5 steps to teach you how to warn users about churn and effectively recall them

In user operations , in addition to the important issue of attracting new users, what is more important in the later stage is how to retain users; analyze multiple data to find the main reasons for user loss and take corresponding actions.

1. Pay attention to your lost users

The main tasks of user operations include: user acquisition, user activation, user retention, user payment, and user recommendation, which is the main content of the AARRR model. We try our best to improve user contribution, activity, and loyalty.

However, the AARRR model pays more attention to attracting new users and improving user value, and is more suitable for the relatively rough stage of the product's wild growth period; but when the product reaches the maturity stage or even the decline stage, when users no longer use the product, any value enhancement work will be of no avail, and the high customer acquisition costs will be difficult to recover as users leave, especially in an era when Internet traffic has become stock operations and private domain traffic.

Therefore, user churn prevention operations play an extremely important role in user operations. This time I will simply share with you the operational ideas and methods for user churn. Don’t say goodbye to lost users easily!

2. When to Care About Churn

All products need to pay attention to user churn, but the priorities are different.

User growth also depends on the product's life cycle. The product life cycle theory divides products into four stages: introduction, growth, maturity, and decline. Different stages have different user operation focuses. In the early stages of the product, the main focus is on user acquisition and retention, while attention and investment in user churn are mainly in the maturity stage.

We are a financial management platform, and currently we only operate existing users (in the maturity-decline stage), so we will pay more attention to the loss of users, and the recall of lost users is more critical.

Large companies have a large user base and a stock of product users. They can achieve stable growth and long-term retention by relying on their own brand and the spread of old users, and are basically in a period of long-term growth.

Products in the mature stage have a large number of users, are relatively mature and have a stable experience, and provide better support for user operations. Investing in user churn warning at this stage can more easily achieve positive input-output; of course, if operational resources are sufficient, it is still recommended to conduct user churn prevention operations earlier.

3. Loss warning settings

After users have been silent for a long time or even completely lost, the input-output ratio of intervention will be very low. The correct way to deal with it is to establish a complete loss warning mechanism, identify users at risk of loss in a timely manner, intervene and guide, and maximize user retention.

The general prevention mechanism can be built in the following five steps:

• Defining churned users: What kind of users are churned users?
• Analyze the signs of churn: characteristics of churned users and their behavior before churn.
• Establish an early warning mechanism: monitor data and identify potential lost users.
• Lost user stratification: stratify lost users and formulate differentiated strategies to recall them.
• Conduct intervention guidance: Intervene based on user characteristics and reasons for churn.

We define lost users through two indicators: time and key actions. That is, how long the user has not performed key actions. For example, the key actions on our platform are withdrawal and investment. The length of time is mainly divided into six levels, ranging from 3 days to 120 days (refer to normal user behavior). This was done when we built the label system, which helps us reach and recall users in a targeted manner.

For example, we define that if there is no investment for 7 days after withdrawal and the assets are less than 30%, it is considered partial loss, which has reached the warning trigger.

The judgment of the length of time requires specific data analysis based on product and user characteristics. We can check from Umeng or other tracking platforms how often users log in on average, how long they log in each time, and the frequency of investment withdrawals (especially withdrawals upon maturity and investment behavior).

Analyzing the signs of churn behavior is a prerequisite for identifying churned users in advance. Here, I directly classify churned users into partial churn and total churn (based on the two dimensions of amount and time respectively), and divide them into user levels for refined operations.

The purpose of establishing an early warning mechanism is mainly to prevent further loss of users. By identifying the behavioral signs of users who have already lost, a complete labeling system (updated daily) is established to promptly identify users at risk of loss and trigger the system (for example, automatically push small discounts before large withdrawals to retain users).

Intervention and guidance means timely intervention after identifying users at risk of churn; targeted intervention is carried out based on user characteristics and reasons for churn. Common intervention methods include SMS outreach, preferential guidance, event rewards, etc., so that users can use the product again in a timely manner instead of directly churn; the churn intervention of major products is now relatively mature. If you pay more attention to the recall notifications of Taobao, funds, Du Xiaoman, JD Finance, etc., you will be able to discover the basic intervention methods for users at risk of churn.

4. Recalling lost users

Many immature platforms do not have a churn warning mechanism. Once a user becomes a real churn user, the cost-effectiveness of recalling the churned user is low. However, users are our assets and we cannot give up easily.

Establish various churn warnings and a complete labeling system, followed by detailed user recall and AB testing. The common recall method is SMS/activity push.

• Pre-lost users: The user withdrawal page (withdrawal success page) uses copywriting and event discounts to recover users;
• For some lost users: establish AB testing, reach users by adding SMS/push (activity discounts, change copywriting), and monitor data;
• Completely lost users: treat them as new users and recall them via SMS (redirect card and coupon push to reach users);
• Users who withdraw large amounts of cash: Customer service will call out to understand the reasons for the withdrawal and provide them with more attractive special benefits;

Many times, it is difficult to accurately classify the types of user churn, so a general recall method must also exist, but the content and frequency must be controlled; the retention of new users is very important. For example, when we go to Baidu to invest in banking products, they will give you cash coupons and interest rate coupons (some will even give you coupons when they leave); because for these new users, their first experience is very important, and it is what operations need to focus on.

Good retention of new users will lead to an increase in overall retained users and avoid wasting customer acquisition costs.

V. Analysis of recall effect

Review our goals: Increase user lifetime value and reduce churn rate.

The innovative redirection of cards and coupons saw an increase of 116% in investment and 57% in card and coupon usage in the month of official launch.

Based on comprehensive data, users are divided into different levels. The wake-up rate increased by about 90% in the second month after launch, and the average investment amount per person increased by 37%.

VI. Conclusion

From the very beginning we must pay attention to the retention of new users, because only by raising the sheep well can we better attract more sheep.

After we have the data, we analyze the user portraits, conduct label management, member level management, establish a comprehensive user churn warning mechanism, set up targeted recall actions, conduct data analysis, user interviews, and pay attention to details, which will eventually pay off.

The above is just my personal sharing, welcome to communicate.

Author: Youth Weichun

Source: Youth Weichun