Look at the product growth of WeChat Reading through the AARRR growth model!

As we enter the second half of the mobile Internet, with the disappearance of the demographic dividend, it is becoming increasingly difficult to obtain traffic. Most of the new user traffic comes from the existing market. Throwing money at a brute force approach will not bring about good user growth and retention for the platform; user growth has entered a refined stage, and how to acquire a large number of high-quality users at the lowest cost is a problem that operations and products currently need to solve;

I recently finished reading the book Growth Hacker and combined it with my own experience with user growth. Taking WeChat Reading as an example, let’s talk about some insights into user growth.

This article mainly consists of the following aspects

1. About WeChat Reading

2. Product AARRR Model

3. Conclusion

1. About WeChat Reading

1.1 Product Overview

The first version of WeChat Reading was released in August 2015, with the product positioning as social + reading. Slogan: Reading is no longer lonely. Mainly based on the WeChat relationship chain, it creates a reading social application that integrates book reading, book recommendations, book review sharing, and book friends communication;

WeChat Reading Related Pages

1.2 Market Analysis

According to an industry research report by Analysys Qianfan, WeChat Reading currently belongs to the first echelon in the industry, with 8.04 million IOS download channels and more than 7 million active users in the first half of 2018.

China's mobile reading market size

Mobile reading app download rankings in the first half of 2018

1.3 User Analysis

The ratio of male to female users of WeChat Reading is close to 3:2, with the majority being those born in the 1990s and 1980s, and mainly distributed in coastal areas.

User population ratio

Age ratio of users

Regional share

1.4 Core business logic of the product

The main logic of the product is to add social elements based on functions such as user book search, reading, book review, and sharing. While providing a good reading experience, it enables book lovers to exchange and share their reading experiences;

Core business process diagram

1.5 Product Structure Diagram

Product Structure Diagram

2. Product AARRR Model

The AARRR model includes the following five elements:

Acquisition: How do users discover (and come to) your product?

Activation: What is the user’s first-time experience like?

Retention: Do users return to the product (repeat use)?

Revenue: How does the product make money (through users)?

Refer: Is the user willing to tell other users?

2.1 User Acquisition

The user acquisition stage mainly focuses on finding the core channels for user growth. After finding the corresponding channels, further optimization is carried out on the channels. For example, WeChat Reading has a marketing campaign of giving away one book for a limited time, and through background data analysis, it was found that the user acquisition effect is very good. Then the next step is to create more marketing activities based on acquaintance social networking, using old users to help the platform attract new users;

Some strategies for acquiring WeChat Reading users

WeChat Reading related page pictures

New user introduction of WeChat Reading from 2015 to 2018

2.1 User Activation

In the stage of stimulating user activity, the growth team mainly does the following work:

1. Collect new user portraits and user behavior trajectories through means such as embedding points, and create a conversion funnel model.

2. Through the collected data, help new users experience the highlights of the product more quickly, discover the core value of the product, and promote further dissemination of the product;

3. Observe the differences between active users and inactive users, locate relevant problems as soon as possible, and make optimizations;

WeChat Reading Stimulates Active Part Strategies

WeChat Reading Part Page

WeChat Reading Monthly Active Users

2.3 User Retention

In the user retention stage, the main role of the growth team is to ensure that the product continues to bring greater value to users. In addition to continuously improving product functional experience, the team must also pay attention to competitive product dynamics, collect user feedback, and continuously improve product value.

WeChat Reading has done a good job in user retention:

1. Reading time incentive system: using "discounts" to encourage users to read. In terms of improving user retention, WeChat Reading has done an excellent job in the book coin exchange mechanism: as long as you read for 30 minutes, you can exchange it for 1 book coin. "Reading - exchanging coins - buying books" has formed a good positive cycle, and up to 10 book coins can be exchanged per week. It is helpful to encourage users to continue to buy books, read them again, and improve user retention.

2. Social activities such as "sharing/interaction" improve retention rate: On the one hand, establish a user growth system to display the books read, reading time and friends' reading rankings. Take advantage of users' desire for glory and comparison to increase the frequency of their use. On the other hand, based on social networking among acquaintances, old users share with friends through WeChat’s own channels, WeChat Friends and Moments.

Some strategies for improving retention in WeChat Reading

WeChat Reading User Retention Rate

2.4 User Monetization

All Internet products go through so much work in the early stages, and the ultimate goal is to make the product profitable. Common business model strategies include building memberships, limited-time use of core features, etc. The work of the growth team at this stage is mainly to analyze user payments for various business model strategies through data analysis, and to find business strategies that most users pay for.

WeChat Reading User Monetization Strategies

WeChat reading page

Daily recharge amount of WeChat Reading from 2015 to date

2.5 Virus Spread

Viral spread is mainly due to users' recognition of the product and their willingness to actively share it with people around them to experience it;

There are two core indicators of viral transmission: K factor (the degree to which a user spreads a product to others x the proportion of infected users converted into new users) and viral cycle (the time required from a user sending an invitation to a new user completing the conversion). The K factor can be increased by inviting friends, increasing channels, optimizing landing pages to improve conversions, etc., and the operation threshold can be lowered. Improving the core functional experience can shorten the cycle.

In addition to these methods, we must also make full use of user psychology such as user liking, profit-seeking, reciprocity, seeking help, showing off, competing for scarce resources, fear of losing and missing out, and laziness.

Some viral communication strategies of WeChat Reading

WeChat Reading Related Pages

3. Conclusion

The overall performance of WeChat Reading’s user growth is average. I personally think that the main reason is that WeChat Reading makes use of WeChat’s powerful social chain. But it is still a latecomer in the mobile reading market. In the reading industry, there are many reading applications that have been deeply rooted for many years, and the market competition is quite fierce. On the other hand, the impact of applications such as short videos has resulted in the growth of WeChat Reading being lower than expected.

suggestion:

1. Improve the overall quality of WeChat reading audio. For some users, they prefer the function of listening to books rather than reading. Currently, the reading function is still very rigid. If this function can be optimized, it can promote the conversion of potential users.

2. Provide diversified content needs for different user groups. Although WeChat Reading has signed contracts with many writers, its influence is currently very limited. It could try to cooperate with other platforms such as Get and Chaos University to sign contracts with influential writers in a certain field to produce better quality content.

3. Improve the recommendation mechanism and combine algorithms with people.

Source: Internet Home