Common data indicators

Daily Active Users (DAU): The number of active devices per day
Weekly Active Users (WAU): The number of active devices per week
Daily New Users (DNU): The average number of new users per day in a week, calculated as: the number of new devices in a week (without duplicates) divided by the number of days in a natural week
Peak Concurrent Users (PCU): The highest number of active devices in a week
Monthly Active Users (MAU): The number of active devices in a month (without duplicates)
Activity (DAU/MAU): Reflects the overall user stickiness and measures the overlap of daily active users during the period.

Daily/weekly/monthly new users
Registration conversion rate: the conversion from activation to registration.
DNU ratio: the ratio of new users to active users, which can be used to measure the health of the product.

Retention Rate = Users Still Using / Total Initial User Count.

The next day retention rate: The proportion of new users who successfully restart the application the next day.

7-Day Retention Rate: The proportion of new users who successfully restart the application on the 7th day. Experienced a complete experience cycle, have the opportunity to become loyal users.

30-day retention rate: The percentage of new users who successfully launch the app again on the 30th day. After 1-2 version iterations, it can be used as a basis for the quality of the revision.

Facebook has proposed the 4:2:1 theory, where the next-day retention can reach 40%, 7-day retention can reach 20%, and 30-day retention can reach 10%. This is a quite good retention indicator.

Total usage duration: The total duration of all usage from app launch to end within a certain statistical period (without deduplication). Average usage duration/single usage duration/new user duration old user duration/time interval... Usage duration related indicators are also important indicators for measuring product activity and product quality.

Returning users: users who did not launch the APP last week but launched it this week;
Continuously active n-week users: active users who have launched the APP at least once a week for n consecutive weeks;
Important users: users who have been continuously active for 4 weeks or more;
Continuously active users: users who have been continuously active for 1 week or more;
Lost users: users who have not launched the APP for n consecutive weeks (1 week or more, but no more than 2 weeks). Lost rate, return rate, etc.
User composition indicators are used to analyze the composition of registered users, which helps understand the health of active users through the structure of new and old users.The definition of important, returning, and lost users is different for each company, and can be used to monitor the health of users by setting up return and loss alerts based on product business needs.

GMV is definitely greater than actual sales,
Often reported using GMV to show the scale of the platform.

ARPU=Total Revenue / GMV / Payment UV.

Each time a user visits a page, it is recorded 1 time,
Multiple visits, cumulative visits

A visit to a website is counted as one visitor for an IP address.

Within a fixed period, the same client is counted only once.

Conversion Rate = (Number of Conversions / Number of Clicks) * 100%

The definition of lost users varies according to the different types of products.

Focus on active users, but also pay attention to important features on the product. Such as collection, like, comment, etc., these features are related to the development of the product and the depth of user use.

The key indicator for evaluating whether a landing page is attractive to users

The high bounce rate may be due to the product/activity itself not being attractive enough,
or it may be that this type of user is not the target audience for the product.

Exit Rate = Number of Exits on the Current Page / Total Visits in the Session * 100%

Exit rate reflects the attraction to users,
If the exit percentage is very high,
It means that users only browsed a few pages and left

The total duration from the start to the end of a device's usage within a specific time period.

Analyze the average usage time per person, average usage time per time, and single usage time to measure the stickiness of user product landing, and also serve as a reference for measuring activity and product quality

The number of times users open the application within a certain time period.
Focus on the average number of launches per person, combined with usage time for analysis.

The time difference between the last time the app was used and the time it was used again.

Use frequency distribution to observe the stickiness of the application to users and the depth of the operational content.

The proportion of users willing to pay among all users

The retention rate of the revenue period

The return rate is a risk indicator, and the lower the return rate, the better.