装配式柔性铺装地砖周期性市场潜力分析数据

本数据能够帮助本公司（生产商）精准识别不同地区铺装地砖的周期性市场潜力度情况，淘汰低市场潜力的产品规格，优化生产排期，提升资源调配效率，增强季节性需求匹配度，提高供货及时率。通过将原材料和产能资源集中在市场潜力指数高的地砖品类，降低仓储成本，缩短供货周期，增强区域市场竞争力，提升利润率。同时，本数据也有利于上游原料供应商和下游工程承包商分析比较不同地砖产品的市场潜力波动规律，从而协同优化原料备货、施工排期和项目采购策略。1.数据收集和预处理：收集公司装配式柔性铺装地砖不同型号销售数据，包括统计周期、销售地区、产品型号、该周期该型号产品销量/块、该周期所有产品总销量/块、该周期该型号产品销售额/万元、该周期所有产品总销售额/万元、该型号产品消费者评分。通过数据清洗确保数据质量。
2.该周期该型号产品销量占比计算：该周期该型号产品销量占比=该周期该型号产品销量/该周期所有产品总销量。
3.该周期该型号产品销售额占比计算：该周期该型号产品销售额占比=该周期该型号产品销售额/该周期所有产品总销售额。
4.该型号产品周期性市场潜力指数构建：该型号产品周期性市场潜力指数=W1×该周期该型号产品销量占比+W2×该周期该型号产品销售额占比+W3×（该型号产品消费者评分/5），其中W1、W2、W3是权重系数，根据各因素的影响程度经内部专家研判后进行调整设定，W1+W2+W3=1。
5.趋势识别：使用ARIMA（自回归积分滑动平均）模型（一种用于分析按时间顺序排列的数据点，以识别趋势、周期性和其他模式的统计模型）进行时间序列分析，基于该类型产品的历史市场潜力指数数据，识别该型号产品的市场潜力指数趋势。

This dataset enables the company (manufacturer) to accurately identify the cyclical market potential of floor tiles for paving across different regions, eliminate product specifications with low market potential, optimize production scheduling, improve resource allocation efficiency, enhance seasonal demand matching, and boost on-time delivery rates. By concentrating raw material and production capacity resources on floor tile categories with high market potential indices, the company can reduce warehousing costs, shorten delivery cycles, strengthen regional market competitiveness, and improve profit margins. Meanwhile, this dataset also helps upstream raw material suppliers and downstream engineering contractors analyze and compare the fluctuation patterns of market potential across different floor tile products, so as to collaboratively optimize raw material stocking, construction scheduling and project procurement strategies.

1. Data Collection and Preprocessing: Collect sales data of different models of the company's prefabricated flexible paving floor tiles, including statistical cycle, sales region, product model, sales volume of this product model in the cycle (unit: piece), total sales volume of all products in the cycle (unit: piece), sales revenue of this product model in the cycle (unit: ten thousand yuan), total sales revenue of all products in the cycle (unit: ten thousand yuan), and consumer ratings of this product model. Ensure data quality through data cleaning.

2. Calculation of Sales Volume Proportion of the Product Model in the Cycle: Sales volume proportion of this product model in the cycle = Sales volume of this product model in the cycle / Total sales volume of all products in the cycle.

3. Calculation of Sales Revenue Proportion of the Product Model in the Cycle: Sales revenue proportion of this product model in the cycle = Sales revenue of this product model in the cycle / Total sales revenue of all products in the cycle.

4. Construction of Cyclical Market Potential Index for the Product Model: Cyclical market potential index of this product model = W1 × Sales volume proportion of this product model in the cycle + W2 × Sales revenue proportion of this product model in the cycle + W3 × (Consumer ratings of this product model / 5), where W1, W2, and W3 are weight coefficients, which are adjusted and set based on the influence degree of each factor through internal expert deliberation, and W1 + W2 + W3 = 1.

5. Trend Identification: Conduct time series analysis using the ARIMA (AutoRegressive Integrated Moving Average) model, a statistical model used to analyze chronologically ordered data points to identify trends, cyclical patterns and other patterns, and identify the market potential index trend of this product model based on the historical market potential index data of this type of product.

搜集汇总

背景与挑战

背景概述

该数据集是杭州利环环境集团有限公司提供的装配式柔性铺装地砖周期性市场潜力分析数据，包含528条CSV格式记录，每月更新。数据集通过统计周期、销售地区、产品型号等字段，结合销量、销售额和消费者评分，计算市场潜力指数和趋势，用于优化生产排期、资源调配和供应链协同，提升企业竞争力。