In industry intelligence, we can not only check the category visitor proportion data, but also discover which categories in this industry are worthy of our efforts and discover the products in this category by querying these visitor proportion data. Whether there is market potential, this will make it easier for us to understand the data of the category in advance and avoid wasting major energy on worthless categories later. How to analyze data and find those categories worthy of our focus and maintenance? Here I will give you a step-by-step detailed demonstration using shoes as an example.
You can see that I selected shoes. This is a first-level category, which can also be called a top-level category. After clicking on shoes, another category appears. This is the subcategory under the shoes category. We Call it a secondary category. Among the secondary categories of shoes are: boots, non-professional sports shoes, flat shoes, garden shoes, other shoes, high heels, sandals & flip-flops, shoe accessories, indoor slippers/home furnishings Nine categories of shoes. In order to analyze which category has market prospects, we need to query the visitor proportion data of these nine categories one by one. Here we first check the data of boots.
We see that boots account for 27.05% of visitors and 8.34% of orders. This data indicates that under the first-level category of shoes, boots account for 27.05% of shoes in the second-level category. market, and then we will analyze other categories under the secondary category.
To analyze other categories, we can use industry trends. Instead of querying industry data one by one, we can use industry trends to query three industries at once, so for the sake of efficiency, we use this tool to obtain data.
We chose boots, non-professional sports shoes, and flat-heeled shoes under the shoes. The data of the three categories accounted for 26.22% of boots, 49.28% of non-professional sports shoes, and 39.59% of flat-heeled shoes. . Let’s take a look at the proportion of orders in these three categories.
The proportion of transaction orders in these three categories is 7.96% for boots, 36.46% for non-professional sports shoes, and 15.48% for flat shoes. By analyzing the two data sets of the number of visitors and the number of orders, it can be found that the number of visitors If the quantity is large, the order volume will also be large. This is like opening a physical store offline. If there is no flow of people into the physical store, will the sales be good? Among these three categories, the market for non-professional sports shoes is very large. If you want to choose one of the three categories, it is recommended to choose the category of non-professional sports shoes. Next, we will continue to analyze the data of other categories to see which category has the most market.
After querying, we can see that the data proportions of these categories are: garden shoes 2.37%, other shoes 3.52%, high heels 31.18%, sandals & flip-flops 34.2%, shoe accessories 6.92%, indoor slippers / Home shoes 9.8%. After analyzing these categories, we found that some categories have a large number of visitors and a large order volume, while some categories have a small number of visitors and a small order volume. Maybe many novice friends did not know how to analyze before, resulting in the store uploading a lot of shoe products, but every day Unable to place order. I have met many friends asking for advice in this regard. The most common one is why my store has uploaded so many products but there is no traffic or orders? This is largely because there has been no detailed analysis and no investigation into which products have a market, visitors and orders.
We analyzed the data of nine categories earlier. Let’s summarize which categories are worthy of our careful maintenance in the future. Among these nine categories, we can see that the largest proportion is non-professional sports. Shoes, the other four categories of flat shoes, sandals & flip-flops, high heels, and boots all account for about 30%. We will not query the transaction order volume data of these five categories because the number of orders will naturally increase if there are many visitors. There will be more.
So, if we want to sell shoes on AliExpress, we will focus on selling shoes in the five categories of non-professional sports shoes, flat shoes, sandals & flip-flops, high heels, and boots, and the other four categories. We can also sell categories with a small proportion on the shelves and in stores, but we just don’t focus on these products.