Product Operations: How to Develop a Growth Plan for Your Product!

After the concept of growth hacking was introduced into China, through everyone's joint efforts, it is now well-known in the Internet industry; I was fortunate to be involved in it because I wrote several articles. Because of this, I am often asked by new friends:

1. How to plan growth for your product? Where should you start?
2. The team is too weak, and the hacker growth model and concept are difficult to implement?
3. After reading the article, I learned from you. How did you achieve growth?

etc.

In fact, the channels through which I learned about growth hacking are the same as everyone else’s. One is the professional books written by teachers, and the other is the online case analysis and sharing.

I believe that teachers’ books on growth hacking have popularized this concept, without my need to elaborate. Different industry experiences have different ways of growth. It is important to choose the best ones to read and study and establish basic and systematic concepts. After understanding the concepts and models of growth, you should know that the books are theoretical knowledge and you should not apply them mechanically. Different industries, company resources, and team sizes are all different. You should simplify things and understand and apply them flexibly.

The content about growth hacking on the Internet can be roughly divided into three categories:

1. Disassemble excellent product growth cases and share brief processes and logic;
2. Share your own product growth experience and attach specific growth figures;
3. Share growth hacking concepts and methodologies, and popularize applications and ideas.

It is advisable to learn other product growth strategies and cases to continuously enrich your own content library. But we need to look at this dialectically. The sharer only simplifies and summarizes the case through external data and process screenshots. No excellent product can grow to the top of the market in one step. The wheels of history of failure and success crush it 365 days a year. When you see a successful case, why can't you apply it to your own product? It is because many unknown factors in it cannot be copied or absorbed.

We are often shocked by other people's devilish growth numbers, which stimulate our dopamine and make us think that others are proficient in the way to growth, while we only know one thing and not the other, so we can't play with growth. But when you open the article, you will see that the product itself is large in scale, and the growth is driven by the APP leading to the official account, the official account leading to the mini program, various promotional resources, and the budget being activated back and forth. In fact, you can do it, but the company's budget and traffic are a bit small.

We should learn to deduce and think: how much overlap there is between new users and our own users through our own channels, and whether the retention and payment ROI data performance is reasonable, but most articles do not mention this.

Understanding the concepts and methodology of growth hacking is basic and necessary, but many articles often copy and paste models from books and explain growth according to the AARRR model. This is correct, but we can understand it as internal growth of the product. Growth can be divided into internal and external growth. We should not be fixed in our thinking and understanding by a certain form. As long as the method can drive growth, it is worth retaining and modeling.

For example: There is actually a growth area that is not mentioned in the article: Product matrix growth

For example: maternal and child products. We serve mothers through a matrix of official accounts: -1-1 years old, 1-3 years old, 3-6 years old, etc. The official account content is finely classified and operated, but the purpose is to serve the main product.

For example: my family’s tool products. The core functions only meet a certain category of needs of players. Through user feedback and research, the product matrix can be extended to small market segments such as screenshots, screen recording, download acceleration, making friends, discount information, etc., to cover mainstream users. The purpose is also to increase the volume of the main product, and the development cost of small products is not high.

Back to the topic, when we look at growth rationally, we will not be deified or confused by magnified concepts and numbers; growth exists in our daily work, and there are actually many ways and methods to explore and study it. As long as you seriously put growth thinking into learning practice; most people are influenced by external voices. There are so many sharing and cases that they can’t even read them all, so how can they have time to think about the essence of the product.

Below I share an example of my own product growth. The data is only for case demonstration purposes, and I hope it will inspire you.

1. Set a North Star goal and dismantle the growth model

At that time, the DAU of the product I was working on was around 5,000 at a certain stage, and there would be an increase of 3,000 on weekends due to holidays. However, as the number of new registrations continues to increase, the daily active users have not increased significantly, and have remained stable at around 3-5% of the total number of users, and the monthly active users account for 20-30%, which is at the general level of the tool industry.

Therefore, I will increase the daily active users of the product to 3,000 as the first step of the phased goal. So how to increase the daily active users?

Let's break down the data first:

• Daily active users = new active users + old active users
• Newly added active users = newly added users on the day - newly added unregistered users = newly registered inactive users
• Number of active old users = number of active users on the next day + number of active users for five consecutive days + number of active users for two consecutive weeks, etc.

When you reach this step, you need to think about which point is easiest to break through and test and verify?

• Old users: Based on user attributes and background data, old users have a certain degree of awareness of the product and have developed fixed behavioral habits. The frequency and duration of activity are stable, which is not conducive to rapid breakthroughs.
• New users: newly registered but inactive users. Having completed registration means they have a certain understanding of the product and are in a high freshness period after registration. But why did they not trigger any core functions on that day? Is it because they are not interested in the content/have not found the access function/have high barriers to getting started? Users in this link account for a certain proportion, and the active conversion diameter step is the shortest, so testing and optimization can be carried out.

2. Team storming and developing plans

After setting goals and optimization points, this step needs to be to storm the problems, list hypothetical solutions and set a final implementation plan. Before the team storms, a certain proportion of time should be allocated for market research and collection. In addition to the commonly known ways to increase daily activity, such as clocking in and signing in, are there any other products or new ways of playing worth learning from? These need to be raised in the meeting.

There are two types of market research collection: one is to search for shared cases online, and the other is to directly download well-known APPs from large manufacturers for experience.

I usually use the second approach for the following reasons:

1. Large companies have abundant resources and the latest gameplay or innovations. Although there is a way of playing and learning from each other, new products will be updated as quickly as possible and integrated into their own products, which can relatively reduce the search time cost. For example: get up early and check in to share the bonus pool. Currently, the products I installed on JD Finance, Weibo, and Qutoutiao are all online and in use.
2. The key points of event design and copywriting are worth learning. Due to resource and team factors, large companies will have better layout and aesthetics in UI design and copywriting packaging, which can be used as a reference. Secondly, learning more excellent designs can also improve your aesthetic ability and copywriting design ability to a certain extent.
3. Experience the process steps and sort out the logic. Directly downloading and experiencing the activity functions of the APP can provide a more intuitive and detailed experience, which helps to sort out the activity steps and key factors of each conversion node.

After collecting experience, we sorted out several executable plans. To finalize the implementation of a plan, we need to take into account factors such as product resources and team member schedules. The analysis is as follows:

1. The daily sign-in function needs to give users variable rewards. Currently, the product only has a membership system, without points or mall gameplay; the props are single and not suitable.
2. The check-in and share-the-rewards function requires the establishment of a bonus pool and requires users to pay a certain amount of money. The development cost is high and the product's commercial closed loop is poor, so it is not suitable.
3. Reading gives free time (NetEase Reading APP), users read for 70 minutes per week and get two days of reading time on the weekend; the product itself has a membership system, and only one H5 page is needed for development, which is suitable for the current product and team status.

Solution design considerations: Through data analysis and calculation, we can obtain the weekly and monthly active user frequency and the average duration of each active session. Take the lower average value and set it to five hours per week, with two days of activities on Saturday.

It should be noted that from a long-term perspective, it is not easy to set a high participation threshold when an activity is initially built, which will affect the freshness of the activity and user interest. Secondly, when the new activity covers most of the users and they are aware of it, in the next cycle, the activity will be improved or the threshold will be raised. Users will already have knowledge and proficiency in the steps, so there is no need to emphasize it again. Instead, you can act as customer service in the user group to educate other users.

Keep in mind the three elements of an activity: simplicity, timeliness, and wide coverage.

Activity process steps: Add a pop-up push for registered users - the activity page displays the cumulative active time in real time - default participation, you can receive it on Saturday if you meet the conditions.

3. Build a data funnel dashboard to optimize data maximization

After the implementation plan process steps are sorted out, the team begins to schedule the progress: prototype production - UI design - front-end and back-end development - test follow-up - online release - data tracking.

The data funnel dashboard is divided into two parts:

• Daily number of newly registered users - number of activity pushes - number of activity clicks - number of users who trigger the function on the same day (to avoid data pollution, it can be subdivided into whether there is a triggering behavior within 30 minutes after the user pushes the activity) - number of users who trigger the function on the next day;
• The number of users participating in the activity - the number of users meeting the conditions (the five hours can be broken down) - the number of users who have received rewards - the number of users who participate again in the next week.

The current schedule is as follows: one week for prototype and UI design, one week for front-end and back-end development, one week for online testing data, and two weeks for activity optimization. In addition to the design and front-end and back-end development personnel who need to work full-day, the later data tracking and debugging can be done by arranging personnel to follow up.

The activity is followed up for two weeks because after an activity goes online, there is a period of activity popularity (3-5 days). During this stage, the activity is in the initial exposure stage, and users feel fresh and enthusiastic about participating, which may affect the overall pollution data. Generally, this type of activity requires extending the data cycle and conducting observation tests.

4. All activities are launched online and added to the operation template library

After the activity was launched, it did not reach the ideal state in the second week. The number of daily participants and the number of people receiving activity rewards were relatively stable, and the conversion rate was not high. The investigation found that due to factors such as low push intensity and coverage and imperfect reminder mechanism, users had little understanding, forgot to claim, and no encouragement and reminders were given in the second week. Subsequently, the general push mechanism was optimized.

The reason I say this is to illustrate that no matter how experienced a veteran is, it is impossible to achieve perfect results in all aspects from activity design to process planning to online operation; all require continuous debugging through data feedback optimization. So don’t over-promote cases, just do your best.

After one month, the activity achieved its set goals. At this time, it can be pushed online to all users, and the activity template can be added to the project case library for backup and later review and learning.

In the subsequent optimization process, the activity was also iteratively designed and gamification was added. This was briefly mentioned in the previous article, so I will not elaborate on it here. The functions of internally growing activities will also be upgraded along with product iterations and user coverage (user attributes will also improve as the user base increases).

Summarize

Hacker growth is explained through two parts. On the one hand, we pursue new ways of playing and concepts, and must not be overly convinced by dogma. Everything has two sides, the expressed and the unexpressed. We must think rationally and look at it dialectically. On the other hand, practice is the best way to verify learning. We do not have to copy the entire set, solidify the growth model process, and lock in team thinking. We should simplify, flexibly, and extend the application based on our own product resources and team strength.

Although I am not clear about the work plan of every operations colleague, I think every article, every video, every conversion improvement... are all pushing the product to grow upward.

There is no need for myths about growth. Start with the work at hand and record your own growth path~

Author: Mao Li

Source: Operational Growth