Detailed explanation of cross-border e-commerce data analysis and replenishment strategies
This article aims to help readers better understand and apply related technologies by introducing data analysis methods and replenishment strategies in cross-border e-commerce. Specifically, we will discuss how to use Excel’s “Pivot Table” function to conduct product price range analysis and category layout analysis, and how to implement inventory management and replenishment analysis through Power Pivot.
1. Commodity price range analysis
In order to conduct effective product price range analysis, we first need to collect information such as unit price and quantity of products in online store orders, and filter and organize them. Next, filter the data through Excel’s “Pivot Table” function and draw relevant conclusions.
1. Open the data source
Open the data source for the required analysis, such as “Project Five Task Two Product Structure Analysis”. Select any data and click the “From Table” button under the “Data” tab to enter the Power Query editor.
2. Calculate new indicators
In the PQ interface, calculate indicators such as order cost (Order cost) and order price (Order price) by adding new columns. In addition, the proportion of goods in orders and gross profit need to be calculated.
3. Create a pivot table
Select any data in the new worksheet, click the “PivotTable” button in the “Insert” tab, and set the pivot table fields. In this way, it is possible to observe the sales of products in different price ranges.
2. Category layout analysis
Category layout analysis can help merchants better understand which product categories are performing well. To do this, we need to collect order information and use Excel functions to process it.
1. Enter query
Click the “Show Query” button in the “Data” tab to enter the corresponding query interface.
2. Copy and set queries
Copy the desired query operations in the query list and adjust the query parameters to meet specific analysis needs.
3. Data analysis
By observing the data obtained, you can evaluate the performance of different product categories from a profit perspective and make decisions accordingly.
3. Replenishment analysis
Replenishment analysis is one of the key steps in ensuring adequate inventory. It involves the analysis of historical sales data and forecasting of future demand.
1. Data import and calculation
First, import the inventory quantity of each product in the store into Power Pivot, and calculate relevant indicators, such as sales in the last N days, how many days need to be replenished, etc.
2. Import PivotTable
Import the calculation results into Excel’s pivot table for further analysis.
3. Data analysis
Based on the analysis results, it can be determined which products need to be replenished immediately, and which products can be replenished after one or more cycles.
4. Summary
Through the above steps, we can effectively conduct cross-border e-commerce product price range analysis, category layout analysis and replenishment analysis. It is worth noting that the rational use of data analysis tools not only helps improve operational efficiency, but also brings more business opportunities to enterprises. I hope this article can provide you with valuable information and inspire you to explore more possibilities in the field of cross-border e-commerce.