Customer and Product Matching

In the previous documents, you have already analyzed finding required products for customers and finding target customers for products templates in detail, and answered the following question: what kinds of products do designers need to create and which target groups these products should serve. In addition, you also need to answer the question that your boss cares about most: how much profit margin is expected. 

Assuming you have already filtered specific groups and product attributes, you can now analyze the product's sales performance in terms of Sales Revenue, Sales Volume, Tag Price, and Average Retail Price in detail.

Top 5 Sales Revenue Analysis

Due to the large number of product IDs, if you want to quickly analyze sales performance, you can analyze the sales performance of the top 5 products by sales revenue, as shown in the following figure.
1. Drag Product ID, Sales Revenue, Count, Tag Price, and Sales Revenue into the analysis area.

2. Double-click Count and rename it Sales Volume, set Summary Mode to Average for one Sales Revenue, double-click the field, and rename it Average Retail Price.

3. Add a Filter Condition for Product ID to filter out the top 5 products by sales revenue.

After dragging the component into the dashboard, you may notice that not all the data is displayed, as shown in the following figure.

If you check the filter conditions for the component, you’ll find that the conditions are affected by the filter components you set up earlier, as shown in the following figure.

So, you need to adjust the control scope of the Tree Label in both Finding Required Products for Customers and Finding Target Customers for Products, as shown in the following figure.

Top 5 Sales Volume Analysis

Similarly, for the analysis of top 5 sales volume, see Top 5 Sales Revenue Analysis. You can directly copy the Top 5 Sales Revenue Analysis component and modify the filter conditions.

In addition, if you want the products to be compared within the same category based on actual needs, you can use Filter to separately filter out the values of Clothing, Accessories, and Shoes under the Main Category. The following figure shows Top 5 Clothing Sales Volume Analysis as an example.

Dashboard Display

Tree Label Filtering

Current VIP Level, Gender 1, Age Range, and Registration Channel have been added to the tree label. You can also select fields based on actual needs.

In addition, you need to configure the scope of Filter Component to control only the components created in the Customer Product Matching, as shown in the following figure.

Time Filter Component

Since the overall data spans a long period of time, analysis misjudgments may appear. Therefore, you can add a Date Interval component, as shown in the following figure.

Tab Component

Congratulations! You have completed all the analysis steps of the Retail E-commerce Customer and Product Analysis. You should now understand how to perform data processing across multiple tables and have become more familiar with FineBI functions through hands-on practice. Additionally, you should now have a clear approach for analyzing how to choose retail e-commerce customers and products.