性(特征、功能、益处)的价值取向。
- 方法: 工程, 质量
联合分析

联合分析
- 敏捷方法论, 客户体验, 设计思维, 市场研究, 产品设计, 产品开发, 统计分析, 价值主张
目标
如何使用
- 向受访者展示一系列产品概况(属性组合),并要求他们做出选择、排序或评级。然后进行统计分析,揭示每个属性的感知价值。
优点
- 有助于了解客户对不同产品功能的偏好和权衡;可以优化产品设计和定价;有助于市场细分和新产品开发。
缺点
- 设计和分析可能比较复杂;结果取决于属性和水平的选择;受访者在真实市场中的行为可能并不总是与调查中的行为一致。
类别
- 客户与营销, 经济学, 产品设计
最适合:
- 了解客户如何重视产品或服务的不同属性,以优化设计和营销。
Conjoint Analysis finds applications in various industries, including consumer goods, automotive, healthcare, and technology, making it adaptable across different project phases, particularly in the stages of design and market feasibility studies. This methodology is often initiated by product managers or market researchers seeking to understand customer preferences before launching a new product or feature. For instance, in the automotive industry, manufacturers can assess how consumers value aspects such as fuel efficiency, safety features, and price, informing both design and marketing strategies. Participants typically include a representative sample of the target market, allowing for diverse input that can reveal unique segments within the audience. By analyzing results, companies can identify not only which attributes are most important to consumers but also the trade-offs they are willing to make, aiding in decision-making regarding product specifications and pricing structures. This process also enhances the ability to create targeted marketing messages that resonate with distinct consumer groups and informs decisions on product bundling or feature prioritization, thereby improving the likelihood of market success for new releases.
该方法的关键步骤
- Define the product attributes and levels relevant to the study.
- Select a suitable experimental design to create product profiles.
- Develop a choice set or questionnaire including product profiles.
- Administer the choice task to the respondents.
- Collect and organize the choice data for analysis.
- Apply a statistical model, such as logistic regression, to analyze the data.
- Calculate part-worth utilities for each attribute level.
- Interpret the results to determine attribute importance and customer preferences.
- Conduct simulations to predict market behavior with proposed product configurations.
专业提示
- Utilize hybrid methods by combining traditional conjoint analysis with machine learning techniques to capture non-linear preferences and complex interactions among attributes.
- Incorporate iterative testing in exploratory phases to refine attribute definitions and levels based on preliminary respondent feedback.
- Segment your sample thoughtfully to identify niche market segments that may have distinct preferences, thus uncovering more tailored insights for product differentiation.
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