When a product enters its mature stage, its operating strategy will naturally need to be adjusted from before. The fastest way to learn is to deconstruct a mature and complex product and analyze how it builds a user growth model. This article will take NetEase Cloud Music as an example to analyze how it improves operational efficiency by building a typical user growth model. I hope it will be helpful to you.

Students who have experienced user operations for a complex product that has entered its mature stage may have this feeling: the idea of ​​gradually growing a product from 0 to N by continuously adding various operation strategies to achieve growth is clear, but as the product develops and has a huge user base and enters its mature stage, many strategies have been implemented sporadically at a single point in the development process, resulting in the relationship between various strategies being particularly complex, difficult to manage, and inefficient. So what should we do at this time?

Today I will introduce to you a method of improving operational efficiency by deconstructing complex products and rebuilding a typical user growth model.

Only by knowing the enemy can we target the target. Let’s start by understanding the product’s growth history and business:

1. Growth process

1. Product iteration

First, let’s review the iterative growth process of NetEase Cloud Music, which can be roughly divided into the following four stages:

Initial stage (March 2013-July 2014): Improve basic music listening and social functions to retain core users

Development period (July 2014-July 2015) Achieved stable growth in users, focusing on maintaining the social atmosphere within the product

Growth stage (July 2015-September 2017) The product achieved explosive growth and began to drive explosive growth through operational means

Mature stage (September 2017 to present): Product growth slowed down, and large-scale commercial exploration and trials began

Combining the above Cloud Music user growth trend chart and version iteration records, the product has mainly gone through the following stages.

In the early stage of product improvement, the focus is to complete user growth and traffic. In the later stage, after completing user growth and entering the mature and stable period, the focus shifts to commercialization and realization, and in the continuous trial and exploration

2. Core business logic

As the product matures, we now see Cloud Music evolving from a simple music listening tool into a comprehensive and complex product with audio, video and community attributes. However, in essence, any successful product expands its business and conducts operations around its core functions. Therefore, it is very necessary to disassemble the core business logic.

From the above product iteration path, it is not difficult to see that the core function of Cloud Music is "listening to music", and the core user path is "finding songs - listening to songs - expressing", thus extracting the core business logic of the product, as follows:

3. Product path

Then sort out the product path based on the core functions of the product used by users:

After completing the above analysis, we have a relatively comprehensive understanding of the product NetEase Cloud Music. Then, let’s get down to business and analyze in 5 steps how to deconstruct complex products and build a typical user growth operation model.

2. Business Model

1. Sort out the product's commercial channels and user value development paths

[Business Channel] After Cloud Music accumulated hundreds of millions of users, it embarked on the road of commercial exploration. Specific methods include: advertising, membership income, shopping malls, music copyrights, performances and games, etc. It can be seen that its business channel is to generate income and keep users paying or contributing traffic value.

[User Value Development Path] Refer to the iterative content of the four stages of the product:

1. In the initial stage, the main focus is to verify the product MVP, and users are willing to download and use cloud music to listen to songs and share them with others.
2. In the development stage, based on the feasibility of MVP, we will improve the core functions to complete the early user accumulation. By adding comments, likes, and sharing functions, we will guide users to express and interact, enhance their sense of identity and belonging, and stabilize retention to accumulate users.
3. During the growth phase, we will focus on the community module, optimize core functions and enrich scenarios to increase activity and retention, enhance community attributes to cultivate users' interactive habits, and encourage users to produce content to feed back to content consumers; at the same time, we will begin to explore commercialization.
4. In the mature stage, the product has reached maturity and the focus has shifted to commercial monetization, focusing on tapping the user's payment potential and continuous traffic contribution.

2. Refer to the user value stratification method to classify and define typical users

The user growth ladder is defined based on the user value stratification, that is, under ideal conditions, users advance from one level to the next to complete the value leap and maintain a typical growth path of continuous contribution during their life cycle. So first we need to do basic value stratification for Cloud Music users.

Usually, the life cycle value stratification of users of traffic-based products can be usually divided according to the user's activity and retention in the product; paid revenue products can be directly divided according to whether the user pays, the first payment behavior and the Nth payment behavior. However, for complex products like Cloud Music, whose business model combines both traffic revenue and direct payment revenue, it is necessary to first split the typical user types and then segment each type of typical user.

Based on the attributes of Cloud Music’s tools, community, and paid revenue, users can be roughly divided into the following four types:

1. Passerby users
2. Content consumption users
3. Content Contributing Users
4. Consumer purchasing users

Describe the user's general profile based on the user's behavioral characteristics:

Based on the user portrait, we further refine the user's specific behavior and define specific data for each layer of typical users. Here, we only use typical cycles and position numbers to demonstrate the definition. For specific operations, we can combine the actual business scenarios, analyze the detailed user behavior data, and combine the business product characteristics to obtain specific critical values.

The above four categories are just a rough division according to typical users, and the focus is to help sort out the user growth path. Users at each level can be stratified in a more fine-grained manner according to their specific value contribution type and contribution degree. Here, we will simply use a picture to describe the idea. The three commonly used value stratification models involved in the detailed user stratification are the four quadrants, pyramid, and RFM, which will not be elaborated in detail. If you are interested, you can check the relevant information later.

4. Sorting out the operation model based on the typical user growth ladder

Assuming that there may be an ideal typical growth relationship between these four types of users, we integrate the core functions of the above user classification collection products to build a new user growth ladder, and sort out the user operation model around the growth ladder (see the figure below for details)

5. According to the user growth ladder, sort out the optimal growth path for users at different levels

The functional diversity of Cloud Music products determines that the user growth path is complex. In order to improve operational efficiency, it is necessary to sort out the optimal growth path for users and implement effective guidance strategies.

From the perspective of user's subjective initiative, it can be mainly divided into autonomous and passive types. Autonomous users are highly proactive and spontaneous, do not like routines, like to make their own decisions, and are not easily guided by aggressive operational strategies; passive users, on the contrary, are easier and more willing to be guided and motivated. Therefore, when sorting out the optimal growth path for users, we look at these two types of users separately.

6. Design incentive strategies to guide user behavior based on the user's optimal growth path

First, the user behaviors that need to be guided are classified according to the difficulty of intervention as follows:

• One-time behavior: Allow users to complete a key behavior at one time, such as following a content source, placing an order for the first time, etc. (user behaviors that are highly correlated with the core experience process)
• Behaviors that keep users engaged for a long time: such as continued use of core product features, continued browsing, continued payment, and continued content contribution.
• We hope that users will ensure a certain minimum level of contribution: such as completing daily sign-ins, sharing, etc.
• Allow users to complete advancement or transition in ability or identity: such as advancing from a casual user to a content contributing user, or advancing to a paying user.
• Allow users to have a higher level of emotional identification with the product: such as publishing and creating more content to generate interactions or generate their own social relationship chains.

Whether the guidance of user behavior is effective mainly depends on the design and polishing of the functional rules of the back-end product and the front-end operational strategy incentives. Here we have sorted out the common incentive strategies corresponding to different behavior categories.

Finally, integrating different user behaviors with user growth stages and models into a complete set of typical user growth models can guide us in carrying out related operational work to a certain extent.

PS: Of course, long-term and rhythmic user operations also need to be combined with a set of operational incentive systems that conform to the characteristics of the product in order to ultimately form a complete user growth system (I can expand on this part when I have time).

Author: Adai

Source: Adai

Related reading:

A brief discussion on user stratification in user operations

4 ways to improve the user operation system!