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The science of consumer research, how to analyze the data with insight?

2024-07-18 17:00:05  来源:尚普咨询  浏览量:0

消费者调研是一种收集和分析消费者相关信息的过程,它可以帮助企业了解消费者的特征、需求、偏好、行为、满意度和忠诚度,从而制定有效的产品、价格、渠道和促销策略。消费者调研的数据来源可以有多种,例如问卷调查、深度访谈、焦点小组、观察法、实验法等。消费者调研的数据类型可以分为定量数据和定性数据,前者是可以用数字表示的数据,后者是可以用文字描述的数据。消费者调研的数据分析是指对收集到的数据进行整理、处理、归纳、解释和评价的过程,它的目的是从数据中发现有意义的模式、关系、趋势和差异,从而得出有价值的洞察和Conclusion

消费者调研的数据分析的科学,主要体现在以下几个方面:

数据分析的目标。数据分析的目标是指数据分析的具体问题和期望的结果,它应该与消费者调研的目的和目标相一致,也应该符合企业的战略和营销目标。数据分析的目标应该是明确的、具体的、可衡量的、可实现的和有意义的,它可以用SMART原则来检验。例如,一个数据分析的目标可以是“分析消费者对某一新产品的认知、态度和购买意愿,以及影响这些因素的关键因素,为产品的定价、包装和推广提供依据”。

数据分析的方法。数据分析的方法是指数据分析的具体步骤和技术,它应该根据数据的类型、数量、质量和分析的目标来选择。数据分析的方法可以分为描述性分析、探索性分析、推断性分析和预测性分析,它们分别用于描述数据的基本特征、发现数据的潜在结构、检验数据的假设和关系、以及预测数据的未来变化。数据分析的方法还可以分为统计分析、因子分析、聚类分析、判别分析、回归分析、关联分析、文本分析、情感分析等,它们分别用于分析数据的分布、维度、分组、分类、关系、规则、内容、情感等。数据分析的方法应该是合适的、有效的、可靠的和科学的,它可以用CRISP-DM模型来指导。例如,一个数据分析的方法可以是“对问卷调查的定量数据进行描述性统计分析,对深度访谈的定性数据进行文本和情感分析,然后用因子分析和聚类分析对消费者进行细分,用判别分析和回归分析对消费者的认知、态度和购买意愿进行预测和解释”。

数据分析的结果。数据分析的结果是指数据分析的输出和输出,它应该能够回答数据分析的目标和问题,也应该能够为企业的决策和行动提供支持。数据分析的结果应该是清晰的、准确的、完整的、有用的和有说服力的,它可以用KISS原则来呈现。例如,一个数据分析的结果可以是“消费者对新产品的认知、态度和购买意愿受到产品的功能、品质、价格、包装和口碑的影响,其中功能和品质是最重要的因素,价格和包装是次要的因素,口碑是最不重要的因素。消费者可以分为四个细分市场,分别是高端忠诚者、中端追随者、低端尝试者和无兴趣者,它们的占比分别是15%、25%、35%和25%。高端忠诚者对新产品的认知、态度和购买意愿最高,低端尝试者次之,中端追随者再次之,无兴趣者最低。建议企业针对不同的细分市场,采用不同的营销策略,例如,对于高端忠诚者,可以采用高价高质的策略,强调产品的功能和品质,提高产品的知名度和忠诚度;对于中端追随者,可以采用中价中质的策略,平衡产品的功能、品质、价格和包装,增加产品的吸引力和竞争力;对于低端尝试者,可以采用低价低质的策略,降低产品的价格和成本,扩大产品的覆盖和试用;对于无兴趣者,可以采用放弃的策略,不再投入资源和精力,转移注意力和焦点”。

Conclusion

消费者调研的数据分析是一门科学,它需要运用科学的方法和技术,才能从海量的数据中挖掘出有价值的洞察。本文介绍了消费者调研的数据分析的基本原理和步骤,以及一些常用的数据分析工具和方法。本文还结合尚普咨询公司为客户提供的一些消费者调研案例,展示了如何运用数据分析的科学,为企业提供有用的建议和解决方案。希望本文能够对消费者调研的数据分析的实践和理解有所帮助。




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