Product Operation | How to build a points system from 0 to 1?

Points system: connects users and products, can effectively guide user growth, and cultivate new users into high-value users.

1. Background

The Yunmeishe App has a function setting of "obtaining vitality points by completing specified tasks".

After we operated for a while, we found some problems with the setting of vitality value, such as:

• Vitality points can only be exchanged for high-definition publishing and watermark removal, while member users themselves enjoy the rights to high-definition publishing and watermark removal.
• The vitality value will be cleared at the end of each year, and many top users have a large amount of vitality value.
• The "action" of gaining vitality points does not match the existing operational goals. Users do not have reasonable understanding of the tasks corresponding to points and do not have enough motivation to complete the tasks. In addition, the rules of the entire points system are not complete.

Therefore, we started the points system in December last year, striving to achieve four goals:

1. We need to design and develop a points mall based on the existing points system to expand the use of points;
2. Calculate the points distribution, taking into account the interests of both super-high points users and long-tail users;
3. Based on user behavior, optimize the corresponding task items for points acquisition, so as to slowly cultivate user usage habits through points;
4. The points mall brings a certain amount of income to the platform.

2. Total amount and distribution of vitality value in the station

To optimize the points system, we first need to understand: What is the user’s existing vitality value accumulated?

It is necessary to mobilize the enthusiasm of mid- and long-tail users, while also considering the redemption costs of top users. We first export all vitality values ​​from our own BI system, and then use U-App event analysis to analyze the events. We select the numerical value type and the custom interval setting to obtain the user interval distribution.

According to the data gradient, we can see intuitively that: currently the overall distribution of vitality values ​​is very wide, some users have very high vitality values, and most vitality values ​​are within 1000. Excluding the relationship with new users, we need to push this part higher.

(P.S.: In order to obtain a more realistic vitality value (integral) gradient, it is necessary to exclude lost users before calculation.)

Secondly, re-plan the task system.

We have done a lot of tasks based on vitality points before, and we found that when users accumulate so much vitality points, they come from many channels. We have a very detailed understanding of each task, such as: daily video releases, number of likes, number of comments, etc., to show that users really like and comment in order to obtain points.

Therefore, we will track every day whether the points belong to this source, and finally find that posting, signing in, and liking may have higher points because the user tasks are more objective. In addition, the points obtained from previous rewards and sharing were relatively low. This part was later calculated to form a chart showing how users could earn points by completing tasks.

According to the data processing results, we can see that tasks such as sign-in (punch-in), posting, and liking are at the top and are more popular among users. During the optimization process, we need to retain this popular task, while also encouraging users to follow our lead, to form a sense of one link after another and to form user habits. Then, the corresponding rewards for the tasks will also be adjusted accordingly.

3. Target Group

After completing the above two parts, we will make a new plan for the future.

Based on the "user grouping" method of U-App , users are defined and selected based on relevant data such as the number of logins and usage time. There are mainly four types of users:

1. New users: They have just downloaded and registered the App, and their points are 0. We will promote a specific system for these users.
2. Regular users: They only use the App’s functions but have not developed the points task system. They are more active.
3. Senior users: They have been using the app for a long time and will actively collect points and complete corresponding tasks. The points of this type of users are at least 5,000.
4. General users: low activity and low points.

IV. Implementation steps

1. Current points status

Points are exported through Yunmeishe’s own BI system, and data analysis is performed to view point distribution, thus preventing users with huge point loss from affecting actual results.

For example, if there is a user who has not logged into the Yunmeishe App within a year, but may have more than 50,000 points in his points account, then we will regard this type of user as a lost user.

1. Compare the data for each task

After understanding the current distribution of points, you also need to understand the source of points, which will help optimize the points task later.

First, all the tasks that can earn points need to be arranged, and then the total number of points that the user can earn for the task is extracted one by one through the background database according to the corresponding task. Even if the user makes consumption after earning the points, it should be included in the user's total points. Based on the extraction results of each item, we can finally draw a percentage chart of points sources.

1. In the points task system, check the user ratio corresponding to the points in different echelons

Use event segmentation to see the percentage of users in the old vitality value and new points systems.

1. Prediction based on existing vitality value mechanism

Regarding the task part, we made predictions based on the vitality value rules at the time - how many users can reach what points qualifications within how long?

for example:

• It takes an average user at least 4 days to reach 1888 vitality points.
• It takes an average user at least 7 days to reach 3888 vitality points.
• It takes an average user at least 17 days to reach 10,000 vitality points.
• It takes an average user at least 167 days to reach 100,000 vitality points.
• It takes an average user at least 334 days to reach a vitality value of 200,000.

By comparing the data in the above steps, we can find that there are unreasonable links in the current points rules.

For example: According to the current points task rules, an ordinary user needs to complete all tasks for 7 consecutive days to get a chance to remove the watermark. Most new users will sign in and post videos within 1-2 days after registration, but the points rewards are relatively small, which will inevitably lead to a decrease in new user stickiness.

Therefore, we reset the task rules and points rewards.

1. Optimization of points rules

We set the actions that users most need to complete into the points rules, such as: posting videos, sharing, following, etc.

1. New Points Prediction

According to the new points rules and optimized points tasks, Yunmeishe divides users into four categories for calculation:

1. Top users are users who complete each task every day;
2. Senior users are users who complete 80% of the tasks;
3. Advanced users are users who have completed 50% of the tasks;
4. Ordinary users are users who complete 20% of the tasks.

Based on the above four types of users, calculate the time required to reach the following points levels.

1. Build a points mall

Once the existing points distribution and new points rules are clear, it is easy to build a points mall. There are two points to note during the construction process:

1. Redemption control for users with large points;
2. New users/ordinary users need to set the rewards they can get by "jumping", and the number of points that can be redeemed is crucial.

Therefore, replacement goods are divided into two categories: virtual and physical .

Virtual goods are released in high definition and without watermarks. Since the watermark-free goods can also be purchased using another currency on the site, US dollars, and US dollars can be directly exchanged for money, in order not to affect the income, we have increased the watermark-free price to 9999. The price for high-definition 1080p release has been reduced to 999, so even new users can receive rewards at the time of registration and reap the benefits. The physical prizes range from 10,000 to 200,000 yuan.

The points mall will be used to increase revenue in the future, which means that it will introduce a system that requires additional payment or payment plus points redemption. The overall development is divided into three steps:

1. Optimize the overall task system in advance;
2. The first version of the points mall, which only involves redemption, was launched online;
3. Merchants will be introduced to settle in the points mall and part of it will be launched online (under preparation).

Points achievement: Estimate how many new behaviors the new points policy will encourage users to generate - for example: How many users will be motivated to post how many videos by a "benefit" of 300,000 yuan? What actions can be used to leverage points to drive user growth?

5. Results Review

1) It is necessary to monitor the sources of the total points on the site every day, compare the optimized points source chart with the points source chart before optimization, and derive the core task - the data growth of sign-in, posting, and likes. At the same time, it can be found that the completion rate of auxiliary tasks such as improving personal data and sharing is relatively high.

2) Has the corresponding target population been optimized?

• Among the four categories of users, namely new users, ordinary old users, senior old users and ordinary users, the situation of new users completing novice tasks and using points has been improved;
• Through tracking and comparison, some of the former ordinary old users have been transformed into senior old users, and the stored points of senior old users have been consumed to a certain extent;
• General users are transformed into ordinary old users.

6. Some thoughts on the points system

The points system is a means of operation and a manually formulated and automated operating mechanism. Starting from registration, users will follow this mechanism throughout the entire process. When users reach key nodes, they automatically obtain benefits.

But the core of the points system is the user experience, and users do not earn points just for the sake of earning points. The series of actions we set must be supported by complete tutorials, operational strategies, and product capabilities, which are mutually reinforcing.

There are two key elements in building a points system:

1. Points tasks are derived from business goals, and the settings of points tasks will be different in different stages of the product.
2. The value of points and incentives for users need to take into account the needs of users at all levels.

The three values ​​of the points system:

1) The points system is a product that aggregates tools and content, similar to the blood of a product.

We connect each function through a points system to guide users to complete the paths and tasks set by the product.

For example: There are some auxiliary functions in the App, which are distributed relatively loosely. For example, there are functions such as watching and liking in the clips, and these functions are connected through a points system.

2) Guide the growth of users.

From new users to high-value users, from silent users to active users, use points and benefits to promote their growth and assist in the management of the user life cycle.

3) Improve user loyalty and activity.

In short, the points system connects users and products, which can effectively guide user growth and cultivate new users into high-value users. After all, only when users consume can a product survive.

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Author: Lei Zhen

Source: Lei Zhen