Why are there two ways to define "new user"?

There are two ways to define " new users ". One way is to define it as the number of new users who open the app within a period of time. This is new users in a broad sense. Another way is to define it as the number of new users who have performed "key behaviors" within a period of time, such as shopping/speaking/recharging. Growth hackers pay more attention to the second type of "new users".

In the traditional sense, we can use the download and installation volume of each electronic market and official website as the number of new users (of course, this is very inaccurate), or we can use the number of new users who open the APP within a period of time as the new users. A more rigorous way is to use newly registered users as the new users.

Usually, we call new users who open the APP but are not registered visitors. In the user life cycle, they are also called potential customers. The subsequent stages correspond to novice, growth, maturity, and loss. In the growth hacker's AARRR model, the user life cycle is divided into five key stages: acquiring users, increasing activity, improving retention, generating revenue, and self-propagation. A new user opening the APP means acquiring a new user.

Since new users who open the APP can be counted as new users, why should we consider registered users as a statistical indicator of "new users"?

We call registered users activated users. Whether it is the user life cycle model or the AARRR model, from potential customers to newcomers, or from acquiring users to increasing activity, user registration is a key behavior.

User registration represents the user's initial recognition of the product experience and the primary expression of product demand. At the same time, the operator obtains part of the user's information, such as email, mobile phone and even more personal identity information, and has more ways to guide the user's subsequent behavior, such as churn awakening.

Taking "registered users" as a consideration indicator for new users represents a shift from "quantity statistics" to "quality statistics" in the definition of operational indicators.

The number of "new registered users" actually represents the insight into user behavior. User registration requires multiple steps such as opening the APP - entering the registration page - filling in information - submitting registration information. Users who take action for the product are actually users who recognize and have demand for the product.

In refined operations, we pay more attention to "user quality" rather than quantity. When we count the number of new users, we will also count the new user acquisition effect of each channel, such as the number of new users in each e-marketplace, the number of new users in each advertising channel, and the number of new users in each activity. This corresponds to the control of operation and promotion costs.

Traditionally, we evaluate the quality of a promotion channel by looking at how many new customers it brings, how much exposure it has, how much investment it has made, and how to calculate the ROI of the promotion. Between the channel with a single customer acquisition cost of 10 yuan and the channel with a single customer acquisition cost of 20 yuan, we think the first channel is better.

But through the analysis of "quality statistics", we can draw the following conclusions:

Channel A has a customer acquisition cost of 10 yuan, 100 new users, a total cost of 1,000 yuan, 20% of which are registered users, and the cost of a single registered user is 50 yuan;

Channel B’s customer acquisition cost is 20 yuan, with 100 new users and a cumulative expenditure of 2,000 yuan. Registered users account for 40%, and the cost of a single registered user is 50 yuan.

From this conclusion, we can see that the cost per registered user of Channel A and Channel B is the same, but in one promotion, Channel B brought twice as many registered users as Channel A, saving operational manpower and improving promotion efficiency. Channel B is better than Channel A.

In refined operations, we pay more attention to "effective users". Registered users are only one manifestation of effective users. When measuring the number of "new users", we should pay more attention to users' key behaviors.

Different products have different definitions of "key behaviors". For example, the "key behavior" of e-commerce products is users placing orders to purchase, the "key behavior" of gaming products is users recharging, and the "key behavior" of social products is users leaving messages to interact.

Of course, this is the core key behavior. The participation rate of a certain event can also be used as the "key behavior" of event promotion and conversion users, such as receiving coupons, participating in theme interactions, etc., to evaluate the quality of new users.

The definition of "key behaviors" varies in different stages of the product. The cold start stage focuses more on the number of users who generate "core behaviors" and develop into seed users. The user growth stage focuses on the number of users with "participating behaviors", such as registration and logging in for three consecutive days. The user retention stage focuses on the number of users with "retained behaviors", such as logging in for three consecutive days after being added for 7 days.

The above definition of "new users" in refined operations is actually a simple user stratification based on the subsequent behaviors of new users. Users who meet the "key indicators" of the current operation stage are regarded as effective new users and are also the key users of subsequent operations.

After defining the "new user" indicator, the new user acquisition behavior is no longer just about downloads and opens, but rather optimization around core indicators . For example, taking registration as an indicator, it is necessary to optimize the registration process experience by observing the user's registration behavior path.

Source: Zhugeio Data Coach ( zhugeio1 )