I believe everyone agrees with one point of view: Whether it is To B or To C, users are the core resources of the enterprise and one of the most important values in Internet products. Therefore, deeply exploring user value has become the key to the operation of most enterprises today.
We have previously introduced to you how to use the RFM model to allow enterprises to focus on more valuable users. This article will introduce in detail the user life cycle model APMDR and the implementation practice of the " Kangaroo Cloud Customer Data Insight Platform " based on the APMDR model.
The APMDR model can provide scientific basis for formulating effective operating strategies for various types of users, achieve the purpose of extending the user life cycle, help enterprises effectively manage the business life cycle, and truly realize data-empowered business development.
What is the APMDR model?
The user life cycle refers to the entire process from the beginning of contact with the product to the time the user leaves the product. The length of the user's life cycle will directly affect the revenue of products and companies. Therefore, the user life cycle should be scientifically quantified and appropriate operating strategies should be made at the right time to extend the user's life cycle.
As shown in the figure above, the life cycle of an average user is mainly divided into five stages: acquisition period, promotion period, maturity period, and decline period. For customers in different periods, the profits that customers bring to the company are different, and the corresponding operating strategies are also different.
We need to divide the user life cycle according to the characteristics of each user at different stages, and then customize different operating strategies according to the users in different periods. At this time, it is the APMDR model's turn to appear .
● A (Acquisition) acquisition period
In the acquisition phase, target users mainly include unregistered or newly registered users. They may have just come into contact with the platform, or have already started to try to use it, but have not settled in or registered. In addition, there are some users who may have downloaded and registered the platform and showed active behavior on that day, but have not yet become retained users of the platform. Users in the acquisition period include potential users and new users.
For the target users at this stage, the main goal of operations is to activate potential users and make them become formal users. In order to achieve this goal, a series of measures can be taken, including improving product functions, adding content, launching product promotions, and improving promotion strategies. Through these measures, we can improve user experience and increase users' trust and satisfaction with the platform, thereby promoting them to become our long-term users.
● P (Promotion) promotion period
In the promotion stage, the target users are mainly those who have developed active habits on the platform for a period of time. They have become accustomed to using specific functions, and their activity level has reached the standard, becoming active users or retained users of the platform.
For the operational goals at this stage, we can take a series of measures to promote users to repurchase and increase their frequency of use of the product. For example, by providing product usage guidance, personalized content and product recommendations, as well as discount promotions and other measures, we can enhance users' awareness and satisfaction of products, thereby motivating them to use our platform more frequently.
● M (Maturity) maturity stage
In the mature stage, target users are mainly users who have completed paid conversions and have not been lost. They are paying users of the platform and have full trust and dependence on the product. For operations in the mature stage, we can take a series of measures to further improve user value. For example, by increasing product functions, implementing layered operation strategies , providing richer membership benefits, and continuously launching new products.
● D (Decline) recession period
Entering the recession period also enters the survival period of operations . At the beginning of this stage, we need to try new operating strategies. Users in the decline period often appear as users who have not taken active actions for a continuous period of time. The operation at this stage is mainly to reduce the loss of users. Measures such as early warning, increasing switching costs, coupons, and improving user experience can be taken to increase user usage.
● R (Retain) retention period
During the retention period, the target users are mainly those who have uninstalled or have not had any active behavior for a period of time. The recall probability of these users is relatively low, so we need to adopt some special operational strategies.
The operation of users in the retention period is mainly to retrieve users, and try to attract them to start using the product again through product upgrades, launching preferential products or gifts, conducting A/B testing and other measures.
Implement the APMDR model in the customer insights platform
After understanding the basic concepts of the APMDR model, let us use a specific example to illustrate how to generate an APMDR model in the " Customer Data Insight Platform " to guide the advancement of operational work.
Business logic sorting
First, clarify the life cycle model tags of what business we need to establish , sort out the consumption situation and usage logic of its business scenarios, and complete the construction of the core business logic diagram .
Divide user types
Through logical rules, life cycle and stage user behaviors are defined, and user types are divided. Taking a shopping platform as an example, user types can be divided by formulating boundary parameters through some major data, such as the user's first order practice, effective order volume and occurrence time, last order time, and shopping frequency.
Based on the analysis of the business scenario, we should implement label processing based on the following rules:
Complete the generation of APMDR model
Next, you can complete the creation of labels and the generation of APMDR models in the " Customer Data Insight Platform ".
01
Create a user entity and bind the order table and related auxiliary tables to the corresponding user entity.
02
Based on the business analysis rules mentioned above, create derived tags and combined tags. The field values used include the number of user orders, the time of the user's first order, the time of the user's last order, the number of user logins, the user's browsing time, etc.
03
In the process of label processing, we can use the label value distribution function to evaluate whether our classification standards are reasonable. For example, if a certain type of label value is too high, or a certain type of label value is not covered by instances, we need to adjust accordingly. Classification rules to ensure rationalization of processing labeling rules.
04
Tag circle group realizes the implementation of APMDR model. Based on the creation of the above tags, users can be divided into multiple life cycle categories: retention period, decline period, maturity period, promotion period, and acquisition period. User groups can be grouped according to different tag values and customized for different users. Apply different operational strategies.
Summarize
The above is the implementation of the user life cycle model APMDR in the " Customer Data Insight Platform ". In actual applications, users do not necessarily go through the entire cycle, and what we can do is guide users to move to a more valuable stage and prevent users from slipping from a high-value stage to a low-value stage.
With the help of the user life cycle model , a powerful tool, enterprises can achieve a comprehensive analysis of user behavior changes and conversion processes, formulate more targeted operational strategies, improve user loyalty and participation, and maximize user value. and succeed in a highly competitive market.
"Dutstack Product White Paper" download address: https://www.dtstack.com/resources/1004?src=szsm
"Data Governance Industry Practice White Paper" download address: https://www.dtstack.com/resources/1001?src=szsm
For those who want to know or consult more about big data products, industry solutions, and customer cases, visit the Kangaroo Cloud official website: https://www.dtstack.com/?src=szkyzg
Microsoft launches new "Windows App" Xiaomi officially announces that Xiaomi Vela is fully open source, and the underlying kernel is NuttX Vite 5. Alibaba Cloud 11.12 is officially released. The cause of the failure is exposed: Access Key service (Access Key) anomaly. GitHub report: TypeScript replaces Java and becomes the third most popular. The language operator’s miraculous operation: disconnecting the network in the background, deactivating broadband accounts, forcing users to change optical modems ByteDance: using AI to automatically tune Linux kernel parameters Microsoft open source Terminal Chat Spring Framework 6.1 officially GA OpenAI former CEO and president Sam Altman & Greg Brockman joins Microsoft