Every day, we need to use data to diagnose the situation of the store. In daily life, we will come into contact with sales data, advertising data, store traffic data, etc. Today we will focus on the data on Amazon sales. What role does it play in our store operations?
1. Analyze Amazon sales data to find high-quality products in the store
Before explaining this case, let's first look at a formula:
Sales = Traffic * Conversion Rate * Average Customer Price
This formula is widely known in the e-commerce circle, and there are several variants. Everyone is keen on how to improve the various factors of the formula to ultimately achieve the goal of increasing sales. In particular, some courses focus on how to improve search rankings to gain higher traffic, etc. There are countless such courses.
In fact, for platforms like Amazon, when considering sellers, they focus more on the conversion rate factor. Amazon doesn’t care how much traffic you get, because all the traffic on the platform belongs to Amazon. No matter which product the traffic is assigned to, the total amount of traffic will not change. So from Amazon’s perspective, traffic is a quantitative rather than a variable. Amazon only cares about your conversion rate. In order to obtain higher GMV, Amazon’s choice is to give as much traffic as possible to products with high conversion rates.
2. Use Amazon sales data to track product promotion results and analyze product growth
Accurate analysis is rooted in complete data records. It is recommended that all sellers do a good job of data collection during the promotion process. The simplest way is to use an Excel spreadsheet to create a worksheet for each product and collect the following data every day: number of visitors, order volume, conversion rate (automatically calculated), transaction amount, category ranking, and main keyword ranking (3 to 5). In addition, you can create a chart in the table with time as the horizontal axis to draw the corresponding line graph.
As you collect more Amazon sales data, you will slowly discover that the data has some interesting characteristics.
1. Spiral upward characteristics: We found that the product traffic and transactions have a leap-like increase every week. For example, if the transactions in the first week are 2, 3, 3, 2, 4, 4, 5, then in the second week they will suddenly jump to a new height, such as: 9, 9, 8, 6, 8, 7, 8. By the third week, the number of transactions may jump to more than 10. The data shows a trend of a leap-like spiral upward on a weekly basis.
2. Consistency of promotion cycle: Excluding unexpected factors such as out-of-stock, review, certification, etc., the promotion cycle of a new product is generally about 6 to 8 weeks. After this, the data gradually stabilizes and will no longer show a spiral upward characteristic unless new promotion resources are invested.
3. Conversion rate stability: On the chart, the conversion rate will appear as a broken line that fluctuates around a fixed value. If the time period is long enough, you can also see a slight upward trend in the conversion rate.
This is the end of the knowledge about Amazon sales data in this issue. If you want to get more information about Amazon sales data, please pay attention and we will continue to answer you~
