In the “Data Aspect” – “Product Analysis” in the “AliExpress” backend, you can view the detailed data of the single product in the “AliExpress” store, and guide us to analyze the shortcomings of the single product. The product analysis function includes a lot of data. I will just find a single product in the store to show you how to perform data analysis.
We see that there are two options to expand data analysis and traffic sources. We first click “Traffic Sources” to open it.
After opening it, we can see the source and destination data of visitors to this product. 34.68% of visitors to other sites on the site. After coming to this product through other sites on the site, 69.93% of people exited the store, and 16.75% of people purchased the product. After adding to the shopping cart, 5.14% of the people browsed other product pages of the store, 3.77% of the people added it to favorites, 3.19% of the people browsed other pages of the store, and 1.21% of the people came directly to the order page. Through these data, we We can know what aspects we should improve. For example, if the exit rate from our store is high, it may be that the product keywords use irrelevant words, thus attracting buyers who are not very interested in entering the store. Since they have no intention, they will definitely click immediately. If the page is closed, or the product itself is not attractive enough, we still need to optimize it. In fact, the exit rate of this product from our store is 69.93%, which shows that its attractiveness is still acceptable. Most sellers have this data between 70% and 80%. However, in order to continue to reduce the exit rate, we need to optimize and increase the attractiveness of the product.
TOP visitor region is to view the country distribution of visitors to this product. 57.15% of visitors to this single product are from other countries, Russia accounts for 16.24%, Brazil accounts for 11.23%, and France accounts for 15.39%. Understand After finishing the visitor area, we click “Expand Data Analysis” in Figure 8-15 to view more detailed product data.
Expand the data analysis chart. In the conversion analysis, we first look at the data of search exposure and pageviews. The blue data bar represents the data of this product.
The search exposure of our product is 14481, which is far beyond the industry average exposure of 88, but it is still far from the top 10 in the industry, but it is very close, which shows that the exposure of the product is very good. Next, let’s look at the pageview data. Although our pageviews of 311 have exceeded the industry average, it is still far from the top 10 in the industry. Therefore, if this single product wants to improve, we still need to work on the pageviews. We can optimize the associated template. and decorating stores to strengthen store guidance.
Let’s take a look at the number of visitors and orders. The number of visitors to our product is 247, which is 633 different from the top 10 in the industry. Earlier we saw that the exposure of the product is about the same as the top 10 in the industry, so why are the visitors The numbers are so different? The reason is the click-through rate. We all know that exposure is equivalent to how many people see our product. However, you must click to browse the product. Therefore, if the exposure is similar to the TOP10, fewer visitors must mean that the click-through rate is low. Among the number of transaction orders, our number of orders is 25, which is 63 orders different from the top 10 in the industry. This data shows that our conversion rate is definitely lower than that of the top 10, so let’s see if the click-through rate and conversion rate are low.
Our click-through rate of 1.53% is lower than the industry average. This shows that there is a problem with the main image of our product. We need to optimize the attractiveness of the main image to increase the click-through rate. The subsequent transaction conversion rate of 10.12% is similar to the top 10 in the industry, but it is far behind the industry average. Since the conversion rate is similar to the top 10 in the industry, why is there such a big difference in the number of orders? It should also be the reason for the click-through rate, because the click-through rate is half of the top 10 in the industry, so the number of visitors browsing this product is relatively small. If the conversion rate is good, if you want to increase orders, you need to add more visitors. So we have to find ways to increase the click-through rate and the number of visitors.
Next we directly check the visitor behavior analysis. In the visitor behavior analysis, the average stay time of buyers in our store is 39, and the top 10 in the industry is 65. This shows that our product description page is not particularly attractive to customers. It is necessary to optimize the description page and enrich product information to increase appeal. In addition, the number of inquiries is basically 0, which means that our product description is very detailed and customers can understand the product well without consulting us. However, this description is not attractive, so the stay time is not long. If the number of inquiries is too high, it means that our product description is difficult for customers to understand, then we need to supplement the product description.
Then let’s take a look at the number of times added to shopping carts and the number of times added to favorites. The number of times our products have been added to shopping carts is 59, which is far from the 218 of the top 10 in the industry. The number of times added to favorites is 13, which is 45 compared to the top 10 in the industry. Very different. These data indicate that the product is unattractive. We need to enhance the attractiveness of each product in all aspects to make these two data go up.
Finally, let’s take a look at the keyword analysis tool. The keyword analysis tool can see the TOP10 keywords exposed and browsed. Through these keywords, we can understand which keywords our single product uses to bring traffic. , which keywords have the greatest exposure, which keywords have the most views, etc. If the keywords displayed here have many words that are not related to the product, it will affect the browsing and conversion of the product, indicating that we need to adjust the product Keywords, if many keywords are not exposed and viewed, please check whether the keywords of the product have search volume.