Huawei HMS core launched a new member conversion & retention prediction model

Now? , Paid learning knowledge , Pay for music , Pay to watch TV shows , Pay for online shopping …… And so on, scenes have become the daily life of most young people .

And for businesses , Paying members as a means of differentiated user operation , It is not only conducive to improving users' brand loyalty , In the present , It has become a general mode of flow realization .

How to effectively improve the paid membership rate of users and establish a high viscosity membership relationship ？ Scientific and reasonable member transformation potential evaluation is very important .

Huawei forecast service has launched a new member conversion and member retention forecast model , From evaluating the transformation potential of non paying members to paying attention to the renewal retention of paying members , The whole link focuses on the transformation life cycle of paying members , Help developers build high viscosity Membership .

The conversion potential of non paying members is evaluated in advance

The transition from non paying members to paying members , In addition to the need for membership differentiation and the attraction of value-added services , It also needs to be combined with scientific and reasonable member payment potential evaluation , In order to effectively improve the conversion rate of member payment .

The member transformation prediction model is based on the user's recent application performance , Through scientific algorithm evaluation , Calculate the member payment probability of active non paying members in the next week in advance , Based on this , Operators can formulate corresponding payment promotion marketing policies for members with different payment probabilities

for instance , Suppose a utility App, Functional member payment is the main business model of its business . Member transformation prediction model , Operators can take the predicted population of high probability members as the key object of operation to promote payment activities , Then, with the help of intelligent operation platform, people are stratified , Then focus on the first charge welfare activities of members to reach , Realize the effective improvement of final member payment conversion .

The retention probability of members shall be known in time

As a high-value user of the enterprise , Paying members with high stickiness should have high loyalty , It is not easy to lose to the competitive platform , But the current situation is , The homogenization of Internet products is serious , The competition is getting fiercer , The lack of stickiness of paying members has become a problem for many Internet companies “ Heart disease ”.

The member retention prediction model can be based on the user's recent behavior in the application , Through machine learning technology , When the user's membership interest is about to expire , Scientifically evaluate the user's recent renewal probability , Personalized layered operation strategy , Achieve accurate crowd touch and effectively improve member retention .

In addition to the attraction of renewal benefits , Operators can also use the member retention prediction model , Based on user's interests , Focus on content , Push personalized messages . for example , Some video APP Filter through Huawei analysis , Focus on people with high probability of membership renewal , When analyzing the page access preferences of these users , It is found that the visit of variety page is significantly more than that of other columns . Based on this analysis , Operators can enjoy the highlights exclusively by pushing paid members of the current popular variety shows , And further enrich the exclusive variety content of more paying members to continue to attract temporary members to renew .

For products with a member payment system , From the first payment of non paying members to the later renewal of paying members , The member paying behavior of users directly represents the length and loyalty of their life cycle . Only insist on data-driven , Tiered operations through persistent users , Tap core potential users and guide them through active operation strategies , In order to establish a highly viscous user relationship .

At present , The member conversion and member retention prediction model has enabled the white list for free , If your product has relevant operational needs , It can be done by email [email protected] Contact us .

To learn more about forecasting service usage , see also ：

Forecast service official website

Refer to the development guidance document , Quickly complete basic data reporting ：

Android Integration documentation

iOS Integration documentation

Web Integration documentation

Apply it quickly Integration documentation

HarmonyOS Integration documentation

Wechat applet integration document More highlights , Please see the official Huawei Developer Forum →https://developer.huawei.com/consumer/cn/forum/home?ha_source=sanfang