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Common indicators and meanings in big data analysis, I believe that many inexperienced people are helpless about this, so this article summarizes the causes and solutions of the problem, through this article I hope you can solve this problem.

There are quite specific terms in the field of data analysis. As a small partner who wants to enter the field of data analysis, it is very important to understand the common indicators and meanings in data analysis. It is not only conducive to the smooth development of business, but also very useful for monitoring, analysis and mining potential of business. It needs to be explained that the indicator definitions of each enterprise are similar.

User data metrics

1. Add new users every day

How many new users are added to the product every day? Function: Measure and judge the promotion effect of channels.

2. Active users:

Active users are divided into daily active users (DAU), weekly active users (WAU), and monthly active users (MAU).

3. Activity rate

Active Rate = Active Users/Total Users (Daily, Weekly, Monthly)

4. Retention rate

Retention: New users promoted through channels may gradually lose some users after a period of time, so the remaining users are called retention. Role: Evaluate the stickiness of product features to users.

Retention rate: the number of users who used the product on Day N among the new users on Day 1/the number of new users on Day 1 (Retention rate on the next day N=2, Retention rate on Day 7 N=7, Retention rate on Day 30 N=30).

Behavioral data indicators

PV (Page View) page views

It refers to the total number of users visiting a website or a page in a certain period of time. It is usually used to measure the traffic effect brought by an article or an activity. It is also an important indicator to evaluate the daily traffic data of the website. PV can be accumulated repeatedly, based on user visits to the website, and recalculated every time the user refreshes.

UV(Unique Visitor)

This refers to the total number of users who come to the website or page. This user is independent. The same user visits the website at different times and is only counted as an independent visitor. It will not be accumulated repeatedly. Usually, the number of cookies on the PC side is used as the statistical basis.

3. Visit

A user comes to a website through an external link, and the process from when the user comes to the website to when the user closes the page in the browser counts as a visit. Visits can be accumulated repeatedly, for example, I open a website and close it again, and then reopen it, which counts as two visits.

4. Home Page

A page that serves as a home directory for a website and is also the starting point for a website. It is usually the home page of the website.

5. Landing Page

It refers to the first page that users come to the website from external links and jump directly to. For example, a friend sent me a Taobao link introducing a hot T-shirt. I clicked on the meeting and jumped directly to the page introducing the T-shirt, rather than one of Taobao's many other pages. This page introducing the T-shirt can be counted as a landing page.

6. Bounce Rate

It refers to the behavior that users come to the website through links and leave the website without any interaction on the current page. This is considered as adding a "bounce" to this page. The bounce rate is generally aimed at a certain page of the website. bounce rate = number of users who bounce on this page/PV.

7. Withdrawal rate

Usually for a particular page. After a user visits a page of a website, all pages related to this website are closed from the browser, even if a "exit" is added to this page. Exit rate = number of users exiting on this page/PV.

8. Click

Generally speaking, for paid advertisements, it refers to the number of times a user clicks on a link, page or banner, which can be accumulated repeatedly. For example, I saw a news link on the PC side, clicked it in and watched it for a while, and then clicked it in and watched it again after a while, which counted as two clicks for my contribution to this news.

9. avr.time Average length of stay

The average length of time a page has been visited by users, usually used to measure the quality of a page's content. avr.time= number of visitors/total length of stay of users.

10. CTR click rate

The ratio of the number of times an ad, Banner, or URL is clicked to the total number of times it is viewed. It is generally used to assess the drainage effect of advertising. CTR= number of clicks/number of times seen by users.

11. Conversion rate

It refers to the number of times a user completes a set conversion link and the percentage of the total number of sessions. It is usually used to evaluate the quality of a conversion link. If the conversion rate is low, it is urgent to optimize the conversion link. Conversion Rate = Number of Converted Sessions/Total Sessions.

Commodity data indicators

Return On Investment (ROI)

Reflecting the relationship between input and output, measuring whether my investment value is worth it and how much value it can give me (not just profit), this is from the perspective of investment or long-term business. The formula is: Return on Investment (ROI)= Annual Profit or Annual Average Profit/Total Investment ×100%, which is usually used to evaluate the value of an enterprise for a certain activity. A high ROI indicates that the project value is high.

2. Total amount

Including: total turnover (GMV), turnover volume.

Total turnover: i.e. journal, including sales amount, cancelled order amount, rejected order amount and returned order amount

Number of transactions: that is, the number of goods placed

3. Commodities

Including: hot-selling goods, high-praise goods, bad-rated goods, goods refer to measuring which goods are good and which are not good from the perspective of commodities, focusing on promotion or optimization.

After reading the above contents, do you master the methods of common indicators and meanings in big data analysis? If you still want to learn more skills or want to know more related content, welcome to pay attention to the industry information channel, thank you for reading!

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