Before I came into contact with the working methods of growth hackers, I always thought that growth hackers were very metaphysical. Modifying a button copy or adjusting the background color of a page can bring about a huge increase in revenue.

We often see some Silicon Valley growth stories in the industry, and there are also many voices saying that "Silicon Valley's approach" is not suitable for us and is incompatible with local growth. Throughout my entire product career up to now, I believe that the working method of a growth hacker team is a more scientific and effective growth method.

We are not deifying "growth hackers" here, nor am I advocating that you just modify the copy, adjust the background color, and wait for tens of millions in revenue. Instead, I think the workflow and problem-solving mindset of growth hackers are worth learning. Let's talk about the actual growth of a content information product from 0 to 1, which can be summarized into five steps and shared with you. Because the relevant business is sensitive to privacy, the relevant indicators will be blurred.

Step 1: Identify your North Star Metric

Since our mission is to revolve around growth, we are not simply taking chances by changing module A today and module B tomorrow. Instead, we have a relatively focused direction so that all team members can work towards the same goal.

Don't think that you can achieve growth by taking one step at a time and walking steadily. Sometimes you choose the wrong path and go in the wrong direction, and every extra step you take will be a reason to get beaten.

So there is no doubt that the first step is to find the "North Star Indicator" of the product. The term "North Star Indicator" is not unfamiliar to those who have been exposed to growth. This is the first step in growth and an extremely important step. There are many books and related articles that will explain the North Star Indicator in detail. The approach I personally recommend is to first list the product's business goals and user value, and finally collect a series of indicators through internal solicitation, and then screen out a suitable North Star Indicator from them. The screening factors can be based on the following six factors.

1. Allow users to experience core value

2. Can it reflect the user's activity level?

3. If the indicators are improved, will the company become better?

4. Is it easy to understand between teams and across departments?

5. Is it a leading indicator, not a lagging indicator?

6. Is the indicator easy to break down and easy to execute?

Finally, based on the product’s business goals and user value, we listed the number of weekly active users, the number of paying users, and the number of weekly news views. We then screened them based on the six elements of the North Star Indicator and found that “total number of weekly news views” was the most appropriate North Star Indicator at the moment.

Step 2: Derive the Growth Formula

After determining the North Star indicator "Total number of weekly news views", the second step is to break down the North Star indicator and obtain a structured formula, that is, which variables mainly affect the North Star indicator and how the variables are calculated to equal the North Star indicator.

Total number of weekly news views = X * Y

There are many ways to deconstruct the growth formula, and it is always centered around the North Star indicator to simulate the user role process. From the entire process from the initial point of a new user to the end point of reaching the North Star indicator, you can deconstruct the growth formula for the North Star indicator of the product business.

After the simulation character runs through the process, the following growth formula is finally obtained. Each variable can be continuously decomposed until it can no longer be decomposed. All the North Star indicator growth points of the product are included in the formula.

Back to your own situation, derive the growth formula based on the current business and North Star indicators, and break down the variables in the formula. At this point, all growth points are clear at a glance. Which indicator's increase will bring about which changes? The entire team and even the company will be very clear about which indicator depends on which factors.

Step 3: Find the growth levers

Once you have derived the growth formula and found out a lot of growth points, don’t think about “breaking them down one by one” at this time. This will cause the team to lose focus and fail to maximize efficiency and output.

It is also possible that because there are so many things that you can do, you may not know where to start. This is when the power of the growth formula comes into play.

The key to achieving effective growth is not to do many things at the same time, but to find the one or two things that currently have the most critical impact on the growth rate. The growth formula solves this problem very well. The growth lever allows us to focus on improving the largest part of the space, thereby maximizing the effect.

"Give me a suitable lever and I can move the earth." The growth lever in the growth formula is the "fulcrum".

The source of growth leverage is to decompose each variable of the growth formula and search for data indicators under each variable. The ones with the greatest impact and the largest growth space can be defined as growth leverage. Therefore, finding growth levers is very dependent on search data, and it may take some time to build them.

Back to our own situation, based on the data under each variable of the growth formula, we can derive the performance of the current North Star indicators and variables.

A preliminary check shows that the paid members' information viewing performance is quite good, so the current problem can be located under the "number of views by trial members". According to the viewing situation of trial members, the performance of "view ratio" and "average number of views per person" has a large room for growth and is highly operational. Therefore, in a short period of time, we can focus on the information viewing of trial members to conduct relevant growth experiments.

Step 4: Create an idea library

After the first step of obtaining the North Star indicator, the direction is clear. After the second step of breaking down the North Star indicator to obtain the growth formula, the growth framework is also available. After the third step of digging out the growth levers based on the growth formula, the current focus is also available. At this time, the growth team can propose hypotheses for the growth levers and establish an experimental idea library for rapid verification.

Because the experimental ideas are proposed and summarized by all members of the entire growth team, in addition to having a clear understanding of the core indicators and growth formulas, members need to make the ideas in the idea library more "scientific" and screen and sort them based on the following three dimensions.

Impact: How much impact can this thing have on the present or future? Is it expected to increase by 10% or 80%?

Difficulty: How much resources are needed to do this? Can it be completed and tested in a few hours or will it require weeks of effort?

Confidence value: How confident are you in achieving your goal by doing this thing? Is it supported by data or just a flash of inspiration?

Finally, after weighted average, high confidence, high impact, and low cost priority are undoubtedly the highest.

Back to our own situation, we discovered that the growth lever is the number of information views by trial members. We focused on the two factors of "viewing ratio" and "per capita" to build an idea library, proposed experimental plans, and screened them according to "influence", "difficulty" and "confidence value".

Pip Name:

1. Increase the proportion of registered users viewing on the same day

2. Increase the number of views for trial members

3. Trial members can be activated without any frequency

4. Recall of expired trial members

…..etc

Experimental ideas:

Optimize the successful registration landing page, recommend relevant information and guide subscriptions. Because landing pages are a simple and easy way to match needs, improve the matching degree between core content and user needs, shorten the experience path, and increase the conversion rate of core actions.

….

Step 5: Continue experimenting and monitoring

During routine experiments, the experimental subjects and experimental groups that require AB testing are planned. The experimental subjects can be tested on a small number of users first and then the scope of the experiment can be gradually expanded. As long as the experimental plan meets the requirements of a single variable, multiple groups can be compared at the same time. The optimal experimental plan can be obtained more quickly based on the comparison results. However, it is not recommended to conduct multiple tests at the same time to avoid mutual influence.

Subjects:

Huawei user mobile terminal, Android version is 3.3.1

Experimental version:

Original version: Users maintain the original product flow and interaction when viewing news details, and the subscription entry button remains unchanged

Experimental group A: When the user stays for more than 5 seconds while viewing the news details, the subscription entry button will cycle for 3 seconds to zoom in and out

Verify whether exposure to the subscription button increases user clicks on the subscription button.

Experimental group B: When the user stays for more than 10 seconds while viewing the news details, the subscription entry button will cycle for 3 seconds to zoom in and out

Verify whether the length of time users spend reading information affects their subscriptions.

After the experiment, the following conclusions can be obtained through AB testing third-party tools:

In routine tests, each module of the product should be more flexibly configurable. As much configuration as possible can reduce R&D investment and maintenance costs, and can also enable experiments to be conducted more quickly. If a creative experiment must be conducted based on a "release version", that would be a shame. Accessing and building an AB platform can also enable experiments to be conducted more quickly.

When it comes to setting up and developing resources, the working method of the growth team is not friendly to certain types of companies. This is because the working method of the growth team has certain requirements for speed and efficiency. If obtaining data is very cumbersome, it is not suitable for the growth team's workflow, because the initial point of growth is data analysis, and the end point of growth is also data verification and conclusion. If even the data dashboard has not been built, it is not recommended to use the growth team process to work, because it is difficult to look at the data and the efficiency is really slow. Building a data dashboard is the cornerstone of the growth team, and AB testing tools are weapons.

at last

The essential quality of an excellent growth team is a growth mindset, which means not being afraid of failure and having the courage to try. Practice does not lead to true knowledge, but it can summarize and feed back from each experiment to the next, constantly discovering and solving problems. This is not just growth in product data, but also growth in personal product career.

Author: Chief Bragging Officer

Source: Chief Boast Officer (ITman-99)