A big seller: I am working on shoes and clothing, and there are many variants. I want to analyze the sales distribution of a certain product's attributes and colors, instead of looking at ASIN or parent ASIN. Can Saihu solve it?

Saihu ERP: Yes! The SPU statistical analysis function of Saihu ERP automatically analyzes the sales of the same type of products, and clearly compares the attributes and trends that are most popular in the market. It does not require manual data processing and supports cross-store data analysis.

(Practical steps: Data>SPU Statistics>Analysis button)

What is SPU?

SPU, we generally say that products with the same product attribute value and characteristics can be called a SPU. For example, a mobile phone case is an SPU, which has nothing to do with the store, color or style.

for example:

The product developer designed a traditional domestic animation series of clothes, and printed the images of each animated character on the clothes. This clothes must have various sizes to meet users of various physiques.

Use "Anime Series" as the model name and "DHXL" as the SPU

"Color" as attribute one, "black" and "white" as attribute values

"Size" as attribute two, "XL" "L" as attribute value

For example, the SKU of the white pattern style in size L: DHXL-white-L, DHXL is its SPU.

(Practical steps: Product > Variant List > Add Variant Product)

Do you have a very familiar feeling ? The concept of SPU is actually a bit like the parent SKU.

Statistical analysis of SPU for multi-attribute commodity management

In order to make it easier for sellers of multi-variant categories to manage and analyze local products, Saihu ERP has developed multi-attribute product management and SPU statistical analysis functions.

On the multi-attribute list page, you can quickly add and maintain local multi-variant product information, distinguish the characteristics of products by attributes and attribute values, and then perform data statistics on the SPU statistics page to view the comparison of all SKUs under each SPU (parent SKU). Data, including profit, sales, refunds for returns, FBA inventory, costs, and more.

Help sellers quickly find more popular SKUs and attributes from a series of products, reduce unnecessary production and procurement, and improve return on investment. The keywords for advertisement placement can also borrow the results of SPU statistical analysis.

If you want to use the SPU statistical analysis function, you need to set the attributes of the product first, that is, create a lot of attribute products (SPU). In order to facilitate users to quickly create batches, Saihu ERP has added an automatic generation function. After setting the SPU and attribute values, thousands of SKUs can be created with one click.

(Practical steps: fill in the SPU, model name, attributes and click to generate automatically)

At this point, you may have some doubts. This process is to create new SPUs and SKUs, which is very convenient, but the SKUs that have been created in history have not entered multi-attribute products or attribute values. Do you need to delete and recreate the historical data? SKU?

No, in order to allow the vast majority of users to use the multi-attribute product management and SPU analysis functions, Saihu ERP has made a very convenient method of adding attributes, which can directly add the created SKU locally and directly assign its corresponding attribute value. , save trouble and worry.

Saihu ERP multi-attribute commodity management function helps sellers to establish a standardized multi-attribute commodity management system. The SPU statistical analysis function helps sellers realize cross-store data analysis, quickly find the attributes and trends of hot-selling products in the SPU, and stock up scientifically.

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