基于市场细分的数字化社区生鲜折扣平台运营策略研究

Research on Operational Strategies of Digitally-Driven Community Fresh Food Discount Platforms Based on Market Segmentation

摘要: 传统社区生鲜零售的“日清折扣”模式面临显著的供需错配与代际消费行为差异，其根源在于市场细分理论(STP)长期忽视“时间”作为消费者稀缺资源的核心维度。文章突破STP的静态细分常规，引入时间价值理论，构建了“时段 × 人群 × 场景”的三维市场细分模型，并提出“智能分时折扣解决方案提供商”的创业定位。通过钱大妈模式的案例分析与策略优化推演，发现数字化赋能的商品分层动态折扣与“预约 + 自提”流程再造，在理论测算层面可有效降低损耗率、优化客群结构。研究将时间价值维度纳入生鲜零售的市场细分框架，拓展了STP理论在高频消费场景中的应用边界，为数字化社区生鲜折扣平台的创业实践提供了理论依据与操作路径。

Abstract: The traditional “daily clearance discount” model of community fresh food retail faces significant supply-demand mismatches and intergenerational Differences in Consumer Behavior, rooted in the long-term neglect of “time” as a core dimension of consumers’ scarce resources within STP theory. This study breaks from STP’s static segmentation conventions, introduces time value theory, and constructs a three-dimensional market segmentation model of “time slot × demographic group × scenario”, proposing the entrepreneurial positioning of an “intelligent time-phased discount solution provider”. Through a case analysis of the Qian Dama model and a deduction of strategy optimization, it finds that digital-enabled dynamic tiered product discounts and the reengineering of the “reservation + self-pickup” process can, at the level of theoretical calculation, effectively reduce loss rates and optimize customer structure. This study incorporates time value into the market segmentation framework for fresh food retail, expanding STP theory’s application boundaries in high-frequency consumption scenarios and providing a theoretical foundation and operational pathways for digital community fresh food discount platform startups.