Data Zongheng is a data product created by AliExpress based on the data in the platform. Sellers can select products for their stores based on the data provided by Data Zongheng, guide store operations, and make correct decisions.

First understand some industry terms:

(1) Search volume: the number of times a certain keyword is searched by buyers.

(2) Exposure: The number of times product information is seen by buyers on the AliExpress website

Buyers search through keywords and the information is displayed in the search results page, then Statistics enter exposure.

When buyers browse products through category navigation, and the information is displayed on the search results page, the exposure is counted

(3) Views: The product or store homepage is clicked by the buyer Number of views

(4) Number of visitors: The number of buyers who have visited the product or store.

(5) Number of regular visitors: The old visitors in the data aspect refer to the buyers who have visited AliExpress.

Tips: The buyers who have visited AliExpress are similar. Higher order rate than new visitors.

(6) Number of inquiries: the number of buyers who have contacted or have the intention to contact.

Buyers who have sent inquiries will be counted as the number of inquiries.

Buyers who have clicked the Send Inquiry button or Want Want button but failed to successfully send the inquiry are also included in the number of inquiries.

(7) Purchase rate: the ratio of the number of visitors/the number of buyers placing orders.

(8) Search index: The corresponding index obtained after data processing of the number of searches for the keyword in the selected industry and within the selected time range. The search index is not equal to the number of searches. The higher the index, the greater the search volume.

(9) Search popularity: The corresponding index obtained after data processing of the number of people searching for this keyword in the selected industry and within the selected time range. Search popularity is not equal to the number of searchers. The greater the popularity, the more searchers.

(10) Transaction index: The corresponding index obtained after data processing of the cumulative number of transaction orders in the selected industry and within the selected time range. The trading index is not equal to the trading volume. The higher the index, the greater the trading volume.

(11) Competition index: The competition index corresponding to the product word in the selected industry and within the selected time range. The larger the index, the more intense the competition.

The following is a detailed introduction to the process of product selection through data analysis. In fact, it is a process of first understanding the market and then making decisions. We need to know what is lacking in the market, which industries are less competitive, which products have greater demand from buyers, and our products are of good quality and low price relative to the market average. Of course, it is impossible for our products to meet so many conditions at the same time, but we will try our best to find such products. This is product selection.

The purpose of product selection: to ensure the success of promoting popular products.

The essence of business is to maximize profits. In the process of operation and promotion, you will always encounter various problems. Some products are easy to sell, some products are not easy to sell, and some products are difficult to sell in a short time. It can be made into a hit within a short period of time. Some products may never become a hit. What we hope is to make as many products as possible into a hit. This is the meaning of product selection.

Steps in product selection: data acquisition, data analysis, and competitiveness analysis.

1 Data acquisition: As the name suggests, it is to obtain the data we need. The more data we obtain to provide raw data for product selection, the higher the quality of the data itself, and the higher the quality of the product selection.

2 Data analysis: It is to process and analyze the data obtained previously. The more ingenious the processing method, the more ingenious the angle of analysis, the larger the amount of data involved, and the more accurate the conclusions drawn from the analysis can be. Provide a theoretical basis for product selection.

3 Competitiveness analysis: Based on the first two steps, we have a certain understanding of the market, and we need to consider the ultimate issue of product selection—are our products good enough? Which products are suitable? To create a hit product? This link is called competitiveness analysis and competitive product analysis.