How to use data to capture your target users?

A question that operations personnel are usually concerned about is: What methods can be used to regain lost users? Today we are going to talk about some key guiding strategies and how to properly use data to capture your target users?

Generally speaking, when operators talk about methods to regain users, they usually mean planning some activities to motivate those lost users through message push and bring them back. But this method that everyone uses generally does not produce good results. Why? The reason is that they took action only after the "battle had failed".

When you find that users are churned, you will plan activities desperately. For example: a big discount or some promotional measures, but what you get in return are often users who bring you the least profit and the highest maintenance costs. The results proved: this was a failed strategy. Once your app is "banished" by users, there is almost no way to wake up these lost users. What you need to do is catch your users before they churn. This is the right choice.

New user retention data of an App: User retention rate is low on the 2nd and 5th days

So the question is, how can we retain more users and prevent them from leaving? This requires that the application be able to further understand their needs, enhance their experience, and increase user satisfaction during each interaction with the user. This may not sound complicated, but it is not easy to do well. However, in summary, what you really need to do is to make smart use of your user behavior data. So how do we do it specifically?

Here are four tips to make sure you’re putting your energy in the right place:

1. Clarify the user life cycle

If you pay some attention, you’ll find in your user behavior data that there are clear signs of what stage your users are currently in. This requires you to observe, discover, analyze, make decisions and take action. One of the methods is to use the user life cycle method, define what stage of life the user is in, and analyze within this stage.

First, for your product business, sort out the stages of the user life cycle, and divide it as detailed as you need. For example, it can be divided into:

• Early stage
• The stage of attraction
• At risk of churn
• The lost stage.

Then, you need to clearly define what the users are like at each stage.

For example, for e-commerce applications, the early entry stage can be defined as the stage within 15 days after a user’s first purchase. An engaged user stage can be defined as a user who has made at least three purchases or visited your app more than 10 times in a week. In addition, make sure that your classification of the user life cycle is a closed loop. At a specific time, each user is only in one stage. This is a necessary condition for the implementation of the user life cycle.

2. Rely on your data

After defining the different user lifecycle stages, you need to have behavioral data that you can use to build user segments. Compare the essential differences between a user who is being attracted and a user who is at risk of churn, and build a data model based on this. Understanding this is critical to modeling each stage of the user lifecycle.

Use data to identify which users are satisfied with your product and analyze their behavioral data. These analysis results can provide directional guidance for planning marketing activities and conducting refined operations. With strict definitions and measurable behaviors, you can label and categorize users for profiles, and understand what decisions you need to make to win back customers who are at risk of churn.

3. Determine the lifetime value of your users

How to distinguish a good user from a bad user? Which are the good and which are the bad users, those who make you the most money or those who actually cost you money and resources? To distinguish these, we must first establish an average user lifetime value, then combine the cost of maintaining different users, and integrate the cost into his user value.

For example: there are some users who consume your free support services heavily, and some users make you spend time processing a lot of unnecessary data. Taking costs into account can help you improve the accuracy of your segmentation results and ensure that these are the target users you care about and want to retain. You can also add some life cycle stages to match those users with relatively low profits, and plan some marketing plans for this group of people for precise operations. Considering their lifetime value, you can also simply remove them from a campaign you are planning.

4. Global considerations

Some operational plans that you think are good may very likely cause user loss. So how do you prevent this from happening? This requires avoiding relying solely on activity indicators to measure the success of an activity, but rather considering it comprehensively from all aspects. Imagine this scenario: you planned an event and notified all users via push notifications. You immediately discovered a significant increase in conversion rates and purchases, so you felt that the event was a success and are ready to continue implementing this method. But in fact, this activity caused some users to cancel the message push function and even uninstall the app. This is exactly what happens when you take on this promotion, you don't consider the overall information of the user, you don't treat them differently, and you don't clarify their relationship with your brand. This is a small profit at the risk of sacrificing the future.

At this time, it is necessary to carry out refined operations on users. The entire life period of users should be taken into consideration, and the user's situation in each period should be measured and tracked, rather than just focusing on the immediate changes after the implementation of the activity. You can do this by dividing your users into two groups. For one group of users, do not send any push notifications to them, while for the other group of users, you can implement active push notifications and compare the value of these two groups of users regularly. It is very helpful for focusing on long-term user retention and user engagement.

We are gradually entering an era of data-driven decision-making. In the future, we will rarely see strategies like winning back lost users. Instead, we will focus more on improving user retention and activity, and planning promotional activities that drive real value to users. The framework of operating the user life cycle is not new, but the premise of doing this is that we can accurately collect user behavior data. Only in this way can we use it maturely. If you do the above points in your operations, you will understand your users better, know which users are worth your investment, and maximize the value of your resources.

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This article was written by @Cobub and published by (APP Top Promotion). Reprinting this article requires the consent of Top Promotion , and please attach the link to this article!