"Experience" my understanding of user growth "new users"

Estimated reading time ：8min

Reading suggestions ： This article is the methodology summarized in daily work , It's not long , Suggest 「 Collection 」 Oh .

Solve the pain ： How the product is designed , It can improve the stickiness of new users ？ And the role of data students .

00

preface

User life cycle , It can be divided into six stages ： Potential customer period 、 New user period 、 Growing period 、 mature period 、 A recession 、 Loss period . In the previous post , Little fire dragon shared with you 「 Potential customer period 」 Data analysis involves , Interested students can punch the blue part . This article will write about daily work 「 New user period 」 Data support and implementation involved .

The new user serves as the water inlet of the product user pool , It determines the trend of large market users . In recent years, , With the gradual decline of Internet dividends , The customer acquisition cost of the product has also gradually increased , In this context , Good service to new users has become an important issue for major manufacturers , And enhance retention , It is an important result of good user body feeling .

below , Little fire dragon as a consumer , Analyze what features of the product can make users stay .

01

New users' psychological exploration

Little fire dragon appeals ： Some time ago, the Spring Festival , Nothing to do at home , Want to exercise , However, due to the low outdoor temperature , So I downloaded a Keep Bodybuilding APP, Exercise at home .

▼ Before applying the software

In the download APP Before , I will see what software is available on the market according to my own demands , Can match my needs .Keep Of Slogan「 Self discipline gives me freedom 」 It's very attractive to me , And it's also for people like me , Software designed by players who don't have time to go to the gym , So I decided to download to try .

The core of the product

• Products need to extract core values , Help users match in a short time .
• Clearly tonal Slogan Will play a good Bonus , Improve the quality of products .

▼ In application software

When I open Keep, After selecting the privacy agreement, etc , There are new user guides , Because I haven't used it before APP, So this guide can help me get started quickly . Then there is a series of rolling irons , When I finish a course , Will give me a medal of sport , And increase the sports experience , I feel a great sense of accomplishment . After class , Some sports suits will also be pushed for training , I am also interested in , I bought a sports Bracelet inside .

The core of the product

• The core value of products should be guided , Let users feel when they apply for the first time .
• A perfect user growth system is very important in the whole user life cycle .
• Help users from 「 Single demand 」 towards 「 Diverse needs 」 shift , Reduce user fatigue .

▼ After applying the software

Postganglionic , Because of the busy work , Neglecting exercise . But often receive Keep Exercise of classmates Push, I always do sports after work .

The core of the product

• Push from time to time , Maintain information exchanges with users .
• Keep emotional contact with users , Let users have a sense of dependence on the product .

The above is a user application APP Simple psychoanalysis . Then some data partners may ask , What role does data play ？ In fact, all three stages are involved , But the exploration on how to improve the stickiness of new users , Mainly focused on 「 In application software 」 Stage , Next, we will expand layer by layer .

02

Explore key behaviors that affect retention

In the process of new users using the product , There may be a function that matches the original intention of the user application , So that users can rely on the product , This function is called 「 Cool point function 」, That is to say, it is often mentioned in the use increase 「AHA Moment」. So how do we find this through data 「 Key behaviors 」, Thus through certain guidance , Let more users survive .

Mining of key behaviors , It can be done by 「 Quantitative mining 」 and 「 Qualitative mining 」 A combination of ways .

▼ Quantitative mining

We quantify key behaviors , The aim is to find out 「 Whether to apply this function 」 And 「 User retention 」 The relationship between , The stronger the positive correlation is, the more important the application of functions is to the retention and improvement of users , The more you try to guide users to experience . There are three ways , You can refer to ：

Mode one ： Whether to apply the retained variance comparison of functions .

Mode two ： Functions and retained Pearson The size of correlation coefficient .

Perason The correlation coefficient

It's a linear correlation coefficient , Is the most commonly used correlation coefficient . Write it down as r, Used to reflect two variables X and Y The degree of linear correlation ,r The value is between -1 To 1 Between , The greater the absolute value, the stronger the correlation .

Mode three ： Build a classification model

Function as a feature 、 Whether to retain as label, Judge the impact of function on retention according to the contribution of model features （ Random forest 、GBDT Methods such as ）.

The conclusion of the above three methods will not be much different , The first way is best understood .

▼ Qualitative mining

In addition to quantitative mining , Product students sometimes pass user questionnaires 、 Pay to recruit users to explore users Aha moment , There will be no more explanation here .

See here , I wonder if there are any friends who have such doubts , Or to Keep give an example ： By exploring 「 Buy equipment 」 Users of 「 Retain 」 Generally far higher than the market , Can we draw a direct conclusion 「 Buy equipment 」 Yes 「 Retain 」 There is a significant positive impact ？

The answer is No , Because there may be a 「 Cause and effect 」. It is the purchase of equipment that changes the user retention ; Or the retention of these users is on the high side , They happen to be interested in these devices . And our quantitative mining above , The solution is 「 Related issues 」 Instead of 「 Cause and effect 」.

Is the content we have done above meaningless ？

The answer is No , Let's analyze . If 「 Buy equipment 」 It can improve user retention , Then we can directly deduce that it is a 「 Key behaviors 」; If 「 Buy equipment 」 User retention itself is on the high side , At least we can explain that this function has the characteristics of high retention of users , Here we need to make a judgment based on the product .

If you infer that this function is helpful for user retention , Can be guided , Increase users' favor for this function , So as to improve the retention of users . Bear in mind ： It is difficult to change the basic demands of users , But you can try to guide the expansion .

for instance

Small fire dragon application Keep The basic demand of is just exercise , At first, he pushed me equipment , I'm not interested at all , But with the deepening of exercise , It is gradually found that it is necessary to buy some equipment . After a workout , The product push aroused my interest , So I have an impulse to buy .

03

Exploration of key behavior application times

When you find the key behavior , The next step is to explore the impact of the number of triggers of key behaviors on retention , That is to say, it is often mentioned in the use increase 「Magic Number（ Magic number ）」.

The relationship between the number of function applications and retention can be used , utilize 「 The law of the elbow 」 Find the turning point . Of course , Sometimes the inflection point may not be very clear . In this case , It needs to be based on the understanding of the product , Choose the right number of times .

04

Guide process exploration

After analyzing the product 「 Key behaviors 」 as well as 「 Number of applications 」 after , It also needs to be guided through the product , Effectively guide users to these functions naturally . The user-oriented design in the early stage should follow three principles ：

1、 Reduce obstacles ： Move the product registration step backward , Let users try the product first 、 Remove redundant steps 、 Hide too much non essential information 、 Avoid cold starts .

2、 Content focus ： Guide users to focus on key behaviors , Avoid distractions .

3、 Personal Tailor ： Let users choose interests and preferences , Give different directions according to the user's purpose .

As a data analysis student , Analyze according to the new user's guidance funnel , combination AB Experiment to improve the guidance scheme .

05

Four elements of designing products for new users

Finally, I would like to summarize the four elements that little fire dragon believes are necessary to design products for new users ：

1、 Enhance application power ： Put the core value of the product first , Let users feel as soon as possible , Provide personalized content and quality experience , Form a user incentive system .

2、 Reduce application costs ： Reduce redundant steps in the user activation process , Postpone the registration process , Avoid cold start , Through the mining of key behaviors , Give the user proper guidance .

3、 Increase daily rewards ： Give users a sense of gain , Use red envelopes and other ways to attract users to generate active behavior .

4、 Form a closed-loop user growth system ： Enhance the interaction between products and users , Let users leave assets on the product , Increase the time and energy users spend on products , Increase sunk costs for new users .

The above is the content sharing of this issue