How to design a user activation growth strategy from 0 to 1?

When working on growth, everyone pays close attention to attracting new customers. But if you calculate the conversion rate of each step in the new user acquisition funnel, you will often come to a very bad conclusion: more than 95% of the acquired users are lost. In this case, the primary task of a growth person is not to spend hundreds of thousands or even millions of dollars to attract new customers and expand channels, but to solve the problem from the root and improve the overall funnel conversion rate. So the questions we should think about are:

• Why do users stay and why do they leave?
• What functions are the remaining users using, and where do the lost users go?

User activation is the first step after acquiring new users. Its goal is to allow users to experience the value of the product for the first time and complete the conversion of key behaviors, thereby increasing the motivation to stay and reducing the possibility of churn.

1. Clarify the goals of the new user activation phase

The ultimate goal of new user activation is to turn new users into old users who continue to use the product and gain long-term value from it. Therefore, new user activation is particularly important in the entire process of user retention. The activation moment for a new user is when that new user first experiences the value of your product. Represents the user's emotional expression towards the product. The product leaves a strong enough first impression on the user, making the user feel pleasantly surprised, thus laying the foundation for continued use of the product in the future.

The activation moment usually occurs when a user first uses a product. Whether a user experiences this moment determines whether the user will become a retained user or a lost user of the product. The activation moment is determined by analyzing the behavioral differences between active users and churned users, and analyzing the core user needs behind these behavioral differences. Through product strategies or operational means, try to meet the needs of these new users as much as possible, thereby triggering these users to reach the activation moment.

1.1 Thinking model at the activation moment:

1.2 Assumptions of activation time:

• Products have long-term value and significance for users. The concrete manifestation is that the product has achieved PMF.
• Through key behaviors, new users can quickly and easily feel the long-term value that the product brings to them.
• New users who perceive the long-term value of a product are more likely to become retained users.

1.3 The strategic nature of the activation moment:

Through simplified behavioral data, simulate the moment when users first gain the core value of the product.

Simplified behavior:

• In actual business, new user activation may be triggered by a combination of multiple user behaviors. Users with different characteristics may have different behaviors, perceive different product values, and have different activation time nodes.
• The activation moment is to find a behavior that is most likely to make most new users feel the value of the product. This helps find a clear behavioral goal for new user activation strategies.

Simulation value:

• The activation plan must allow users to feel the value of the product and benefit from it.
• The strategy to induce users to reach the activation moment cannot be to simply and mechanically force users to perform certain actions, but it must also simulate the moment when users obtain product value as much as possible.

2. How to find the activation moment of new users

You may subconsciously think that the activation moment is when the user logs in or registers. In reality, many products use user login and registration as the standard for activation rate and activity rate. But these two behaviors may not necessarily make users feel the value of the product. Therefore, it’s easy to get sidetracked if you focus only on login and registration. So what behavior can make most users feel the value of the product? How to find this behavior?

2.1 Find the steps for new user activation time:

Step 1: Propose alternative actions:

1. Identify the long-term value of your product;
2. Find the user paths and user behaviors that can most quickly help new users realize the long-term value of the product when they start using the product;
3. According to the above method, several alternative behaviors are proposed that are most likely to reach the activation moment of the new user.

Commonly used alternative behavioral analysis methods:

(1) Through key issue analysis:

• Who: Who is the user?
• What: What needs do users want to solve with this product?
• Why: Why did the user make this request?
• Vs: What other ways can users use to solve this need?

(2) Through user research and analysis: Compare interview records of users with different behavioral characteristics to discover the most important value of the product to users and find alternative activation behaviors.

• Long-term active users: What keeps users using the app for a long time?
• Users who leave quickly after registering: Why do they leave quickly?
• New users who actively use the app after registration: What actions did they take and what profound experiences did they have?

Case: Du APP

Step 2: Find the activation behavior:

1. Evaluate how quickly activation occurs and find the new user activation cycle.
2. Compare the early retention curves and find the behavior that is most strongly correlated with early retention during the new user activation period as the activation behavior.

Principles for determining the new user activation cycle:

• The higher the frequency of usage, the faster new users will gain value from the product.
• The shorter the life cycle, the faster new users can derive value from your product.
• Through data analysis, the new user activation cycle is determined based on the time window when the early activation behavior of the vast majority of new users occurs.

Examples:

Suppose this is the retention rate of new users of a video editing product in the first 30 days:

1) Draw the new user retention curves for different user groups:

2) Compare the retention curves to find the behavior that is most correlated with retention:

1. The retention curves of "no special effects elements used within 3 days of installation" and "no text special effects used within 3 days of installation" are basically the same, and are not of reference value in the current case;
2. The user retention curve of "using special effect elements within 3 days of installation" is more different than "using text special effects within 3 days of installation". Therefore, it is preliminarily determined that "using special effect elements within 3 days of installation" is more strongly correlated with retention and is more likely to represent an Aha moment.

Summary: The behavior that is most likely to represent an Aha moment is: "Using special effects elements within 3 days of installation"

Step 3: Calculate the frequency of behavior:

Reasons for calculating behavior frequency:

• For some products, activation only needs to be done once. For example, the first order from an e-commerce company. However, the activation behavior of some products needs to be repeated multiple times to ensure that new users feel the value of the product, such as watching short videos.
• In theory, the more repetitions you have, the greater the improvement in retention. However, in the new user activation stage, time is of priority, and it is not realistic to ask users to repeat too many times. Therefore, we hope to ensure that users get value by finding the optimal number of activation times while not burdening them.

Common methods for calculating behavior frequency: Maximum marginal utility method

1. Draw a distribution graph of the number of activation behaviors of new users on the first day.
2. Analyze the relationship between the number of activation behaviors on the first day and the retention rate on the next day.
3. Find the number of activation behaviors corresponding to the point with the largest marginal benefit of retention.

Examples:

For video editing products, we collect user data for users who used “special effects elements” on the first day:

Analyze the relationship between the number of activation behaviors on the first day and the retention rate on the next day: Plot the retention rate on the next day corresponding to the number of activation behaviors on the first day

Find the number of activation behaviors corresponding to the point with the largest marginal benefit of retention: the inflection point of retention rate is the number of times with the largest marginal benefit

3. Identify new user activation leads

3.1 Activation Funnel:

Determine the link with the highest churn rate in the new user activation funnel through quantitative analysis. Design corresponding product operation growth strategies for this link. The following is a brief analysis of how to identify activation leads through the new user activation funnel:

Step 1: Clarify activation indicators:

• New user activation rate = the ratio of new users reaching activation time within a certain period of time
• It can quantitatively measure the activation moment and is also the North Star metric for new user activation.

Step 2: Sort out the new user flow: Record the entire new user experience from beginning to end.

• New user activation link funnel: from channel acquisition -> product download/access -> registration -> complete activation behavior.
• New user activation product funnel: product is opened for the first time -> registration is completed -> activation behavior is completed.

Step 3: Build an activation funnel:

Supporting behaviors: Users must complete these behaviors to reach the activation moment, but these behaviors do not allow users to obtain core value.

Configuration principles for supported behaviors:

• Simplify: The more complicated the steps before reaching the activation moment, the higher the chance of user loss. Therefore, the fewer unnecessary support behaviors, the better, allowing users to reach the activation moment more quickly. For example, after TikTok is introduced into the product, the first step is to browse short videos instead of the registration process.
• Weigh the pros and cons: Although a few support behaviors delay the user's activation moment, they have long-term advantages. For example, when entering the product for the first time, the user is prompted to enable push permissions on the mobile phone.

Step 4: Analyze data and find clues

Based on the steps of the new user activation path, we can propose the following thoughts:

• Can unnecessary steps be removed?
• Is it possible to adjust the order?

Based on the churn rate analysis of the new user activation path, the following questions can be raised:

• What are the possible reasons for the high churn rate?
• Through path analysis, we can understand what the user’s real path is.
• By activating funnel segmentation, can we understand whether the churn rates of different segments are different?
• Understand the user activation speed through interval analysis of the activation funnel?
• What are the reasons behind this through user research?
• Use click heatmaps to understand what elements users click first?

3.2 Excitement Index:

When new users first discover and try a product, they often feel a sense of "excitement" about trying something new. A product’s activation flow and interaction design can raise or lower user excitement. Excitement Index: It is a measure that uses qualitative analysis to understand the experience of new users and roughly assess the user's excitement level. Through this criterion, it is possible to find elements that bring positive or negative emotions to the user experience. Let’s take a quick look at how to use the new user excitement index to identify activation leads:

Step one: Sort out the user process.

• Document the entire new user experience from start to finish.

Step 2: Determine the initial excitement index.

• The initial excitement index of different channel sources is different.

Step 3: Evaluate the impact of each step on the index:

• Rough estimate; simulate users going through the entire activation process and rate the user's excitement index. 0 is the lowest score and 100 is the highest score, and each element may add or subtract points.
• User scoring: Recruit target users, let them go through the entire process, score each step, and record the reasons for the scores. The average score was calculated and the excitement index was obtained.

Step 4: Find opportunities to increase excitement:

• Make the experience consistent by removing elements that reduce the index, adding elements that increase it, or changing the order of steps.

Step 5: Regularly re-evaluate your new user onboarding process.

• Because as the product continues to iterate and optimize, the functional design and interaction will change accordingly. And users will also change as the product changes. Therefore, it is particularly important to regularly re-evaluate the new user onboarding process.

Author: Yang Sanji

Source: Yang Sanji