运动场周边无人零售智能货柜商品需求分析数据

通过研究以及过往经验发现，不同生活场景下人们消费的商品类型也有很大差别，比如学校周边的主要消费的商品为零食、文具等，而运动场周边的主要消费的商品为饮料、纸巾等，所以不同场景下人们的商品需求是无人零售智能货柜行业的一个重要关注点。本数据对各个运动场周边无人零售智能货柜的售卖情况进行分析，从消费者对不同商品类别的选择中，可以得出不同商品类别的售卖占比，体现运动场场景中商品的消费需求情况，帮助充实无人零售智能货柜的企业优化不同类型商品的投放比重，指导各商家在运动场场景的智能货柜上合理分配不同类型商品的优惠方式、优惠力度及新品投放方案。
1、提取了统计区间内无人零售智能货柜有商品售出的数据，包含运动场、货柜编号、商品类别、售卖数量四个字段，对统计区间内的数据聚合，其中数量字段为统计区间内本货柜该商品类型的累计交易件数，对售卖数量及商品类别字段进行分析，2、同类商品售卖数量是通过SUMIFS函数对相同商品类别的售卖数量的求和；3、商品售卖总数量是通过SUM函数将数据统计范围内所有售卖数量求和；4、同类商品售卖数量占比=同类商品售卖数量/售卖总数量*100%；5、商品需求等级运用了ABC分类法，对同类商品售卖数量占比≥40%的，给予“A级”的评价，对40%＞同类商品售卖数量占比≥20%区间的，给予“B级”的评价，同类商品售卖数量占比＜20%的，给予“C级”的评价。

Based on research and accumulated practical experience, it is evident that there are substantial differences in the categories of goods consumed by people across various daily scenarios. For instance, the primary consumer goods around schools are snacks, stationery and similar items, while those around sports fields are beverages, tissues and other related products. Consequently, consumer demand for goods in different scenarios represents a critical focus for the unmanned retail smart vending cabinet industry.

This dataset analyzes the sales performance of unmanned retail smart vending cabinets located around various sports fields. By investigating consumers' selections of different product categories, the sales proportion of each product category can be calculated, which reflects the consumer demand status of goods in the sports field scenario. This work assists enterprises in the unmanned retail smart vending cabinet industry to optimize the allocation proportion of different types of goods, and guides merchants to rationally allocate discount methods, discount intensity and new product launch plans for various product categories on smart vending cabinets in sports field scenarios.

1. Data of unmanned retail smart vending cabinets with completed sales within the statistical interval is extracted, which includes four fields: sports field venue, vending cabinet ID, product category, and sales quantity. Data aggregation is conducted on the dataset within the statistical interval, where the quantity field refers to the cumulative transaction volume of the corresponding product category in this specific vending cabinet during the statistical interval. Analysis is performed on the sales quantity and product category fields.
2. The sales volume of the same product category is obtained by summing the sales quantities of identical product categories using the SUMIFS function.
3. The total sales volume of all goods is calculated by summing up all sales quantities within the statistical scope using the SUM function.
4. The sales proportion of a product category = (sales volume of the same product category / total sales volume) * 100%.
5. The product demand rating is determined via the ABC Classification Method: products with a sales proportion ≥ 40% are rated "Grade A"; those with a sales proportion ranging from 20% (inclusive) to 40% (exclusive) are rated "Grade B"; and products with a sales proportion < 20% are rated "Grade C".

搜集汇总

数据集介绍

特点

该数据集提供了运动场周边无人零售智能货柜的商品需求分析数据，包含商品类别、售卖数量、同类商品售卖数量占比等关键信息，采用ABC分类法对商品需求等级进行评价，适用于无人零售智能货柜的商品投放优化和营销策略制定。