Today, let’s talk about how to define user activation, and teach you 4 tricks to quickly define the user activation behavior of a product.
The first move: the behavior that proposes the possibility of user activation
This is an open exploration phase to define users. The main purpose is to clarify the long-term value of the product and find the fastest way for new users to feel the long-term value when they start using the product.
Then, according to the above method, several most likely new user activation behaviors are proposed.
Generally, the following two methods country email list can be used to initially list several potential user activation behaviors.
Method 1: Go through key questions
Who is the WHO user
What problems do WHAT users need to solve with this product?
Why are WHY users solving this problem?
Is there any other way for VS users to solve this problem?
The usage scenario is generally to find the long-term value of the product through key questions, and the behaviors required to experience these values, and infer what behaviors new users can complete in the short term.
Take the beauty camera as an example, let's set the formula.
who: female
what: take beautiful photos
why: let your friends see your beauty
vs: take pictures first, then P pictures
Possible Activation Behaviors:
Photograph
Use filters
share with friends
Which ones can be done quickly?
first 2.
Well, then we can preliminarily judge the possible user activation behavior when taking pictures and saving them after taking pictures.
Method 2: Through User Research
Simply put, it is to compare different user responses, find the most important value of the product to users, and find alternative activation behaviors.
The following different user personas can be surveyed.
Long-term most active users: why the product is valuable
Users who leave quickly after signing up: Why leave?
Active users after registration: why did they stay?
The usage scenarios are generally that if there are a large number of alternative behaviors, user research can help narrow down the number of alternative behaviors, which is especially important for products with multiple usage scenarios and functions.
Tactic 2: Identify the most critical user activation behaviors
Here are two steps to share with you.
Step 1: Find the activation period for new users and assess how quickly activation occurs.
Step 2: Compare the early retention curve and find out the behavior that the new user did or did not do during the activation period that had the greatest impact on early retention.
How to find out how long?
Principle 1: The higher the frequency of use, the faster the activation needs
The higher the frequency of use, the sooner new users expect to obtain value from the product, and the activation period for new users can be roughly judged based on the frequency of use.
Principle 2: The Shorter the Lifecycle, the Faster the Activation Needs
The shorter the life cycle, the sooner new users expect to get value from the product
Principle 3: Refer to actual data
Analyze real data on new users to see a real-time window of the vast majority of early activations
Example: Pull the time distribution of all users who have potential activation actions for the first time, and judge based on more than 80% of the behaviors
Assumption: Take the beauty camera as an example, suppose the beauty camera confirms that the first day is the activation period for new users, and the corresponding earliest retention period is the first 31 days.
So, how do you compare retention curves manually?
1) Collect retention data for the first 31 days of new users
2) Group users according to whether they have a certain behavior, and collect retained data
All new users
Use the filter on the first day
Photo taken on day 1
No pictures on day 1
3) Draw the first 31-day retention curve of different user groups
4) Compare the retention curve to find out whether there is this behavior, and the one with the largest retention difference
The bigger the gap, the more likely it is to represent an Aha moment.
Trick 3: Counting Magic Numbers
What are magic numbers?
The optimal number of times to find this key row through data analysis, aka the magic number.
However, not every product's magic number is the same.
For some activation behaviors, it is enough to do it only once, such as the acquiring of e-commerce.
Some activation behaviors need to be repeated many times to ensure that users feel the value, such as watching short videos.
In theory, the more repetitions, the greater the improvement in retention, but the activation time of new users is prioritized, and it is unrealistic for users to repeat multiple times.
Therefore, it is hoped that by finding the optimal number of times to activate an action, it is hoped to ensure that users gain value without burdening them.
Here is a short answer to introduce a common method, called the method of maximizing marginal utility.
Draw the distribution map of the number of activations of new users on the first day
Analyze the relationship between the number of first activations and the retention rate
Find the number of activation actions corresponding to the point with the largest retention marginal benefit (the inflection point of the retention rate, that is, the number of times with the largest marginal utility)
Take the number of times the beauty camera uses filters as an example.