In the store overview of Data Zongheng, you can see the store ranking, store operation status, store core indicators, and global distribution data of store visitors. Through these data, you can easily find problems in the store.
First, let’s understand the store rankings. From the store rankings, you can know the hierarchical ranking of your store in the transaction volume of the industry in the last 30 days in a timely manner. There are five levels of transaction stratification. This store is on the fourth level, and the 30-day payment amount exceeds 57% of the same level. This shows that there are many people who are better than our store. We want to upgrade the store to the fifth level. Levels require a lot of effort.
The following store ranking is the store operating situation data. In the store operating situation, let’s first understand the GMV board. GMV (Gross Merchandise Volume) means the total transaction volume. Here you can check the last 7 days and 30 days. The transaction data of days or customized time allows us to clearly understand the GMV situation of the store. In Figure 8-5, we can see the payment amount, number of visitors, purchase rate, customer unit price and other data of the entire store in the last 30 days. There are also prompts for improvement or decrease under the data. We can see the payment of this store. The amount and number of visitors have increased a lot compared to the previous period, while the purchase rate and customer price have dropped. For details, you can click on the “question mark” mark behind the data to see which links have dropped.
If you want to increase the purchase rate, you can optimize the product details page of the store, or delete spam words that are not related to the product, products with traffic but often no orders, products with low conversion rates, etc. Thereby increasing the overall purchase rate of the store. To increase the unit price per customer, you can optimize the associated template and combine it with marketing to encourage buyers to buy more products. Finally, data interpretation tells us that the transaction volume and number of visitors have increased a lot compared to the previous period. If the purchase rate and customer unit price are increased, it will definitely reach a higher level. The wireless data under the whole store data is the sales of mobile terminals. The analysis method is the same as above, so I won’t introduce it in detail.
There is also a country and platform distribution and trend board below the store operating status GMV board. Here you can view the traffic (UV) and transaction (GMV) trends by country and platform. Click the circle on the left to view it. Various data for a certain country or platform. In Figure 8-6, we can see that the GMV of this store is on an upward trend. If there is no problem with the store, it will be fine if it continues.
Let’s take a look at the third module of the store profile, the product core indicator analysis. In the store core indicator analysis, we can see the store’s exposure, number of visitors, and number of paying buyers at a specific time. Other core indicators, you can also check other core indicators to view relevant data. In the data, we see that the number of exposures of the store, the number of paying buyers, and the number of visitors in the last 30 days have all increased, but only the refund amount has dropped by 35%, indicating that There are fewer and fewer buyers refunding, so it is worthwhile for us to continue to maintain this and continue to optimize and improve to further reduce the refund rate. If the refund amount data increases, it means that more and more buyers are refunding money. We need to analyze why buyers refund money? After finding the reasons, find ways to solve them and reduce the refund rate. In addition, we also need to pay attention to the number of buyers placing orders and the number of paying buyers. If the number of orders placed and the number of payments are far different, it means that the successful payment order rate of our store is low. At this time, what we have to do is to urge those who have not Pay successful buyers to increase the store’s successful payment rate.
After understanding these data, let’s take a look at the global distribution function of store visitors. Through the global distribution function of store access, we can see which countries the store’s visitors come from. The proportion of Russian visitors in Figure 8-8 is The most, accounting for 27% of the entire store, followed by Brazil with 12% and the United States with 8%. With this data, we can know the geographical distribution of buyers and deeply understand customer customs and habits, and then develop targeted products that customers like. We can even focus on marketing to these countries, such as free shipping to these countries, to attract more orders. Improve conversion rates.