1. Average number of pages browsed per person

Each customer has an independent IP address, which means that there are multiple IP values ​​for every number of customers who come to the store today. The total number of product pages browsed by customers in the store is the page views, or PV value.

The work of retaining customers in the store can affect the PV value, while the work of attracting customers outside the store affects the IP value. If a customer only browses one product page in an online store, the possibility that he decides to buy is very small. If a customer browses multiple product pages in a store continuously, the possibility that he decides to buy is very high.

When the ratio of the IP value to the PV value of an online store is 1:1, the store will not have any business. When the IP value to the PV value of an online store is around 1:5, the store will have a stable transaction volume, but the sales volume will not be large. When the IP value to the PV value of an online store is around 1:10 or higher, the transaction volume of such a store is very high, and no matter what products are sold, the business will be very good.

From this, we can see that if you want to improve the business of the store, you need to find a way to increase the ratio of the store's IP to PV, and this needs to be achieved through in-store promotion.

2. Average page dwell time

Just like the average number of pages browsed per person, average page dwell time can also be used to determine whether a store can retain customers. Due to the different nature of each industry, the time that customers stay in the store in each industry varies greatly, so there is no way to provide a specific time value for judgment. It is recommended to use the average stay time of customers in the store over a period of time as the base number and record the sales volume during this period. Then compare the new data later to know whether the store has moved forward or backward. The longer the average page stay time of customers, the better the store's customer retention work is

3. Store backend data analysis

Through "Quantum Hengdao-Store Experience", you can get the store's daily and weekly traffic peaks. You can arrange the shelf time of the goods in the store according to the obtained traffic peak value. Reasonable shelf time will bring many customers to the store.

Through the background data, you can also know which products are the most popular in the store, which can serve as a guide for future purchases.

There are many types of background data in the store, and each type of data has its own analysis value. The results of the analysis can serve as a guide for the store's future customer retention and customer attraction work.