From quantifying user behavior to influencing behavior-retention rates

With the mobile game as a whole fiery, now see too much data, too much information, many times we admire and admire the success of others, we always put this industry reached so-called consensus of some data to illustrate the problem. Because we believe that data is strong evidence, and can explain the strength. However, too many times, because of the more external atmosphere, so that in some cases can not see their next clear direction. For example, the retention rate issue today.

About retention rates, including calculation criteria and use methods, but careful people should understand that those are just the primary stages, because even if you know what the retention rate is, you will find that you still do not know what to do?

The reason is that you think everyone is talking, so I'm talking about it. Many times, seen a lot of people are asking, this category of games, benchmarks is how much, on the one hand is really useful, because you see the gap, on the other hand, but found that even though they know the gap, but still do not know how to compensate for the gap, how to solve the problem.

The biggest dilemma with retention rates is that even if you know you have a gap, you still can't find a way to solve the problem. For example, we all know that our next day retention, 7th retention level is not very high, need to further improve, but often we can not find the method, many times, we may go back through the continuous game experience to find problems, but now many people already know through the retention rate to analyze the problem of experience. However, the success criteria that drive the user experience decision and make sense must be the standard that can be clearly bound to the user's behavior, and these behaviors must be the behaviors that can be influenced by the design. However, we have seen that the next day retention rate and the 7th retention rate, which are now explored, do not capture behavior accurately, and help us to complete the design and thus influence behavior.

So, we're going to look for behaviors behind retention rates that need to be quantifiable and designed to affect behavior.

Because these factors enable us through the design can be improved, and these improvements, will necessarily correspond to a certain quantitative basis, because just mentioned, only such criteria is the existence of value, but also can really solve the problem through data analysis, in other words, It's just a simple retention index. We are not able to find these problems more clearly, or more often, only by experiencing and feeling to solve the problem, in this case, the data analysis does not play its due role.

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From quantifying user behavior to influencing behavior-retention rates