In Amazon operations, the trend of “experience-oriented vs. data-oriented” is reflected in all aspects. This section takes conversion rate optimization as an example to explain the difference between “experience-oriented” and “data-oriented”.
For Amazon operators, conversion rate optimization is one of the basic skills of operations, because conversion rate = order volume minus traffic, so under the same traffic situation, how to increase order volume becomes the key to improving conversion. Generally speaking, the conversion rate is affected by multiple factors: shopping cart, price, pictures, graphic content, review score, number of reviews, FBA service… The “empirical operation” methodology usually “selects the big and discards the small” among these factors, and the one that has the greatest impact on the conversion rate is whether the listing link has a shopping cart. The most efficient way to obtain a shopping cart is to send FBA inventory, so that the link has a “prime order” blue label, thereby increasing the possibility of user purchase.
In addition to “selecting the big and discarding the small” among various factors, “empirical operation” also emphasizes operational tactical skills. For example, through special settings in the background inventory (the detailed operation method of this technique will be introduced in Chapter 6), the operator can make the listing display “Only X left in stock – order” in the front-end interface. Soon”, which means “only a few items are in stock, please buy now”. The information that the inventory is about to sell out can encourage consumers to buy, thereby increasing the conversion rate.
In terms of image and text optimization, “empirical operation” can also find ways to improve the conversion rate. For example, in the A+ image and text page of the clothing category listing, the operator can visualize the size information to help consumers better understand the size data and improve the conversion rate.
Although “empirical operation” can achieve “comprehensive + taking the big and giving up the small”, its optimization effect cannot be specifically quantified. At this time, the advantages of “data-based operation” can be reflected, and the back-end operator of the Amazon store can obtain relevant data such as the number of buyer visits, the number of page views, and the conversion rate of order products.
< p>The more times a buyer visits a page, the longer it takes, and the higher their willingness to buy. By comparing the two, we can define the access depth coefficient, and its calculation formula is as follows:
Access depth coefficient = number of page views/number of buyer visits
By comparing the changes in the access depth coefficient with the conversion rate, we can find out the elements that need to be optimized in the listing. It is not difficult to see that compared with the “experience-based operation” method, this method is more efficient and more accurate. In the framework of “data-based operation”, in addition to conversion rate optimization, it also includes CPC advertising optimization, multi-ad group optimization, listing optimization, inventory management and other fields. Only by combining data analysis with business experience can operators finally achieve “fine operation”.