四川地区京东平台品牌服装销售分析数据

通过平台调取品牌店铺在四川地区商品销售数据，可评估该地区不同季节不同产品销售情况，并通过客户颜色偏好度、各尺寸占比数据判断，了解客户喜好和该区域客户群体尺寸的分布情况，优化营销计划，实现生产订单的合理安排和区域针对性前期铺货。数据收集：收集销售相关的数据，包括订单来源店铺、颜色、尺码、季节、省、市、区、品类等。
数据处理：对数据进行清洗、删除重复数据，处理缺失值，识别和处理异常值，确保数据的准确性和一致性。
数据分析：对数据进行统计分析，根据季节变化，统计四川区域内每季产品销售量的top6，然后通过字段“颜色”、“尺寸”分别进行数据分析，对排名前6品类的颜色偏好度和尺寸比例分别进行统计，颜色偏好度=该品类该颜色订单量/该品类订单总量，尺寸比例=该品类该尺寸订单量/该品类订单总量。计算出该区域内各个季节，客户群体偏向的品类，该品类顾客颜色的偏好和尺寸的选择比例，通过自建模型，使用BI实现分析结果的可视化展示。
数据应用：将分析结果应用到运营场景中，帮助品牌店铺更好了解该区域内各季节客户的偏好和销售尺寸的选择，从而制定更精准的营销策略，指导企业合理安排生产和铺货。

This dataset is constructed by extracting commodity sales data of brand stores in Sichuan Province via a dedicated platform. It supports the evaluation of sales performance of various products across different seasons in this region. By analyzing customer color preference and product size proportion data, it also enables insights into customer preferences and the size distribution of local customer groups, thereby optimizing marketing plans, facilitating rational arrangement of production orders, and supporting targeted regional pre-stocking.

Data Collection: Sales-related data is collected, covering fields such as order source store, color, size, season, province, city, district, and product category.

Data Preprocessing: Data cleaning operations are performed, including removing duplicate records, handling missing values, and identifying and processing outliers, to ensure data accuracy and consistency.

Data Analysis: Statistical analysis is conducted on the preprocessed data. First, the Top 6 best-selling product categories in each season within Sichuan Province are counted based on seasonal variations. Subsequently, separate analyses are carried out using the "color" and "size" fields. For each of the Top 6 product categories, the color preference degree and size proportion are calculated, where Color Preference Degree = (Order volume of a specific color for a given category) / (Total order volume of that category), and Size Proportion = (Order volume of a specific size for a given category) / (Total order volume of that category). Through these calculations, the product categories preferred by local customers, as well as their color preferences and size selection proportions for each season in the region, are derived. A self-built model is then utilized together with Business Intelligence (BI) tools to realize the visualization of the analysis results.

Data Application: The analysis outcomes are applied to operational scenarios, helping brand stores gain a better understanding of customer preferences and size selection trends across seasons in this region. This allows the formulation of more precise marketing strategies, and provides guidance for enterprises to rationally arrange production and regional stocking.