What user operations need to do is: promote activation, attract new users, retain, and monetize these key words. With this guiding ideology, our next work will be to think and operate around this central idea. If you can’t clarify the idea of user operations first, you will be aimless and directionless when working. Over time, you will even get lost and unable to do your job well. When I take over a product, I start to think about what kind of users are using the product, how to perform targeted operations for different types of users, and what strategies should I use to promote, attract new users, retain, and monetize these users? With this question, the following story came up.
Starting from user needs, thinking about user needs, formulating targeted operation plans or operating mechanisms, user operation is a targeted task. Sustained and effective operating strategies make the effects of operational work more controllable. The 7 common operating strategies are as follows.
User classification strategy
User classification is based on the user structure of its own products. Through the detailed data of user portraits, user behaviors and characteristics are divided into Lebanon Whatsapp Data categories. Users can be segmented from high to low levels using the attribute of value. The purpose of user classification is to clarify the user life cycle and the value that can be generated by promoting product development, so as to allocate operational resources in a targeted manner and achieve operational goals more accurately. After completing the data analysis in the later stage, we will conduct user classification in more detail. If we say new users, old users, active users, and silent users, it is a very broad user classification. Then we can use the RFM model to segment users.
RFM model: R (Recency) indicates how far back the customer’s last purchase was
F (Frequency) indicates the number of times the customer purchased in the most recent period, and M (Monetary) indicates the amount purchased by the customer in AQB Directory the most recent period. Generally, the original data has three fields: customer ID, purchase time (date format), and purchase amount. It is processed with data mining software and weighted (considering the weight) to obtain the RFM score, which can then be used for customer segmentation, customer level classification, and Customer Level Value. Score sorting, etc., to achieve database marketing!
