How to increase the exposure of AliExpress products by reasonably arranging the loading and unloading time and window recommendations

On the AliExpress platform, product listing and removal time and window recommendations are important factors that affect product exposure.

The importance of loading and unloading time and how to arrange it appropriately

The “on the shelf” in the “up and off the shelf” refers to the release of the product, and the “off the shelf” refers to the expiration date of the product. According to practice, it has been found that the exposure of a product will increase when it is about to be removed from the shelves. Therefore, rationally arranging the time when products are put on and off the shelves is crucial to increasing exposure. First of all, sellers need to understand the peak traffic period of the store. They can usually check the real-time traffic situation through the store’s data analysis tool. After determining the peak period, you can arrange the products to be put on the shelves during this period to gain more exposure.

Let’s take a specific example: Assume that the store plans to upload 140 products, and it is known that the store traffic peak is from 9 am to 11 am US time, then new products can be released starting at 10 am, one every 6 minutes, every Release 10 per day. After 14 days of this, 10 products will be removed from the shelves at 10 a.m. every day, thus forming a good cycle effect. Avoid releasing all products at once or randomly as this will result in uneven distribution of removal times and will not maximize exposure opportunities.

Correct strategies for using window recommendations

Window recommendation is a function provided by the AliExpress platform, which can significantly increase the exposure and ranking of recommended products. However, not all products are suitable for adding window recommendations. Priority should be given to those products with development potential. The specific steps are as follows: Log in to the AliExpress backend and enter the “Product Management” page, click the “Window Recommendation” button behind the products that need to be promoted to complete the settings; you can also add them in batches through the “Other Batch Operations” option.

In order to ensure the effectiveness of window recommendations, it is recommended to conduct a comprehensive data analysis of candidate products. For example, check “Expand Data Analysis” in product analysis to check whether key indicators such as product exposure, number of visitors, search click-through rate, and transaction conversion rate meet industry standards or have growth potential. Adding window recommendations will only produce the desired results if these data perform well.

In addition, for new products that are newly launched but lack sufficient data support, you can also give them the opportunity to be recommended in the window, so as to quickly accumulate user feedback and evaluate their market acceptance. It should be noted that strategies for poorly performing products should be adjusted in a timely manner to avoid wasting resources.

To sum up, by scientifically planning the loading and unloading time and rationally using the window recommendation mechanism, the exposure of products in AliExpress stores can be effectively increased, thereby promoting sales growth.