In the current environment, almost all applications are facing huge user growth challenges. The main reason for this is the decline in the demographic dividend of the Internet, the number of users and the lower and lower growth rate, and even negative growth in some vertical categories. Competition in e-commerce, lifestyle, gaming and other industries is also increasing, and at the same time, the retention rate of new users continues to decrease. Difficulties in new pull and low retention have become a long-term dilemma for various applications.
So, how should we break the situation in the face of growth difficulties?
The obvious answer is: based on data-driven, look for growth opportunities throughout the user's life cycle, and achieve sustained and effective growth with refined operations.
The first step of refined operation is user stratification. With the help of Huawei analysis services, users can be divided into novice period, growth period, mature period, silent period, and loss period.
For novice users, it is necessary to design growth strategies around ROI improvement and promotion to ensure that new users are the target users of the product, so as to promote the activity of new users as soon as possible and complete the transition from new users to growth users.
For users in the growth and maturity stages, the keywords for growth are to increase retention and increase conversion rates. This part of users is the treasure of the application. How to tap the value of such users so that they can be active in the product longer and retain more For a long time, it is of vital value to the application.
For users in the silent and churn periods, it is necessary to consider preventing churn, precise recall, analyzing the reasons for churn, and optimizing the promotion strategy.
Novice stage: reduce customer acquisition costs, promote livelihoods, and promote growth
For novice users, how to reduce customer acquisition costs? We can use Huawei's analysis of events, comparative analysis and other models to determine the overall trend of various events, the model distribution and version of the source of the event, and then through the filter, we can do a comparative test of a large number of materials and identify the best delivery channel. .
For novice users to promote life and growth, they can be guided to complete the execution of key actions as soon as possible through the user's points of interest. For example, video applications guide users to watch videos for a certain length of time or purchase members; game applications guide users to pass basic levels as soon as possible; e-commerce applications guide users to complete the first order as soon as possible. Then through the funnel and attribution analysis, analyze the conversion rate of users in a series of key nodes in the application, optimize the process, optimize the way of distributing benefits, or optimize the UI design of a certain link.
Case: Operational practice of a short video app to reduce customer acquisition costs
In this case, the short video application launched new ads through multiple channels, but it was unable to accurately identify the contribution rate of each channel, and the new user churn rate was high.
App operators use the attribution analysis model of the analysis service to determine the target conversion event as "new download and use" and the attribution event as "clicks on the advertising space of each channel". According to the report generated by Huawei analysis, they found that the volcano video Laxin’s contribution rate was the highest, and Weibo’s contribution rate was the lowest, so the marketing budget investment on Weibo was cancelled and allocated to the volcano video. After 3 months of optimization, the final review results showed that the customer acquisition cost of the video application dropped by 26%, and the new user retention rate increased by 15%.
Growth period and maturity period: promote survival and retention, and improve conversion
For users in the growth and maturity stages, in addition to promoting life and retention, they also need to focus on improving conversion rates. "Retention" and "conversion" are also common problems encountered in almost all applications. For retention, through the "path analysis" function provided by Huawei Analytics, you can observe the actual behavior path of users in the product, see if there is any deviation from the path of product design, and intervene through operational strategies to guide users to what the operators hope The path comes up. At the same time, the funnel analysis model can be used to intuitively see the conversion number, conversion rate, loss number, loss rate, etc. of each link, which provides direction for product optimization. For conversions, through the combination of Huawei's powerful filter function and behavior analysis, users can be segmented and analyzed to understand the behavior characteristics of different users. Based on the analysis results, use audience analysis to group users, operate hierarchically, and accurately reach users. To increase conversion.
Case: An e-commerce application improves retention and conversion practices
An e-commerce fresh food application found that the retention rate and purchase conversion rate of users in the last 2 months were relatively low, and the reason needs to be found and resolved as soon as possible. Operators first segmented users through user attributes, such as gender, age, region, mobile phone brand, etc., and user behaviors, such as browsing products, adding to shopping carts, and purchasing, and then used Huawei analysis for different audience segments. The provided path analysis and funnel analysis report explored its different behavior characteristics, and finally found that the most lost and silent users from the order submission to the payment link are the common characteristics of the purchase of less than 3 orders and the unclear division of the homepage function area. Based on such findings, the application's operators formulated an optimization plan, which ultimately improved the purchase conversion rate of the product.
Silent period and drain period: prevent drain, promote wake-up, sum up experience
Users entering a period of silence and churn are scenarios that application products and operators do not want to see.
During the silent period, users need to focus on preventing loss and precise wake-up. With the help of Huawei's analytical service user life cycle model to provide users with churn risk predictions and recall potential users predictions at various stages, operational strategies can be formulated in advance to avoid user churn as much as possible. It is also possible to identify users with wake-up value and possibility of wake-up through behavior analysis, and carry out the news of wake-up activity. For users in the churn period, the difficulty of recall may be greater than that of pulling new ones. We recommend that more energy be put on experience summarization and optimization to avoid the loss of other active users. For example, through the funnel analysis, behavior analysis, and comparative analysis functions provided by Huawei Analytics, we can gain insights into the characteristics of lost users, enhance their ability to identify before they are lost, and allow lost users to provide optimization directions for current users' promotion, through product optimization, operational plan improvement, etc. Enhance the vitality and stickiness of active users to avoid loss.
Case: The silent wake-up practice of a game App
This is a silent wake-up practice for gaming applications. First of all, by studying the behavior analysis report and audience analysis report of silent users, operators have identified high-value users who are easy to wake up during the silent period. They are the people who paid more than 3 times in the early stage and passed more than 5 levels. Then the design wakes up the copywriting and tests continuously, and conducts interest guidance and value incentives. On the other hand, game operators use Huawei's analysis of the user life cycle model to predict the risk of loss of users at various stages, strengthen the task experience of such users in the game, and distribute gifts through in-app messages and push to prevent loss. Secondly, we conducted detailed behavioral and attribute insights for the users who have lost, and got the preliminary reasons for the loss: the number of game friends of lost users is less than 5; most of them have complained about Gu game stuck. Therefore, the operators designed a plan to verify, and after determining the reason for the loss, they optimized the product and the operation plan. For example, they provided multi-channel login, added a one-click add friend button after each game, and optimized the interaction logic. . After a series of measures were implemented, the user silence rate of this game was reduced by 12%, and the churn rate was reduced by nearly 8%.
Finally, let's review how developers can achieve full life cycle user growth based on HMS Core Huawei analysis services.
First, you need to integrate the SDKs (Android, iOS, JavaScript) of Huawei Analytics Services, so that user attributes and user behavior data can be reported. Together, these two types of data can help you understand which users did what and when, to form The basis of data analysis. In order to reduce the development workload, Huawei Analytics supports automatic collection of 11 user attributes and 27 events, as well as custom user attributes and 500 custom events, which greatly facilitates developers’ requirements for application optimization and is also refined Provide more data support for chemical operations.
Based on these atomic data, Huawei Analytics provides a wealth of analysis models. Including event analysis, behavior analysis, funnel analysis, audience analysis, life cycle analysis, attribution analysis, etc., to help developers gain insights into user growth, user behavior characteristics, and product features. Based on these models, filters can be used Make segmentation analysis for application types, user attributes, audiences, etc. It is worth mentioning that HMS Core Huawei Analytics supports cross-platforms, including Android, iOS, and Web. It only takes half a day for developers to successfully integrate and release. With such agile development speed and these powerful analysis capabilities, Huawei Analytics has become one of the most popular services for developers around the world, and developers are welcome to access and use it.
For more details, please refer to:
Official website of Huawei Developer Alliance: https://developer.huawei.com/consumer/en/hms/huawei-pushkit
Obtain the development guidance document: https://developer.huawei.com/consumer/en/doc/development/HMSCore-Guides/service-introduction-0000001050040060
To participate in developer discussions, please go to the Reddit community: https://www.reddit.com/r/HuaweiDevelopers/
To download the demo and sample code, please go to Github: https://github.com/HMS-Core
To solve integration problems, please go to Stack Overflow: https://stackoverflow.com/questions/tagged/huawei-mobile-services?tab=Newest
Original link: https://developer.huawei.com/consumer/cn/forum/topicview?tid=0203379108668200356&fid=18
Author: pepper