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This article mainly explains "how to understand the aspects involved in the analysis of user behavior". Interested friends may wish to take a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn how to understand the aspects involved in the analysis of user behavior.

We often talk about the data operation of Internet products, and the most important thing in the data operation is the user's behavior data, because only by really mining the user's behavior can we make products that are more attractive to users. that is, to do a good job of user behavior analysis. Now everyone is talking about big data analysis and data mining, in fact, also includes user behavior analysis. Traditional user behavior analysis generally refers to PV, UV, bounce rate, user access depth, user stay time and so on. In fact, these indicators are mainly used as statistics. If we really want to guide products and business, we should have more refined analysis, that is, user behavior fine analysis. For example, we have made an information product, and the click rate of users is there, but how do we know whether users like the content of a certain channel? at this time, it is necessary to make a more detailed analysis of the stay time, comment frequency and comment content of multi-users in the article, otherwise the click rate alone can not explain the quality of the content at all. So, what aspects are involved in the analysis of user behavior?

First of all, the traditional user behavior analysis has evolved into fine analysis. In traditional user behavior analysis, we usually think that as long as a user opens APP, he or she is an active user on this day, and today's new user is considered a retained user as long as he starts APP the next day. Now, we can do more detailed analysis of users' behavior. For example, we have made an Internet reading APP product. If a user opens APP and does not browse an article in it, but generates a zombie user by means of a registration machine, then we can set a rule to define what is an active user, that is, a user who has viewed at least one article today is an active user. For example, many traditional users can be regarded as a user as long as they generate a piece of data in the database, but many Internet products now require a real-name system, that is, if a user's authentication does not meet the requirements, it cannot be regarded as a valid user, such as real-name authentication and mobile phone authentication on social products. Therefore, refined user behavior analysis will make more and more Internet products, especially those companies that rely on false data to obtain investment, more and more disappointed, because the refined analysis of user behavior will make a product healthier and healthier. More and more high quality.

Secondly, the fine analysis of user behavior focuses on user portraits. We do user behavior analysis, although there are great differences in different methods, but the ultimate goal is the same, that is to restore the real behavior and true appearance of users through the data generated by user behavior. That is to say, based on the dimensions of the user's behavior on the Internet product and the time and frequency of the user's behavior, we can restore the user's authenticity as accurately as possible, and construct a complete and fine user profile through the behavior data. Combine the user's behavior data with the user's characteristic data to form a user profile, instead of using statistical tools to get the data.

Thirdly, the accurate analysis of user behavior determines the market of the product. User behavior is one of the effective means to guide product market evaluation, that is, we can judge whether a product meets the market demand through the accurate analysis of user behavior. For example, there is a vertical e-commerce platform that has just been launched, and we can judge whether it is necessary to continue to devote energy to this project by the user's behavior. We can accurately analyze the user behavior data by how many users browse, how many users actually click on the product link, how many users stay on the product page for a long time, and how many users actually buy and pay. It is easy to see whether this TV platform meets the needs of users and whether it is a little attractive to users. Through these analyses, we can determine whether the market space of this product is large enough.

In addition, user behavior analysis needs to be carried out from multiple dimensions. With the development of information science and Internet technology, especially the wide application of data mining technology, the analysis of users' behavior is becoming more and more deep. for example, we can analyze a user's click behavior from many dimensions. including time, space, in which time can have access time, access frequency, stay time, interaction time and other dimensions. In space, there can be regional distribution, access sources, user groups and other dimensions, that is to say, the more dimensions of the analysis of user behavior, the more accurate user information can be excavated, and then the more we can understand the needs of users, and promote the continuous enrichment and improvement of products.

Nowadays, the demographic dividend period has passed, and there are more and more ways to promote Internet products, and the field is becoming more and more vertical. coupled with the fact that homogenization competition directly leads to higher customer acquisition costs, no matter from the perspective of marketers or companies, ROI is being evaluated. In addition to looking at the number of users, we also need to look at the quality of users, and to evaluate the quality of users, we need to do accurate analysis based on user behavior in order to evaluate more accurately.

At this point, I believe you have a deeper understanding of "how to understand the aspects involved in the analysis of user behavior". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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