Data analysis is a very important part of Amazon’s operation process and one of the essential skills for an excellent practitioner. By tracking the traffic and conversion of listings every day, you can better grasp the sales cycle. However, many operators will fall into inertial thinking, thinking that as long as they continue to increase traffic and conversion rate, they can achieve explosive sales. Although this view is not wrong, it is not correct. Because in actual optimization, traffic and conversion rate often have a relationship of increase and decrease. For example, compared with buyers searching for “office table”, buyers searching for “office tables for small spaces” have clearer purchasing needs and are more likely to facilitate transactions. However, there are more than 100,000 links under the search for “offictable”, and only 30,000 links under the search for “office tables for small spaces”: Through competition analysis, it can also be preliminarily judged that the traffic of “office table” is higher than that of “office tables for small spaces”. In addition, it is also necessary to make judgments based on the life cycle of the link. If the listing begins to enter the decline period, it is necessary to develop new products in time.
Another reason is that there is often a bottleneck in the conversion rate, and after exposure, click, browse, add to shopping cart, to purchase, traffic is lost at every step. What operators need to do is not only to analyze the source of traffic, but also to analyze the loss of traffic and deal with these problems in a targeted manner.
For general operators, the analysis of data provided by Amazon backend belongs to the basic operation operation. It is the type of listing data that can be obtained by Amazon backend.
Amazon does not provide data on exposure and collection under natural traffic, so the most valuable data that operators can see are the following.
1 Number of buyer visits (Visit/Sessions): Count the number of users who have browsed the sales page within 24 hours (based on Cookies). A computer client that visits the website is a visitor, which can be understood as UV.
2 Number of page views (PV): Within a certain statistical period, each time a user opens or refreshes a page, it is recorded once, and the page views are accumulated if the same page is opened or refreshed multiple times.
3 Buy button win rate: The percentage of page views of the product page that wins the buy button in the total number of product views, which can theoretically reach 100%.
In addition, there are also order product conversion rate, number of ordered products and sales of ordered products, which are all relatively common values. By downloading daily reports and summarizing them into a more complete analysis table, the traffic changes of listings can be effectively tracked.
The traffic and conversion rate of link A are both decreasing, but the buy button win rate is increasing. According to the observation of the link, it is found that the purchase button acquisition rate is increased due to FBA replenishment, but there are consecutive bad reviews, so the correct way to deal with it is not to push traffic, but to maintain the review.
For Amazon operations, there are always the following two seemingly irreconcilable views.
1 Traffic priority idea. Through the use of high-traffic keywords, off-site traffic diversion, low-price ranking and other methods, the listing exposure and traffic can be increased in a short period of time, and ultimately sales can be increased.
2 Conversion rate priority idea. By using precise long-tail keywords, optimizing pages and categories, etc., we can achieve a higher conversion rate and gradually and steadily increase sales.
The difference between these two approaches is actually due to the different understanding of user behavior. The former believes that buyers are more sensitive to rankings and prices, have a high degree of understanding of products, and are more likely to make purchasing decisions; the latter, on the contrary, needs to identify specific buyer groups, increase buyers’ desire to buy, and then monetize traffic.