01

In the short term, we can understand the retention after the user has a preliminary understanding of the product, which means that after the product has been downloaded, it is not deleted immediately or deleted in the next two days.
New users in the app will enter directly after the download is complete understanding of the product stage, this stage, the product main function interface, if the product itself nothing particularly conspicuous window (which can be understood as liao point), or hooked users at once, the possibility of losing customers is very big, after all, most users only early adopters, loss of this kind of problem, the general intelligence (algorithm), or select the content of the type of recommended products have an advantage, information of the class, the short video, the mall or in a class, live class, can use the height of the hot spot content recommended the use of the hook for most users.
I recently in an attempt to understand Tik Tok, for example, he has a big advantage determines the app short-term retention rates are higher than other similar short video, for three reasons, first: Tik Tok itself attribute and user product positioning determines his music video is more characteristic;Second: the high quality of video is determined by the shooting threshold, high standard and the advantage of video processing.Thirdly, the selection mechanism of the home page makes the selection threshold of the user lower, so we can open the APP to play the short video, and the quality is quite high from the view of my days.(I haven’t found the content of the recommendation algorithm on the front page, but in terms of content quality, there should be a large manual intervention mechanism).

Tik Tok the three characteristic determines the user after open the app, can quickly immersed in a short video in high quality, also is the hook users can quickly, that I feel is better than well quickly, quickly in a short video on the choice of, is a very easy thing to do.You recall a boring afternoon when you wanted to see a good movie to see the tangle and ridicule of the movie process.
For content products with distinctive features such as no shaking, they can start from another Angle.According to the 2016 mobile information industry subdivision report released by the headline, today’s headline entertainment interest accounts for 68.29% of the total platform, accounting for the first place.The second most important social information was 67.29 percent, and the third was the funny category, accounting for 46.56 percent.That is to say, it is only a collection of these three points, so the retention rate in the short term will be extremely high for early adopters.
Of course to a content type products, generally USES a strong visual and interactive forms, that is to say, adopt the user can see understand product focus, the use of the product characteristics, let users can easily to fit in is the rapid formation of the product is not low quality, the product function looks quite good first impressions.
It also helps to understand why a good newbie guide is very important for many new products, which is a quick way for users to quickly learn about the product.Novice guidance may include not only the use of products but also the core highlights of the product (including ideas such as craftsmanship, high quality, etc.).

02

For the medium term, more appropriate content and more comfortable functional use become more important.Any one thing, we can from jing period (or early adopters) gradually transition to the peaceful period, when we are accustomed to most of the product function, the function of the product do more delicate, more convenient, for instance, learn more about the current user, recommendation algorithm is more accurate;For example, it’s easier to operate, and to change the original three-step clicks into one step, much like we use a computer for a long time, many functions we tend to use keyboard shortcuts instead of mouse.For example, provide a more personalized visual solution, app for design style, which means that this is a good step from the product to the use.
Netease cloud music song reviews module, this in itself is not a very need to function, but as a function of the icing on the cake effect is very good, a lot of top comments directly led to the user’s mood, strengthen the appeal of the song itself.

Further forward, providing more interesting content even if it is associated with a weak core function.Netease cloud music “friends” module, I found that I was unconscious spent a lot of time in the above, there is a short interesting video, wacky GIF animation, good music, but also some small celebrity gossip, itself is the module with music there is not a direct relationship, but he from listening to music and the stars, in the form of a circle of friends (of course his recommendation mechanism not the circle of friends, but with a smart and hot recommended among them, the mechanism of cloud music, after all, friends are mostly weak relationship, and slightly different WeChat), as a cloud music modules, this I think is kept as middle can be for reference.

03

Say again for a long time, also is the senior user’s problems, when users accustomed to the content of the product and function, but there will be a “itch” stage, micro letter do again good, with one or two years later, you might think so, however, much more humorous jokes to see, you can often guess some routines, humor also becomes boring.Papi sauce do you still see it, in the words of a lot of net friend, those routines, besides the trill, he now has such problem, trill embarks from the short music video, that is to say a lot of video will in fixed rhythm of the music and the content, it’s decided to many of his video filming and editing routines are the same, I used a lot of depth around users said video repeat rate is too high, often can see a similar form, the novelty is gradually diminishing.
At this stage, generally three Zhang Daqi products offering, the first name is social, the second call user growth system, the third is called continuous operation stimulus (including form varied topics, hot spots, community).
Social good understanding, the reason we don’t give up WeChat, because it has a lot of our social relations, our concern is not WeChat, but the people on the WeChat, just there is no one product can do WeChat such strong relationship chain characteristics.
Live on yy, devoted to the stranger, a short video class well quickly, trill, diminishing in the freshness of the products, can not afford to build micro letter this strong relationship, weak but is still has a strong relationship between mining.
Live streaming or video, as a way of being lonely and boring, we can see some interesting strangers on the screen, and since it’s human, then nature has personality.
Then the be fond of of weak relationship can dig from the content into a personality like, this can be understood as a form similar to that of the AKB48, the difference is that maybe I was like your best work, later to become fans after I like you as a person’s personality and fun, then work is only part of your personality, in the later, you focus on the anchor may not need the content of the very bright eye, you will be more like, even thought he is true.
This is part of the deep mining of the social weakness of content products.
The growth system, in short, is “a few years after the work honors and some privileges and benefits”, which is not done in detail and expands very much.
Continuous operation stimulus, usually divided into two kinds of circumstances, information, media products tend to produce operation of controversial topics, subject content can often surprise, after all is not, subject to choose the good, may point continuously the following reply.
Mall products tend to make holiday, a double tenth, 618, belong to this category, of course, the continuing operations manufacturing festival belongs to the regularity of, also have a regularity, such as drops, worship for no reason to send coupons, give preferential.

04

Summary, although I said is short medium and long term retained, but the spring is not a specific time short, different users at different levels of products use, reflect individual users of short time might not have the same of the medium and long term process.That’s one thing.
2 it is, I said these products function must points successively, not likely parallel development at the same time, some retained function is, after all, three stages are applicable, just to say which stage the best results, the lower the yield, do the most efficient.
As a recent graduate of the college students, you tell him to high quality business top fortune 500 companies, dry, for him, there is no use, it is better to teach him how to improve the success rate of the interview is really.The same is true for retained solution policy usage.
So that’s a little bit of a little thought for retention, hopefully useful.

內容轉載自公眾號 油炸果子

Taking Tik Tok and Ease Cloud Music as An Example to Discover Different Requirements of the Three Stages of User Retention，首發于Cobub。

So in terms of operations, what is the same cohort?

In the same period, the group belongs to a subgroup of users, which refers to the group of users who have the characteristics of common behavior within the specified time.“Common behavior” refers to the similar behavior in a certain time period, which in addition to sort them out according to different time of new users, may be classified according to different behaviors, such as “in June 2017 for the first time to buy”, “on the second week of October, 2017 products began to reduce the use of frequency”, etc.
Note that the cluster analysis focuses on the differences between groups during the same phase of the customer’s life cycle.

Why is Cohort Analysis important?

In the process of product development, we usually measure product revenue and product user volume as the ultimate measure of success or failure of this product.There is no denying that these indicators are important, but they could not be used to measure the product’s success recently, and most likely will hide some issues which need our attention, such as user engagement has been falling, added in gradually slow, etc.On the analysis of user behavior in the process, we need more detailed measures, so that is better for us to accurately predict product development and by version iteration in a timely manner to product optimization and improvement.

Cohort Analysis is the key to improving the retention of APP users

The success of a product, it says, is not how many downloads it is, but how to keep losing users and how to recall them.
We can’t through downloads to determine the specific situation of the development of the APP, because beautiful download data will mislead us thought APP development is very healthy, but in fact, many users download is lost in a few days.Group analysis is the key to improve user retention.
case
For the first time, users of the APP were analyzed in the same time group and observed their retention for the next seven days.

17461 new users start the APP, for the first time in October 30, with 30.6% of people in these users on the first day to start again, the fourth day 12.2%, 7.9% on the seventh day, and this shows that at the time of the seventh day approximately once every 12 users only one active users.It also means we lose 92% of our users
We need to know which groups have better retention and analyze why.Have we launched a new marketing campaign on that day?Or offers promotions or discounts?Or new features that add video to the product?We can apply these successful strategies to other users to improve user activity and retention.We can also compare the retention of different time periods:

? The preservation of the new lads:

By comparing the different time groups, we can see four days, seven days and so on.These data can give us the key information about user login experience, product quality, user experience, and market demand for products.

? Long-term retention:

By looking at the number of days a group of users are returning to use the APP again, we can see the long-term retention of each cohort, rather than the remaining days of the new APP.
We can know where the user is out, and you can know what’s the feature of active users, what they are doing and so on the one hand, will help us in new quickly find target users, on the other hand we can also affect the new users, let them follow the same route, eventually become loyal users.

Cohort Analysis can help us monitor real user behavior, measure user value and develop targeted marketing programs in real time

For example, our operations team launched a 60-day welcome campaign in September to promote user growth through a series of discounts and offers.Through advertising and social media, we have thousands of users growing every day.Five months later, our user growth was very large, and the leader was very satisfied with the result of our activity.
On the face of it, we have achieved the goal of user growth.However, when we study cohort data, starting from the lifetime value of customers, we will find that new users welcome activities in activity 2 months after purchase rate continue to reduce, by contrast, activity before the new users such as users in August, in the activities of this five months purchase rate has been stable.

If we only measure our monthly gross income as a measure, we expect revenue growth to come only from the new influx of users.However, user group data following the launch of the activity shows that once the discount activity is over, revenue will decline.The decline in revenue proves that we have not expanded our loyal user base.
As shown above, through the cohort analysis we can real-time monitoring the real user behavior trend, otherwise, we will get wrong judgment because only analyze the overall data and make the wrong decision.By analyzing the behavioral differences of each cohort, we can develop targeted marketing programs.In this case, the operator needs to develop a new strategy to improve user engagement after two months of activity.

How to implement Cohort Analysis?

Start by defining business questions

Defining a business query is a prerequisite for the study of effective results.Business questions define business goals and research attempts to solve them.
Does the customer purchase conversion rate increase after we optimize the product?Is the user turnover rate reduced after the product improvement?We need to iterate and refine these questions to ensure that it is aligned with business objectives.

Define metrics based on business queries

If the purchase conversion rate and user retention rate are the key indicators to answer business questions, we want to understand the user turnover rate and the final purchase conversion rate from registration to completion of purchase.

Definition cohort

In the previous cases, the group was based on the user who purchased the account within a week of creating an account.In other cases, we can define a group in a different way, for example, a content APP that we might post within 24 hours of creating an account.

Analyze group data over the same period

We also in a cohort of typical form, for example, rows horizontally for natural number, longitudinal for every new clients, forms the internal is to calculate retention rate every day, usually the retention rate of lateral will stay some days later in a relatively stable state, we can see from the picture, keep stable in 5 days.This means that the users are stable.Otherwise, if the retention rate keeps going down, it’s going to go to zero someday.
Let’s look at the longitudinal retention data, and if a product is in healthy development, this data should be getting better and better.Obviously this product is not, the PM should constantly improve the product according to the historical data, improve the user experience, thus improve the retention rate!

Conclusion

Cohort Analysis in the same period will help us to analyze user behavior more deeply and reveal the problems covered by the overall measure.In the current situation where the marketing mode and the activity effect are changing, learning to use the same period group analysis can help us to predict the future income and product development trends.

You Still Don’t Know Cohort Analysis?，首發于Cobub。