• What is user churn?
• Reducing user loss is a top priority for businesses.
• Ten strategies for reducing user churn.
Our previous “cohort analysis method is introduced by comparing different period of specific indicators for time window, and today” A/B testing “is introduced by different groups of users on the same time window for comparing different versions of the reaction.
According to the statistics, 79 percent of smartphone users will check their phones within 15 minutes of waking up in the morning.A 2011 study by a university found that the average person watches 34 times a day.However, recent figures from the industry have been much higher – almost 150 times.We have to admit, we’re addicted.Faced with this high-tech product, we’re not addicted to it, and we’re at least obsessive-compulsive.We can’t wait to see WeChat, weibo, access to mobile phone taobao, jingdong, was just going to have a crush on for a few minutes, an hour to find their own fingers slide is still on the phone screen page.This desire may be with us all day, but it is seldom perceived.
APP operators know the importance of push messages to improve user engagement.The good news is that the user engagement will improve significantly, and the number of users will be greatly reduced.
How do we get the push messages to the desired effect?APP operators must pay close attention to the behavior of users, have a clear preference for users’ interests, and push the content of interest to different groups of users at the right time.The perfect push messages are valuable to the user, which can help the product to improve the user experience and increase the user’s liking.
With the advent of the era of big data, data mining has become more and more important.Front end point buried as a more mature data access method is widely used.Currently buried point is divided into two ways, and will come with no points.Sets a buried point is easy to understand, is called the SDK API, in the code inserts buried point related code, user behavior acquisition.Because we are in development projects, buried point are manually, every business needs change to buried point everywhere, and no burial code, which does not need to be manually inserted into the code, just prior to related configuration, the SDK automatically collect user behavior, avoided because of the change of demand, and buried the great degree error causes such as to bury some heavy and complicated work.This paper mainly introduces the technical implementation of codeless capture technology.
Emerging industries, like sharing a bike or like payment of the ancient and the industry, the new is always going on, new, retained, active, transformation, erosion, activation is operation of the whole process, such as new is the first step, the new do bad, the product is lack of the soul, the soul is the user and no user, to fine the perfect products are meaningless.New is so important, as a new era of qualified operation, how should we pull new users?
Every product manager knows that data analysis is important, but can you give a clear answer to both of these questions?
1. What is data analysis?
2. Why is data analysis so important?
It doesn’t matter if you don’t know the answer, because this article is about to answer it from the following aspects:
1. What is data analysis?
2. Relevant concepts of data analysis
3. How to conduct data analysis?
4. How to measure and collect data?
5. How to do data analysis report?
6. The relationship between data analysis and products
What is Apache NiFi? NiFi’s website explains: “an easy-to-use, powerful, reliable data processing and distribution system.” Popular, namely the Apache NiFi is an easy to use, powerful and reliable data processing and distribution system, its designed for the data stream, it supports highly configurable indicator diagram of data routing, transformation and mediation logic system.
To NiFi can describe more clearly, through NiFi architecture to do a brief introduction to below, as shown in the figure below.
Our APP marketers are always better at getting more and more people to use our products and become our users. But how do you keep them when you have them? It may not be hard for a new app to attract hundreds of millions of users. But it’s never easy to keep these users and increase the number of users to 100 million.
Although users retention needs us to spend a long time to complete the work, we can still take some measures to improve it in the short term and can improve user activity, such as some marketing activities or according to the user’s usage of history to their push precise related news. This is a good way to interact with the users to let them participate, users can be obtained from these activities and news to get more valuable things. Therefore, the app retention rate will be increased.
For example, for a bookkeeping app, an effective user should be logged in every day to add his new income or spending. For an operator’s app, an effective user may be logging in once a month, charging a fee, or ordering additional traffic packets. Therefore, user engagement has no uniform quantifiable definition standard, but it is possible to form the standard of vertical industry. For Banks, for example, start times the average of 1.7 times the user is a reasonable value (the value come from Cobub’s long-term observations, Cobub is a domestic open source mobile application of statistical analysis tools).
Engagement is not like page views (PV), visitors (UV), users pay or conversion rate these indicators as easy to measure, not a data statistical analysis tools to directly reflect product user engagement. However, ignoring user engagement is very dangerous.