7 key points to explain the strategy of recalling lost users

This article introduces the value of recalling lost users, the corresponding strategies and implementation paths for recalling them.

Before reading this article, please ask yourself three questions:

1. How much does it cost to acquire a new user on Double 11?
2. How many users were lost after Double 11?
3. Do you have any strategy to win back lost users?

Key points:

1. Find lost users in three steps

• ① Calculate based on brand user life cycle
• ② Combined with the brand product usage cycle/frequency
• ③Analyze the brand’s historical user activity peak period/loss peak period

2. Four methods to find out the reasons for user churn

Questionnaire survey, customer service summary, competitive product analysis, user portrait analysis

3. Lost customer recovery strategy - practical case study

Formulate lost user strategies, draw up a full process diagram for recalling lost users, and improve the daily report of lost user data

01 The value of recalling lost users

When it comes to lost users, many people will sigh in unison: despite having put a lot of effort into user retention, large-scale loss is still inevitable.

Many brands can only rely on new users and a small number of old users to maintain their active users. This process is extremely painful and can lead to the following problems:

1. The user group that generates profits is too small, and the product benefits are small
2. The cost of attracting new users continues to rise, and the total cost of users is getting higher and higher
3. The retention rate of old users is low, and there is no low-cost user base for product line expansion

Based on this, the value of recalling lost users is reflected:

value

• ① Increase the proportion of active brand users
• ② Extend the life cycle and increase profits
• ③ Reduce the total cost of large-scale users

02 Definition of Lost Users

Before we understand what a churned user is, we need to first have the concept of a pre-churned user. That is, before becoming a churned user, a user must first become a pre-churned user.

Therefore, the judgment of lost users should be divided into two categories: lost users and expected lost users.

1. Determination of lost users

How to use different indicators to determine lost users? Different categories of merchants have different selection priorities:

There are three key points in the numerical calculation of the indicators that determine whether a user has churned:

Of course, some categories of analysis only require one or two of these.

Different brands and different products will have different situations, so you must analyze and judge based on your own situation.

The specific calculation will be discussed in the case study shared later~

2. Determination of expected churn users

Before a user becomes a churned user, he or she will definitely show some abnormal behavior in advance. We define the users during this abnormal behavior period as pre-churned users. The specific determination of pre-churned users requires the following two points:

• ①Analysis indicators are abnormal
• ② Has not yet reached the user loss standard

For example: a decrease in payment amount, a decrease in online time, a decrease in the number of consultations, etc.

When key indicators drop significantly, you must sound the alarm. This is a user who may/is about to churn. Intercept him quickly to prevent the churn!

Usually, when the core indicator/process indicator data drops by 30%, users have entered the pre-churn stage.

The pre-churn stage is the stage with the lowest cost for recalling users and also the stage with the best effect.

03 Analysis of the causes of loss

Want to know what happened to the user and why he left? Go analyze your users! According to different lost users, we can conduct targeted loss reason analysis, mainly in the following four ways:

Note: The specific analysis logic will be explained in detail in the following cases

04 Design of flow chart for customer recall

User recall may not be effective just once, because the reasons for user loss are complex and diverse. It is very likely that the first recall does not hit the user's G-spot, or even fails to reach the user's field of vision. Therefore, it is necessary to switch angles and recall users multiple times through other methods and content.

The funnel model reflects not only the screening of values, but also the screening of communication methods. The communication efficiency of communication methods is also improving, and personalization is enhanced step by step.

From the perspective of user value, the first users to be reached are definitely the expected churn users, and the user base is wide, the investment cost is low, and the average user value is also low. As time goes on, the more accurate the users screened, the higher their value, and the investment cost and labor cost will naturally be higher.

The lost population goes from the first recall, the second recall, to the third recall. At each link in the process, there are corresponding lost user screening conditions, contact channels, and contact times. In this way, the overall loss of the lost recall will be very clear, and the operation of each link will be better controlled.

TIPS: High-value users must be retained in the private domain in the early stage. After retaining them in the private domain, have long-term and high-frequency contact with users, cultivate relationships with users on a daily basis, and the cost of communication will be lower when users tend to churn.

05 Communication content for lost users

After understanding the reasons for the loss of lost users and their needs, you can develop a targeted recall strategy. You must group lost users and make targeted recall content based on their needs:

See the following figure:

Combined with the recall flow chart, the communication content is mapped to each communication recall node in the process, which is a complete churn recall strategy.

06 Effect monitoring and strategy iteration

From the churn recall flow chart, we can see that for the same user, there will be a second, third, or even fourth recall, so the data of each recall needs to be recorded for the iteration and optimization of the solution.

The recall data records have the following key points:

1. Monitor the effectiveness data of each recall channel

For example: the corresponding groups, content, and recall effects of template message primary recall and SMS secondary recall

2. Compare and contrast test your content

By conducting AB tests on the same group of people to test the recall effects of different content communications, we can clearly know which type of content this group of people is more interested in and has better effects.

3. Pay attention to the frequency of communication

Based on the above, the first three communications with users should be at least 24 hours apart, and the subsequent communications should be about 7 days apart.

07 Case Practice-Fast Moving Consumer Goods Category Loss Recall

Take the fast-moving consumer goods category - snacks as an example:

1. Determination of lost users

The determination of lost users in the snack category can be simple and rough, based on the repurchase cycle, and the number of days without purchase to determine whether there is loss.

As shown in the figure:

From the data table above, we can see that the average purchasing cycle for snacks of this brand’s users is 25.76 days. If they do not repurchase after 25.7 days, the chance of loss is very high.

Based on the above analysis, we can conclude that: Lost users are defined as users who have not purchased for ≥ 26 days.

2. Determination of expected churn users

Pre-churn analysis indicators: average order value, member activity (check-in, interaction), number of consultations, etc.

For example, if there are three old customers in one year and the average M (average order value) is RMB 85, ​​then when the user purchases again in 26 days and the average order value is lower than 30% of the previous RMB 85, ​​it can be defined as a pre-churn user.

TIP: The decline rate of the analysis indicator can be selected based on actual conditions. The lower the decline rate, the more stringent the user churn warning is, and more energy and resources need to be invested. Brands can adjust according to actual conditions.

3. Analysis of reasons for loss

To analyze the reasons for user churn, we must first classify the users. The reasons for different types of users are generally different.

Take the following groups of people as an example:

Case Study

Target group analysis: Regular customers who have purchased 3 times and have only purchased dried strawberry products.

(1) Current situation analysis

An old customer with low average order value, only buys dried strawberries each time, has bought three times in total, and has not repurchased for a long time.

(2) Logical Reason Hypothesis

Tired of the original product and want to change to other flavors of dried strawberries, other dried fruits, or brands of dried strawberries, because of consumption upgrades or downgrades, etc.

(3) Understanding the actual reasons

① Through the data bank data, it was found that the user had browsed other dried fruit products in the store during the period without repurchase.

②Through the evaluation data, we found that users said they ate too much dried fruits and wanted to try other products, and they were looking forward to new dried fruit products.

To summarize the reasons for the loss: people are tired of eating dried strawberries, but they can’t find other dried fruit products they like in the store.

(4) User needs

Through the above analysis, we can know the reasons for user loss: users are tired of eating dried strawberries and want to buy other dried fruit products, which can be found quickly in the store.

4. Develop a full process diagram for customer recall

To analyze the reasons for user churn, we must first develop a process for churn recall:

5. Develop churn recall strategy/content

There are four major elements in formulating the content of a recall.

Confirm the target population, understand the population's needs, match the needs, and communicate the needs, as shown in the following table:

6. Data follow-up summary

In the early stage, when you just start to run the whole process of loss recall, you must closely monitor the data of each link point, and clearly know which node is effective, which is ineffective, which needs to be optimized and improved, and which can be used continuously.

TIPS: In the effect statistics of each link, it is best to insert comments to explain the data statistics standards and time~

Through the sharing of actual cases above, I hope to help everyone learn how to apply the lost user recall strategy to their respective businesses!

Author: Silkworm Treasure

Source: Huile CRM