[Huawei Developers] Freemind R:
A lot of apps these days are struggling to grow their user base, while traffic is also getting increasingly expensive. Although some apps have acquired a large number of new users, the corresponding churn rate increases sharply. So, it is important that you can win over a number of retained users that are particularly loyal to your app.

What is retention?

Let's take mobile apps as an example. After downloading the app, some users just take a cursory glance, some will never come back after they've claimed the coupons, some may even uninstall the app without ever using it. It is only users who continuously use and benefit the app that can be regarded as retained users.

The retention rate generally refers to the rate of repeated behaviors of a user over a given period of time, and is usually measured by the retention rate after 1 day, 7 days, and 30 days.

Generally speaking, there are three types of retention curves: the smiling curve, flattening curve, and declining curve.

Smiling curve: ideal curve for all app managers. It shows an increasing trend in a certain period of time. For an e-commerce app, for example, it indicates that users keep coming back to purchase your products.

Flattening curve: indicates that the app has attracted some new users, and these users like the app and continue to use it. However, not all flattening curves are good. You want the curve to flatten as high as possible on the graph, as this indicates a better long-term retention rate.

Declining curve: indicates that the app has not achieved a great deal of approval among users. A declining retention rate is a sign that you need to act now to optimize your app, and make it more appealing to your target users. Otherwise, its future prospects do not look good.

How is user retention analysis implemented?

User retention analysis is implemented by segmenting your users. You can segment your users through Analytics by phone model, device type, gender, age, and region. Then, you can think about the reasons why users are retained or churned by looking at these segmented user groups. For example, if you find that the retention rate of new users is much lower than existing ones, you might want to optimize your tutorials, or provide a quick activation service for new users. If you have an education app, and you find that users retained for longer are those who add more courses to their favorites, you can prompt users to add courses to favorites by sending them in-app notifications, or rewarding them with bonus points. If you see that the majority of churned users were using earlier versions of your app, you can prompt users to upgrade in different scenarios and through multiple channels.

How is the retention rate improved?

A retention curve can be broken down into three stages: the onboarding stage, the nurturing stage, and the attrition stage. Through this report, we can see that the best way to improve user retention is either by shortening the onboarding stage and converting new users into loyal users as quickly as possible, or by pushing the curve up as high as possible.

Let's first look at how to shorten the onboarding stage.

The key is to improve the retention rate of new users. Here is a case.

Case: HUAWEI Analytics helped a social e-commerce app improve its retention rate by 15.3%.

The app, which features a range of social functions, faces competition from many similar apps. To increase its Daily Active Users (DAU) by improving its user retention rate, the app took a series of actions: First, Analytics was used to design a funnel measuring behavior throughout the user journey, from when the user first installs the app, to when they register an account, sign in to the app, browse products, add an item to their cart, place an order, and finally make a payment. By monitoring the conversion rate at each stage, it was found that the churn rate between the adding a product to cart and placing an order stages was as high as 39%. This led them to set a 15 minute time limit for the cart, prompting users to place their order quickly. In addition, users were segmented by channel. When doing this, it was found that the retention rate of active users from channel A was much lower than the overall retention rate. So, it stopped trying to attract new users from channel A and increased their investment in other channels. By implementing these strategies, the app was able to increase its user retention rate by 15.3% within just two months.

As the above example shows, you can do all of this, and boost your retention rate, by using HUAWEI Analytics. Once you integrate the HMS Core Analytics SDK, you can upload user attributes and behavior data, so that the actual behavior of users at a specific time can be displayed, giving you the basis of data analysis. HUAWEI Analytics supports the automatic collection of 11 user attributes and 27 events, as well as customized user attributes and 500 customized events, making your optimizations easier and providing more data for refined operations. Moreover, it provides abundant analysis models based on the atomic data, such as events, behavior, funnels, audience, lifecycle, and attribution, enabling you to learn about user growth, user behavior, and product functions. Backed by these models, the filter can be used to perform segmentation analysis of app types, user attributes, and audiences. More importantly, it supports various types of apps, including iOS, Android, and Web apps to meet your cross-platform analysis needs. You can complete the integration and release your apps in half a day. HUAWEI Analytics has become one of the most popular services globally due to its quick development and powerful analysis capabilities.

HUAWEI Analytics has been used by more than 5000 apps globally. Be sure to check it out!

For more details, you can visit:

Our official website

Our Development Documentation page, to find the documents you need:

Android SDK

iOS SDK

Web SDK

Quick APP SDK

We’re looking forward to seeing what you can achieve with HUAWEI Analytics!