The cost of acquiring customers is getting higher and higher. How to build a complete user operation system?

How to do user operations ?

In fact, most colleagues engaged in operations have different methods. As for operations, it is nothing more than attracting new customers , promoting activation, improving retention , increasing orders, and increasing turnover, etc. For different operational purposes, each senior operator has different operating methods.

Below, I will introduce a user operation system transformed through the RFM model . It is also the author’s recent experience. Experienced operators please take a detour.

01 Define different levels of user types

Different types of users

Here we can distinguish between two dimensions: horizontal and vertical.

For example: (data range: data from 1.1 to 3.1 months)

Horizontal: Differentiate according to user consumption frequency (maturity), such as:

1. Primary users: Consume 1-5 single users.

2. Growing users: Consume 6-10 single users.

3. Mature users: users with more than 10 orders.

Vertical: differentiate by user activity, such as:

1. Active period: users who have made purchases in the last 4 days.

2. Decline stage: users who have not made any purchases in 5-10 days.

3. Churn period: users who have not made any purchases within 11-20 days.

4. Death period: users who have not made any purchases for more than 20 days.

In actual situations, a primary user & active period may mean that the user has made less than 5 orders in the past two months , but the user has made purchases in the past three days.

Data requirement table reference (click on the picture to see the enlarged picture)

Note: Here you can see the first three columns, and the last two columns are for data reference.

The above are just examples (mostly e-commerce type businesses). The consumption frequency and activity of users may be different in different industries and businesses. It depends on the specific business.

02 Develop a corresponding user system model

Through the above user definition, we can draw the framework of our entire user operation:

User operation model diagram

Note: This model was inspired by a great article.

The above diagram is simple and easy to understand, and our goal can be broken down into:

1. Primary users are transformed into growth users, and growth users are transformed into mature users;

2. Wake up dormant and lost users and turn them into active users;

3. Through the above two methods, a closed loop is formed.

A few small details are key elements:

1. Since primary users are not familiar enough with the product, there may be a high rate of churn and dormancy among them. Special analysis and operations are required for this group of users.

2. After the growth and maturity stages, special attention should be paid to lost and dormant users.

Especially for the churned users in the mature stage, most of these users have become our loyal fans after long-term maintenance and a large amount of resource expenditure. If the churn data fluctuates greatly, we must set up a project to conduct special research. The people in charge of this area must go further and communicate in depth with these users to find out the real reasons, rather than just guessing the reasons by looking at the data in the office. The results of the analysis must be repeatedly verified with real users.

3. Of course, the most important thing about a detailed analysis of the user system is to prescribe the right medicine, reduce the budget and increase conversion.

Therefore, the operational strategies and methods may be different for different types of users.

03 Specific operation methods

First of all, we can use the above model to mine the corresponding user data.

Let me digress here: many students may have a headache about obtaining this batch of data. Especially for start-up companies, there is no corresponding data platform at all.

So here are 3 suggestions:

1. Export the corresponding order data source table through the background, and process it by yourself through tools such as Excel (the specific Excel method will not be repeated)

2. Communicate with the developer who manages the database and export it through SQL statements. (It’s convenient, but it’s not good to disturb others frequently.)

3. If this system is finalized, be sure to communicate this requirement with product managers. Personally, I think this aspect is very critical. Data is the basis of operations. Having a strong data background will save a lot of workload and improve work efficiency.

The following exports the corresponding data:

Specific data (for example reference only)

Based on simple data analysis , you can try the following operational actions:

1. Primary users are the most likely to be dormant or churned. You can apply for a batch of combination coupons to wake them up. For example: one high-denomination, low-threshold coupon and one low-denomination, low-threshold coupon for activation, and a reminder of coupon expiration (the meaning of two coupons is to allow users to stay longer and spend more. Try to extend the time of using our products);

2. For users in the growth stage, they are relatively familiar with our products. We can set up consumer rebates or issue coupons of medium denominations, and push corresponding copywriting based on their purchasing habits;

3. For mature users, focus on those in the churn and dormant periods. Customer service can be arranged to conduct random interviews to understand the reasons for the loss, and apply for a batch of coupons or gifts (requires product redemption) as rewards or apology compensation, etc.;

4. The purpose of growing and maturing users during the active period is to increase the average spending and frequency of users. Therefore, you can issue some low-value, higher-threshold coupons and push popular or hot-selling products.

The above are just some methods listed by the author. Specific actions need to be determined based on the business and specific data feedback, but the general form can be used as a reference.

Through cross-analysis of multiple dimensions including primary, growth, maturity, active, decline and dormant, we can always identify problems and formulate corresponding operational strategies.

04 Operation cycle and push method

The user operation system requires long-term operations. The specific actions may be adjusted based on data feedback during the process, but the methods and general direction should basically remain consistent.

Of course, depending on the different businesses, the operations will vary.

Take e-commerce business as an example:

In e-commerce business, different user types have different operation frequencies. like:

For users in the death period: data will be collated once a month/half a month for issuing coupons and push notifications, etc.

Users in the churn period: These users are on the verge of death and need to be analyzed every 3 days/7 days for operational activation.

The key point is that after you perform an operation on a group of users, you need to conduct corresponding tracking. If you observe the corresponding data conversion after one week, as well as the proportion of this batch of data at each level in the new time dimension, it will also be convenient for you to make corresponding reports and summaries.

For example, after conducting the above analysis on the data of the previous two months on March 1, in the data retrieved in April, the situation of the March data in the latest data can be used to evaluate your operating results and guide subsequent actions. At the same time, you can also analyze the effects by comparing daily activity, retention and other indicators by combining multiple maintenance.

This aspect may be another article to discuss in detail. Let’s put aside factors such as time and frequency. Here are some simple strategic suggestions:

1. Push discounts to primary users and deceased users to guide consumption;

2. Push notifications to growing and mature users: Push corresponding hot items, featured products, product activities, etc. based on user data feedback;

3. The shorter the user guidance link and jump method after push, the better.

05 Summary & Conclusion

Finally, let’s briefly sort out the methods described in this article:

1. Carry out detailed stratification of our product users.

2. Develop corresponding user models (application of RFM model)

3. Collect corresponding user data based on the established model.

4. Formulate corresponding operation strategies through data analysis.

5. Operation cycle, push method and evaluation criteria for data effects.

When we do user operations, we must determine the goals. Whether it is promoting activation, improving retention, increasing orders, increasing average customer spending and increasing turnover, there are differences in the specific operational actions. Be sure to remember to prescribe the right medicine for your condition, set 1-2 goals, and proceed step by step. The subsequent review and analysis must also be conducted carefully, with statistics done and timely adjustments made.

Of course, the RFM model also factors in a user’s spending amount. You can also take this metric into account when you need to stratify your users in more detail. Then weighting the data may yield different results.