豆制品类菜品预订偏好数据

豆制品类菜品预订偏好数据对于餐饮企业及其供应链管理至关重要。首先，这些数据使企业能够识别顾客对各类豆制品菜品（如豆腐、豆浆、豆皮等）的偏好，从而优化豆制品菜品的菜单设置，满足市场需求，提升顾客满意度。其次，通过分析预订率及其变化，企业能够预测豆制品食材的需求量，进而调整采购计划，减少库存积压和浪费，提高库存管理效率。此外，预订偏好数据还能为营销活动提供依据，比如通过推广高预订率的豆制品菜品来增加销量，或通过特价优惠来提升低预订率豆制品菜品的吸引力。1.数据抽取和预处理：（1）从公司订单系统抽取豆制品类菜品的预订数据，包括菜品名称、菜品代号、预订单号、预订日期、预订时间、预订数量。（2）通过数据清洗去除无效或错误记录，确保数据质量。 2.计算本菜品近30日及近30-60日间的预订率：（1）基于历史数据，利用SUM函数计算所有豆制品类菜品近30日及近30-60日间的预订总数量。（2）使用SUMIFS函数计算本菜品近30日及近30-60日间的预订总数量。（3）本菜品近30日预订率=本菜品近30日预订总数量/所有豆制品类菜品近30日预订总数量×100%；本菜品近30-60日间的预订率=本菜品近30-60日间的预订总数量/所有豆制品类菜品近30-60日间的预订总数量×100%。 3.输出近30日预订率排前三的豆制品类菜品：使用数据透视表对历史积累的预订率数据进行汇总和排序，使用RANK函数筛选出预订率最高的前三名菜品并进行可视化输出。 4.计算本菜品预订率变化值：本菜品预订率变化值=本菜品近30日预订率-本菜品近30-60日间的预订率。 6.本菜品预订偏好趋势判断：若变化值＞0，则为“偏好提升”，若变化值＜0，则为“偏好下降”，若变化值＝0，则为“偏好不变”。Booking preference data of bean curd dishes is critical for catering enterprises and their supply chain management. First, such data enables enterprises to identify customers' preferences for various bean curd dishes (e.g., tofu, soybean milk, yuba, etc.), thereby optimizing the menu setup of bean curd dishes to meet market demand and improve customer satisfaction. Second, by analyzing booking rates and their changes, enterprises can forecast the demand for bean curd ingredients, adjust procurement plans accordingly, reduce inventory overstock and waste, and enhance inventory management efficiency. In addition, booking preference data can also provide a basis for marketing campaigns, such as promoting high-booking-rate bean curd dishes to increase sales, or offering special discounts to enhance the attractiveness of low-booking-rate bean curd dishes. 1. Data extraction and preprocessing: (1) Extract booking data of bean curd dishes from the company's order system, including dish name, dish code, booking order number, booking date, booking time, and booking quantity. (2) Clean the data to remove invalid or erroneous records and ensure data quality. 2. Calculate the booking rates of the target dish in the past 30 days and the period from 30 to 60 days ago: (1) Based on historical data, use the SUM function to calculate the total booking quantity of all bean curd dishes in the past 30 days and the period from 30 to 60 days ago. (2) Use the SUMIFS function to calculate the total booking quantity of the target dish in the past 30 days and the period from 30 to 60 days ago. (3) Booking rate of the target dish in the past 30 days = (Total booking quantity of the target dish in the past 30 days / Total booking quantity of all bean curd dishes in the past 30 days) × 100%; Booking rate of the target dish in the period from 30 to 60 days ago = (Total booking quantity of the target dish in the period from 30 to 60 days ago / Total booking quantity of all bean curd dishes in the period from 30 to 60 days ago) × 100%. 3. Output the top 3 bean curd dishes ranked by booking rate in the past 30 days: Use a pivot table to summarize and sort the historically accumulated booking rate data, and use the RANK function to filter and visually output the top three dishes with the highest booking rates. 4. Calculate the booking rate change value of the target dish: Booking rate change value of the target dish = Booking rate of the target dish in the past 30 days - Booking rate of the target dish in the period from 30 to 60 days ago. 6. Judgment of booking preference trend of the target dish: If the change value > 0, it is classified as "Preference Improvement"; if the change value < 0, it is classified as "Preference Decline"; if the change value = 0, it is classified as "Preference Unchanged."

搜集汇总

数据集介绍

特点

豆制品类菜品预订偏好数据集包含538条记录，每日更新，记录了豆制品类菜品的预订信息，如菜品名称、预订日期、预订数量等，并计算了预订率和预订偏好趋势，适用于餐饮企业的菜单优化和库存管理。