湖南省长沙市订单分析数据

1.通过分析各个订单的Z-Score可以得到各个时间段用户订单金额的稳定性变化，用于合理预测区域的订单金额的走向，优化区域发展战略布局，同时分析销售趋势，供应商更好地安排生产计划和物流配送，提升供应链协同效率2.建立科学的战略决策模型。该模型能够识别高峰时间段，指导企业合理配置资源，通过环比增长数据可以分析得到各个时间段的峰值时间，指导企业科学应对销售高峰期，很好的进行科学排班，确保足够人手，控制人力成本。3.通过t（评分系统）和s（评分系统）的综合分析可以能够制定针对性的渠道优化方案和营销策略，向用户推送优惠信息，提升转化率，提升整体市场竞争力
数据采集：分区域读取数据库中每笔交易订单时间和订单金额。相同时间的订单以数据库内生成前后顺序排序。 Z-Score：通过计算单笔订单的支付价格与整体均值的差值再除以总体标准差得到Z-Score。环比增长：通过计算当前订单金额与前一笔订单的比值减1获得（当首行或者无前序数据返回空值）。t和 s为评分系统，当Z-Score>0.2时t为正不稳定，当0.2≥Z-Score≥-0.2时t为稳定，当Z-Score<-0.2时t为负不稳定。当环比增长>0则s=增大，当环比增长=0时 s=稳定，当s<0时s=减小。峰值区间说明：由于s是基于前一条订单做出的判断， 当前时间的s处于增加而后一条订单的s处于减少的时候则当前订单数据为区间内峰值。

1. Analyzing the Z-Score of individual orders reveals the stability changes of users' order amounts across different time periods. This enables reasonable prediction of regional order amount trends, optimization of regional development strategic layouts, analysis of sales trends, allowing suppliers to better arrange production plans and logistics distribution, and improving supply chain collaboration efficiency.
2. Establish a scientific strategic decision-making model. This model can identify peak time periods and guide enterprises to rationally allocate resources. By analyzing month-on-month growth data, the peak time of each time period can be determined, which helps enterprises scientifically respond to sales peak periods, conduct effective scientific scheduling, ensure sufficient staffing, and control labor costs.
3. Comprehensive analysis of the t (scoring system) and s (scoring system) enables the formulation of targeted channel optimization plans and marketing strategies, pushing promotional information to users, improving conversion rates, and enhancing overall market competitiveness.

Data Collection: Read the order timestamp and order amount of each transaction in the database by region. Orders with the same timestamp are sorted according to their generation sequence in the database.

Z-Score: The Z-Score is calculated by dividing the difference between the payment price of a single order and the overall mean by the population standard deviation.

Month-on-Month Growth: Calculated as (current order amount / previous order amount) minus 1, returns a null value if it is the first entry or no preceding order data exists.

Scoring Systems t and s: The t scoring system is defined as follows: when Z-Score > 0.2, t is categorized as positively unstable; when 0.2 ≥ Z-Score ≥ -0.2, t is categorized as stable; when Z-Score < -0.2, t is categorized as negatively unstable. The s scoring system is defined as follows: when month-on-month growth > 0, s = increasing; when month-on-month growth = 0, s = stable; when month-on-month growth < 0, s = decreasing.

Peak Interval Explanation: Since the s value is determined based on the previous order, the current order data is identified as the peak within the interval when the s value of the current time is increasing while the s value of the subsequent order is decreasing.

搜集汇总

背景与挑战

背景概述

该数据集聚焦湖南省长沙市的订单分析，包含2100条企业数据，每日更新，采用Z-Score和环比增长算法评估订单金额稳定性与峰值趋势，旨在优化区域战略布局、供应链协同和营销策略，提升市场竞争力。