猫粮优势型号识别数据

根据猫粮的销售情况，通过分析不同主要成分和适用宠物品种等关键参数的销售占比，识别出当地市场的优势商品套餐。这为制造商和品牌商优化产品线、聚焦营销重点以及合理配置资源提供了有力的数据支持。同时，也为分销商、零售商以及供应链合作伙伴提供了清晰的市场洞察，有助于他们更精准地把握消费者需求，制定更高效的库存管理和促销策略。1.数据采集：收集猫粮产品的销售订单信息，具体包括：统计时间、型号名称、销售区域、购买数量（件）、主要成分、适用宠物品种。
2.数据预处理：对采集的数据进行清洗，去除重复或缺失的数据记录。
3.计算销售总量：统计时间的年份为该年，使用SUM函数将该年12个月的历史数据中所有购买数量累加，计算出猫粮总销售量。
4.基于主要成分识别优势型号：（1）筛选特定型号名称的订单，利用SUM函数将购买数量累加计算出该型号的销售总量，并计算其销售占比=销售总量/猫粮总销售量*100%。同理，计算其他型号名称的销售总量及销售占比。（2）比较不同型号名称对应的销售占比，较高的那个作为基于主要成分的优势型号。
5.基于适用宠物品种识别优势型号：（1）筛选特定型号名称的订单，利用SUM函数将购买数量累加计算出该型号的销售总量，并计算其销售占比=销售总量/猫粮总销售量*100%。同理，计算其他型号名称的销售总量及销售占比。（2）比较不同型号名称对应的销售占比，较高的那个作为基于适用宠物品种的优势型号。

Based on the sales data of cat food, by analyzing the sales share of key parameters such as different main ingredients and applicable pet breeds, this dataset identifies the dominant product bundles in the local market. It provides strong data support for manufacturers and brands to optimize their product lines, focus on marketing priorities and allocate resources rationally. Meanwhile, it also offers clear market insights for distributors, retailers and supply chain partners, helping them accurately grasp consumer demand and formulate more efficient inventory management and promotion strategies.
1. Data Collection: Collect sales order information of cat food products, specifically including: statistical time, model name, sales region, purchase quantity (unit), main ingredients, and target pet breeds.
2. Data Preprocessing: Clean the collected data to remove duplicate or missing data records.
3. Calculate Total Sales Volume: For the year corresponding to the statistical time, use the SUM function to accumulate the purchase quantities of all historical sales records across the 12 months of that year, and calculate the total sales volume of cat food.
4. Identify Dominant Models Based on Main Ingredients: (1) Filter the orders corresponding to specific model names, use the SUM function to accumulate the purchase quantities to calculate the total sales volume of each model, and calculate its sales share = total sales volume / total cat food sales volume * 100%. Similarly, calculate the total sales volume and sales share of other model names. (2) Compare the sales shares corresponding to different model names, and the model with a higher sales share is regarded as the dominant model based on main ingredients.
5. Identify Dominant Models Based on Target Pet Breeds: (1) Filter the orders corresponding to specific model names, use the SUM function to accumulate the purchase quantities to calculate the total sales volume of each model, and calculate its sales share = total sales volume / total cat food sales volume * 100%. Similarly, calculate the total sales volume and sales share of other model names. (2) Compare the sales shares corresponding to different model names, and the model with a higher sales share is regarded as the dominant model based on target pet breeds.

搜集汇总

背景与挑战

背景概述

该数据集为猫粮优势型号识别数据，包含681条CSV格式记录，每月更新，通过分析销售订单中的主要成分和适用宠物品种等字段，计算销售占比以识别市场优势型号，旨在辅助制造商和零售商优化产品策略和库存管理。