What data do you need to look at for data analysis of competing products, how to get the data of competing products, and the data interface of competing products

In the era of big data, we must understand data analysis, which will have a great effect on the operation of the store. Analyzing the data of our own store can better find the advantages and disadvantages of our store, and analyze the data of competing products. The dregs, but there will be many small partners wondering, where should the data of competing products look? You can go against your intentions: juzivtu can also provide an interface to analyze the data of competing products. Then we can analyze it from these two aspects: 1. Customer loss of competing products, 2. Search loss of competing products, you need to look at the specific data, then Next, I will explain in detail for everyone:
First, the flow source channel opponent's flow, through which channels are they coming from, and whether we also operate these channels! No, let’s see if we can join in too! For example, competing products are driven by through trains, but we don’t have them. Then you have to open it. If people search well, and you search very few visitors, then you have to catch up. More importantly, it depends on the drainage of these channels. Ability, that is, the absolute value of daily data! Through the analysis of traffic channels, we can know where our store is failing, and we can really find the traffic entrance.
Second, natural search keyword analysis If through the first channel analysis, we know that our main weakness lies in the mobile search channel, then at this time we need to further analyze the drainage situation of the mobile search! So, the first thing to do is to analyze the drainage words and deal words! Analyzing the drainage words is to avoid our drainage "blind spots"-high-traffic keywords that others have, but we do not. The analysis of transaction words is to determine the conversion rate. If the conversion rate of others is much higher than your own, then In terms of volume, we will be beaten up.
3. Analysis of the core data of a single product First of all, let's look at these data, our daily turnover, number of visitors, customer unit price, conversion rate, UV value, collection plus purchase rate, etc. Then analyze the formula "sales = impression volume click rate conversion rate per customer unit price" to find the real reason for the poor store data. For example, through analysis, we found that the click rate of the opponent's main image is much higher than that of our own main image, because visitors = showClick through rate! The higher the click-through rate, the more traffic will be obtained under the same display situation, and the more traffic will be obtained, and the transaction will naturally be more when the conversion is OK. The key is that the performance of any data can also determine whether our data is a virtuous circle or a vicious circle.