4 dimensions, detailed explanation of refined operations!

The mobile Internet attaches more importance to traffic than anything else. Without traffic and users, how can we talk about business model , let alone poetry and distant places? The cost of attracting new users for an app can be as low as a dozen yuan, or as high as dozens or even hundreds of yuan. In addition, with the explosion of mini-programs and the establishment of WeChat OS, the APP ecosystem is facing internal and external troubles.

An important indicator of the health of an APP is whether its ability to acquire new users meets the following criteria: revenue - customer acquisition cost ≥ 0 yuan. In order to ensure the normal operation of the APP, we usually start from reducing customer acquisition costs and increasing GMV. Although reducing customer acquisition costs can be achieved by finding new channels , the distribution of traffic has shown an oligopolistic trend, and costs will only get higher in the future. Therefore, increasing GMV has become an important task in APP operation. ,

As the user base continues to grow, it will be difficult to meet users' personalized needs by relying on only one strategy or a single function, which will lead to low user activity, poor retention , and low paid conversion . Therefore, "valuing every opportunity to interact with users and conducting refined operations" has become the core of increasing GMV.

What is refined operation? It can be understood as a differentiated operation strategy based on big data , focusing on users, scenarios, processes, and products.

So how do you proceed?

First, focus on the user

The first step to carry out refined operations is to understand users . Only by understanding users can we provide targeted and personalized services and achieve differentiated operations for each individual. Among them, "labeling" users is a common means of understanding users, such as:

Product Manager (Job Type)

Female, Product Manager (gender + job type)

Beijing, Female, Product Manager (Region + Gender + Job Type)

…

The more label dimensions there are and the finer the divisions, the more comprehensive and accurate the user portrait that can be constructed will be.

To refine user labels, we need to understand user preferences in different dimensions and then analyze the user clusters represented by their characteristics. For example, in the figure below, by setting up three sub-sets of attribute tags, interest tags, and scenario tags, an accurate user portrait was obtained through big data analysis .

However, the key to the problem lies in how to accumulate more user tags. The following are several methods commonly used by operators:

1. Collaborate with the company's R&D department to retain and record effective data one by one.

For example, front-end group access, clicks, browsing, etc., back-end ordering, payment, etc. and data research and development can use IP database collision to identify labels such as region, model, and system;

2. With the help of survey questionnaires.

For example, to test the entire platform, randomly select 3 or more groups of users (with a sample size of no less than 1,000) to push questionnaires at different time periods, and then collect the questionnaires for data processing and analysis;

3. Use professional third-party analysis tools .

For example, Zhuge.io, Getiang (a new user portrait tool launched by Getui), ShenCe, etc. Compared with the first two methods, professional analysis tools can usually supplement the APP's own data based on massive big data, making the labels more comprehensive and the constructed user portraits more accurate, so many operators choose third-party analysis tools.

Understanding users is the basis for refined APP operations. For example, by understanding user characteristics, you can recommend different content to different users, find user groups that are similar to the target users , and use the characteristics of similar user groups to recommend content to the target users.

(The impact of user tags on daily operations)

Secondly, we should make good use of operational means

According to the 80/20 rule, 80% of users will only use about 20% of the functions in the app, while the remaining 80% of the functions require operations staff to use operational means to strengthen user awareness and guide usage. For example, for insurance apps, users usually stop being active after purchasing insurance, because insurance itself is a service that only takes effect when a disease occurs. Therefore, Apps should usually provide users with content that they may be interested in through message push, thereby guiding users to open the App to view and increase activity. This has become an effective means of daily App operations, and of course it is also a very important action for refined operations.

The first thing to consider when pushing App messages is user stratification, that is, who should it be pushed to?

The "users" referred to in refined operations usually refer to "user stratification" . It is to split users according to different dimensions, show different copywriting , landing pages , etc. to different users, and improve conversions at all levels. At the same time, remember that user attributes are fluid, from new users to retained users, which can be further divided into active users to lost users. According to payment standards, they can also be divided into paying users and non-paying users.

So how to use "user stratification" to push to improve APP activity? For details, please see the following example:

Judging from the opening rate, the copywriting of "inviting and giving money" is most effective for low- and medium-quality users; the second group of copywriting of "giving users spiritual rewards" is most effective for high-quality users.

By comparing the data, we can intuitively feel the different performances of users at different levels after receiving content push.

Of course, there are still some problems in the actual process of message push:

1. Push notifications require filtering users, but there are no clear user tags and user groups. Every time you export users to be pushed, you need to retrieve them from massive data;

2. The push may be delayed and cannot be pushed at the scheduled time;

3. It is difficult to manually control the time of pushing news, especially at certain time points. For example, most people are used to reading news on their way to work, but there is a group of people who are used to reading news at 6:00 in the morning.

4. It is difficult to accurately match the scene. For example, when a user enters a restaurant, the APP can accurately push the corresponding coupon information;

For these types of problems, if the company has its own push system, it also needs to prioritize and then determine whether there is resource support, development cycle, etc. This is time-consuming and labor-intensive, so relying on third-party push is the choice of most companies.

(Push capability of individual push)

Getui is the preferred partner for many developers. The push function can be seen in the picture above. Recently, Getui has also launched new features, such as integrating SMS and other multimedia push channels to diversify the ways of message delivery. For example, it breaks through the limitations of push scenarios and enables information connection between users and smart home appliances and IoT devices. These can be said to be new explorations in the field of message push, making push more valuable.

Third, start refined operations from the process

The process is to think about the operational steps of APP operation using funnel thinking. There are three important points to consider when implementing refined operations from a process perspective:

1. Data-driven;

2. Manage user expectations;

3. Page step management;

【Data-driven】

In the early days, there was 2A3R (Pirate Index Model), which calculates the churn rate through the conversion rate of users at each level of the product page, so as to quickly find out which level of the page has a problem and propose a solution.

(Pirate Indicator)

However, today's APP's demand for data is no longer just satisfied with the use and analysis of basic data, but has put forward higher demands for industry analysis, uninstall analysis, etc. This capability requires support from data outside the App, so many App operators choose to cooperate with third parties with large data volumes and strong data capabilities.

(Analysis of product uninstalls by number)

As shown in the figure above, "Geshu" (a data statistics product under Getui) provides a variety of data analysis functions, among which uninstall analysis deeply analyzes the reasons behind the "uninstall number", which is very practical for daily operations.

Managing User Expectations

This can be explained by a question: When a user sees your push, how does he understand it?

For example, the following app push.

When I saw this push, my understanding was how the operation of Meituan affects people’s consumption habits, work status and the operation of the capital market.

If what I see when I open the app is not what I understand, but an inspiring article telling everyone to work hard, etc., then my choice is to quickly close the app and most likely uninstall it.

This is from the reach level, and there are several points that need to be considered for each level of page below.

1. Does the user know what information I want to tell him?

2. Do users understand?

3. What do users understand?

4. What should he expect the next page to be?

5. Why should he look at the next page?

【Page step management】

If the page can be concise, don't have too many.

Every additional page, especially the later ones, means nearly 30% of traffic loss. For example, the case of "membership renewal service process" management:

The usual process for renewing membership services is: being informed that renewal is required -> viewing the renewal landing page -> clicking the renewal button -> displaying renewal user details -> placing an order and paying -> payment successful. There are 6 steps in total.

Display the renewal user details on the renewal landing page and streamline the [Display renewal user details] page. Just by removing one page, the renewal rate increased by as much as 10%. Considering the user base of millions, increasing renewal by 10% will have an amazing effect on conversion.

Fourth, we need to make refined operations “systematized”

Whether it is data management or message push, when the size of the APP is not large, it can be solved manually, but as the size of the APP continues to grow, a complete operation system is needed.

Category 1: Your own company builds a database and push system, creates user tags based on the fields in the database table, exports the desired user groups based on your needs, and filters the combinations yourself.

Category 2: Use Sensors Data, Getui, Zhuge IO , etc. to provide developer services based on big data.

As for how to choose between these two categories, I think we need to make a judgment based on the company’s current stage of development.

Category 1: self-built database and push system/ user portrait analysis platform, etc. Its advantages are:

1. It can ensure the security of data;

2. You can understand segmented user preference records;

3. Ensure the complete ownership of data;

4. Internal communication efficiency and service stability are guaranteed;

But there are also many disadvantages:

1. High cost. To build a database yourself, you first need to ensure that the staff is fully equipped. At least four necessary roles must be in place: data development, data product, data analyst, and product operation that understands SQL. Secondly, you need to use cloud storage. Cloud storage such as Tencent Cloud, Alibaba Cloud, and Huawei Cloud basically cost hundreds of thousands to millions of yuan.

2. It takes a long time. For example, if you write SQL push by yourself, you need to repeatedly verify the accuracy of SQL and the accuracy of exported users. Even a simple push may take at least half a day for two people. In addition, the self-built push system does not have integrated user tags, so it needs to be re-coupled every time.

3. The functions are not perfect. Generally, the company's push platform does not have data visualization function. If necessary, additional manpower will be required to conduct analysis to deduce the next step. If you can integrate data displays at all levels, such as access funnels, message reach, and order completion, you can save a lot of time, but this requires very high development capabilities.

Therefore, when a company is in its start-up phase and has a small amount of data, for example, less than 5 million users, I suggest using a third-party service platform to meet current usage needs. When the company's user base exceeds 10 million, it can combine its own database with a third-party platform to better improve efficiency based on actual conditions.

There are many third-party service providers who are developing new products based on the needs of APP operators. GeTui mentioned above has recently upgraded its original push products to meet the needs of refined APP operations, and launched two new products, "GeXiang" (user portrait) and "GeShu" (data statistical analysis). By connecting the functional modules of message push, user portrait and application statistics, it has established a refined operation service system driven by data intelligence and scenarios. If you have any needs, you might as well try it.

Final summary:

1. You need to have a good balance between relaxation and hard work. You cannot blindly pursue refined operations. You need to consider the current product cycle and which business you need to focus on. You also need to consider the support capabilities of the team itself.

2. Targeted and refined operations. For example, there are four major categories: new users, active users, silent users, and churned users. We need to focus more on new users and active users, followed by silent users, and finally churned users.

Judging priorities does not mean doing everything to achieve refined operations.

Doing high-leverage things and refined operations are not only for users, but also to create more value for the APP.