Do you know what a user growth experiment is? Do you know what the user growth experiment is doing? How does it work? In response to these doubts, the author will use Douyin as an example to talk about what the user growth experiment is bulk sms service doing. Abstract: The core workflow of user growth (UG) was briefly introduced before: analyzing data → forming hypothesis → experimental verification, which roughly described what each step was doing. Now use a case that everyone may have noticed to try to reverse and reproduce the relevant working scene, and try to explain clearly what the UG experiment is doing. Case introduction: Some users may notice when bulk sms service swiping Douyin that the share button becomes their friend's avatar after 2 playbacks, while some users still use the regular share icon.
By the way, this is a simple UG experiment. The links involved in the experiment are similar, we might as well take this example as a representative, mainly bulk sms service talk about: Why do this experiment; Design and distribution of experiments; experiment analysis; Experimental value refinement. The case focuses on what should be done at each step. The specific values are fabricated and not important. Any similarity is purely coincidental. Figure 1 User interface of experimental and control groups 1 Why do this experiment I just borrowed this case, and the following expressions are mainly used to reverse and reproduce from a bystander perspective. 1.1 Focus on strategic goals first bulk sms service Why did Douyin issue this strategy? It is not difficult to see that the direct purpose is to increase the proportion of users who click the share button (sharing rate). Whether replacing the "
Share Button" with the most frequently shared "Friend Avatar" can increase the sharing rate requires experiments to verify. 1.2 What is the purpose of increasing the sharing rate? I have learned some experience: the interaction rate of the user bulk sms service group (the proportion of users who like and comment) is positively related to its retention rate . It is well understood from the product logic: if users interact, they will receive feedback, and continuous interaction will generate stickiness. Suppose you have few WeChat friends and you haven't received any messages, will bulk sms service you still open them often? Assuming that every time you send a circle of friends, no one likes and comments, it will greatly weaken the enthusiasm of the circle. Therefore, when Douyin does this,