User activation, as a key link in the user growth process, plays an important role in connecting the past and the future. It inherits the activation conversion after user acquisition, and determines the number and cost of acquiring effective users; it determines the space and difficulty of user retention, and affects the discovery and improvement of user life cycle value.

This time, we will systematically share with you the ideas and methods of user activation from multiple angles to help you grasp the key points of user activation and conversion, achieve efficient activation of new users, and make every new user feel at ease.

1. Define user activation and clarify activation direction

First, let’s define user activation. User activation is not the same as a user registering an account or logging into an APP. The definition of user activation varies for different types of products, but can be abstracted and defined as:

User activation is the aha moment when a user experiences a product and discovers its value to them for the first time.

After acquiring new users, guiding them to promptly discover and experience the value of the product can keep them active in the new user stage and achieve effective activation. Only in this way will there be an opportunity to allow users to experience the continued value of the product through subsequent retention operations, while contributing value to the product.

However, this definition of user activation is more based on the user’s subjective perspective, which is not operational for data-driven user growth operations. How can we determine whether the user experience has reached the aha moment? Discovered the value of the product? We redefine user activation from the perspective of user behavior.

User activation refers to a user completing a certain number of key behaviors in a product within a certain period of time.

This definition still refers to the user experiencing the aha moment and discovering the value of the product, and it can also be understood as the definition of the aha moment.

Among them, a certain period of time is the time window for user activation, which specifies the user activation time period for a specific product and is also the main operating period for user activation; a certain number of times refers to the number of times user activation behavior occurs, also known as the magic number, which is the data that focuses on user activation; key behavior refers to user activation behavior, and different products often have different key activation behaviors. For example, user activation on Tik Tok can be defined as a user viewing (activation behavior) more than 15 (magic number) short videos within 3 days (time window).

With this definition, we have a more guiding and operational direction in user activation. But how can we effectively unify the definition of user activation from the user's subjective perspective and the definition of user activation from the user's behavior perspective? Does a user's activation behavior a certain number of times really mean that they have discovered the value of the product? This requires us to accurately find users' quantifiable aha moments so that they can better reflect the value of the product.

2. Find the Aha Moment and Determine the Activation Goal

When users reach the Aha moment, they are activated. Accurately finding the Aha moment of users within the product is the ultimate goal of user activation. Guiding users to reach the Aha moment through various products or operations is the main task of user activation. So let’s first look at the big premise: how to find the aha moment for the product.

As mentioned above, the Ahaha Moment can be quantitatively defined as a key behavior that a user completes a certain number of times within a certain period of time. Using the ideas of hypothesis testing and data analysis, we can better find the aha moment by following the steps below:

1. List possible activation behaviors

2. Analyze and determine activation behavior

3. Determine the time window/magic number

4. Test to validate ahaha moments and iterate

Through these four steps, we can better find the aha moment and clarify the goals of user activation work. Let’s take a look at them in detail.

1. List possible activation behaviors

Based on product goals, value provided, business model, and combined with user analysis and research, multiple alternative activation behaviors are listed.

Before specifically listing possible activation behaviors, we need to clarify who the users of our product are? What needs of users does the product meet? How does the product meet user needs? What are the differentiated advantages compared to competing products? What is the ultimate goal of the product? At the same time, with the help of data analysis and user surveys, we can understand the key nodes and behaviors when users actually experience the value of the product when using the product.

Through two-way considerations on the product side and the user side, list 3-5 possible key activation behaviors. Taking Tik Tok as an example, general users mainly consume short video content, and possible activation behaviors include browsing/liking/following/commenting.

2. Analyze and determine activation behavior

After determining multiple possible activation behaviors, you need to further identify the unique key activation behavior and find the behavior that is most relevant to new user activation and retention. A common method to determine activation behavior is to monitor and analyze whether new users have performed this behavior within a certain period of time after joining the product, and the impact on subsequent retention. The behavior that has the most obvious impact on subsequent retention is often the final activation behavior.

3. Determine the time window/magic number

Once the unique activation behavior is identified, the specific time window and Rubik's Cube number need to be determined to complete the definition of the Ahaha moment. The time window and magic number influence each other and need to be considered comprehensively.

The time window is the main period of user activation and varies from product to product. The shorter the life cycle of a product, the shorter the activation cycle; the more frequently used a product is, the shorter the activation cycle. A more accurate way to determine the appropriate time window period is to analyze the main concentrated periods for retaining new users and the churn periods for losing new users.

The magic cube number is the optimal number of occurrences of the key behavior. Of course, the more times the key behavior occurs, the better. However, to determine the aha moment, it is necessary to find the number with the largest marginal utility, that is, the effect of adding this behavior once more on the subsequent retention of users begins to decrease. The number with the maximum marginal utility is generally the magic number. You can also choose the magic number before or after the maximum marginal utility number according to the actual situation.

For example, if a user performs a key behavior once, the subsequent retention rate is 10%; if it occurs twice, the retention rate is 20%; if it occurs three times, the retention rate is 45%; if it occurs four times, the retention rate is 50%; if it occurs five times, the retention rate is 52%. When the marginal utility increases from the third time to the fourth time, the marginal utility has begun to decrease, and the tangent slope of the retention rate curve begins to decrease, so three times is the number of times with the largest marginal utility.

4. Test to validate aha moments and iterate

After determining the activation behavior, time window, and magic number, we have clearly defined the product’s Aha Moment. However, the Aha Moment determined at this time is based on assumptions and data analysis, and needs to be verified in the product through specific test experiments to verify that pushing users to reach the Aha Moment can improve user activation retention data and ultimately obtain an Aha Moment with reliability.

After that, the Ahaha Moment data still needs to be monitored. As time goes by, product function iterations and changes in user structure may still lead to changes in Ahaha Moments.

Once we identify the aha moment, we have a goal for user activation. The destination is clear, and we also need to provide users with navigation maps and transportation to help them reach the aha moment better and faster.

3. Sort out the user process and find activation clues

After clarifying the direction and goals of user activation, we need to sort out the user process, monitor the data funnel, and discover clues to user activation, which is also the entry point for our user activation intervention. The specific steps are as follows:

1. Sort out the new user activation process

2. Monitor and analyze process funnel data

3. Analyze funnel data to find clues

1. Sort out the new user activation process

There are many paths for new user activation, and we need to monitor the main activation processes as much as possible. Taking the final activation state as the end point, trace the user behavior process forward, record each key node, and trace back to the starting point when the user first enters and uses the product.

In this way, we will generally find multiple process paths between the end point of the activation state and the starting point of the first use of the product, and then determine 2-3 main paths through the path data. The user flow paths that are only taken by very few users can be ignored. As shown in the figure below, we can focus mainly on process A and process C. Process B can be given appropriate attention, but it should not be the focus of intervention.

2. Monitor and analyze process funnel data

Build a user activation process funnel data dashboard to monitor and analyze the data of the main activation process. The main monitoring data includes:

Number of participants : number of new users in each process

Conversion rate : conversion rate data between every two steps and between the starting point and the end point

Conversion time : the conversion time interval between every two steps and between the starting point and the end point

By monitoring funnel data, we can have a more comprehensive and systematic understanding of the activation status of users when they reach the aha moment in each process.

3. Analyze funnel data to find clues

After having a main activation process and process funnel data, use different process funnel data to find entry points for intervening in user activation.

Which process has the highest conversion rate? Which step has the lowest conversion rate/highest dropout rate? Which step has the longest conversion time interval? Through these questions, we can discover important clues for user activation. Is there a large room for improvement in the link with the lowest conversion rate, or should we just cut this link out? Is the conversion time too long because the user has forgotten? Or is it difficult to operate? These are our entry points for subsequent optimization of user activation.

The activation funnel is our main way to find activation leads. In addition, click heat maps (the distribution and number of times users click on areas on the page), track checks (detailed usage processes of specific users), user interviews (direct communication with users), etc. are all tools and methods for finding activation clues. Based on product and user characteristics, we can flexibly choose to use them to find the entry point for user activation intervention.

4. Choose activation methods to influence user behavior

After finding the entry point for user activation, we need to choose appropriate activation methods to intervene and influence user behavior at key stages, so that they can experience the aha moment better and faster and reach the activated state. Here we can use Fogg's behavior model to think about specific means:

Fogg Behavior Model: Behavior = Motivation * Ability * Trigger

Fogg's behavioral model theory comes from the Stanford Persuasive Technology Laboratory and is named after the director of the laboratory. It analyzes the causes and psychology of user behavior, that is, the generation of user behavior requires a combination of motivation, ability and trigger. The stronger the motivation, the greater the ability and the more effective the trigger, the better it can enable users to complete the specified behavior.

In user activation, we can provide targeted guidance and intervention based on motivation, ability, and trigger to enable users to generate activated behaviors.

Enhance user motivation (Behavior)

To enhance user motivation, on the one hand, it is necessary to meet user needs and utilize their intrinsic motivation to make users more willing to complete the behavior. On the other hand, it is necessary to increase additional rewards and enhance their external motivation so that users have to complete the behavior.

Based on user needs and internal motivations, we can create a more friendly product experience and new user guidance to help users better use the core functions of the product, arouse user interest and discover the value of the product. For example, the powerful recommendation algorithm is a powerful tool for Tik Tok to activate users, allowing users to see personalized videos that match their interests.

The forms of external motivation are more diverse. Red envelopes for new users are the most common way to increase user motivation. The sense of gain and sunk costs of red envelopes can increase the activation and retention of new users. Free trial classes for online education products, free purchases for new users of e-commerce products, and various gamification tasks all use similar ideas, guiding users to perform key behaviors in the activation process through rewards.

Improving user capabilities

It is difficult to directly improve users’ ability to complete designated behaviors. Some product guidance/user education content can be regarded as a way to improve user capabilities, but another way to improve user capabilities is to reduce the resistance of users to using the product, so that users can better complete designated behaviors under the condition of “limited capabilities”.

Simplifying key activation processes, cutting out unnecessary information and steps, reducing user selection behaviors, and maintaining continuity between previous and subsequent content are all common approaches to reducing user resistance. The gradually evolving login methods of major apps are a typical example of reducing user resistance, from registering an account first and then logging in with a password, to logging in with a mobile phone verification code, and now one-click login with a mobile phone number, simplifying the process to the extreme.

Perform effective triggering (Trigger)

Trigger refers to the stimulating action that guides user behavior, which is divided into internal trigger and external trigger. Internal trigger is a more autonomous behavior of the user, which requires a certain demand intensity and habit cultivation, and is difficult to achieve in the short term. Therefore, in actual user activation, external triggers are more often used to reach users through various channels and methods, reminding them to use the product and perform activation actions. SMS/Push and other push strategies are common external triggers. You can also use a sense of urgency and scarcity to get users to take quick action.

Clarify the direction, determine the goals, discover clues, influence behavior, and use top-down user activation ideas and methods, which are suitable for user activation work for most products. Nowadays, it is becoming increasingly difficult to acquire users for Internet products, and the cost of acquiring customers is getting higher and higher. The relatively inefficient and extensive "attracting new users" will eventually be replaced by the more effective and refined "attracting activation". Only activated users are valuable users. I think this will be a consensus among everyone.

Author: Wu Yijiu

Source: Wu Yijiu