User operation is centered on user needs, maximizing the active reach of users and achieving the expected operational results. So, how to do user operation? This article summarizes the relevant steps, let's take a look.
User operation is mainly user-centric, taking the needs of users as the first starting point, setting operational goals and formulating operational strategies, and continuously reaching users (welfare activities, user experience, etc.) through scientific and systematic operation methods to achieve the expected operational results.
There are many methodologies of user operation, such as RFM model, user path analysis, user life cycle, etc., and now I want to introduce another kind of thinking of user operation, through the dismantling model to find the user group to maximize the benefit of the force point, to complete the user operation goal.
01
First of all, let's understand what is a dismantling model?
The dismantling model is to subdivide a wide range of targets that cannot be implemented into specific indicators until they can be implemented.
In daily work and life, what can quickly get a sense of accomplishment is generally some small goals, such as completing a data analysis report, doing a good job in room hygiene, etc., but for tasks that seem particularly difficult such as processing 100 reports and losing 30 pounds, you are not willing to do it, at least not immediately;
So how can you make your goals more achievable?
You can disassemble 100 tables in time cycle and quantity, the goal is to complete it in 10 days, then you can complete 10 tables per day; lose 30 pounds, then you can set a 5-month cycle, lose 6 pounds a month, lose 1 pound a week, etc., and continue to disassemble and refine from diet, exercise, etc., so that the goals and strategies are landed;
What are the steps to dismantle the model when it comes back to operations?
The first step is to define the business focus indicators, which are often referred to as the North Star indicators, and the specific directions are as follows.
- An indicator that can reflect the upward development of a company or department
- It can reflect the user's activity level (or attract new users, etc.)
- It can reflect the core value of user experience products, such as e-commerce is purchase, and social networking is instant messaging
- If it can be viewed intuitively, absolute data is generally selected as the North Star indicator
- Metrics are operational
It can also be understood here that the indicators for which you are responsible, such as active volume, paid volume, etc.
02
The second step is to build a disassembly model, and after determining the goal, the target is modeled.
1) Confirm the 3 operating elements
- Output variables: key indicators (North Star indicators), which can be understood as indicators for which you are responsible
- Input variables: Find out what are the relevant factors that can influence the key metrics
- Equations: Derive the relationship between these variables
2) Sort out the user behavior journey
Drawing the user journey is to take the user state represented by the North Star indicator as the goal, and sort out the user's journey to reach the goal;
For example;
Taking an e-commerce product as an example, we take "sales" as the North Star indicator of the app, so as to draw the user's journey;
Download the APP - Register - Browse Products - First Time - Continuous Login - Continuous Purchase
3) Horizontal and vertical dismantling of key indicators
Horizontal disassembly:
Sales = Sales of new active users + Sales of existing users
Longitudinal disassembly:
Sales of new active users = number of downloading users× registration rate× proportion of first-time views× first-time purchase rate× per capita output value× unit value of new users
Sales of old users = number of existing users× proportion of continuous logins× purchase rate× per capita output value
Mathematical Formula Integration:
Sales = Sales of new active users + Sales of old users = (downloads × registration rate × proportion of first-time views × first-time purchase rate ×per capita output value) + (number of old users × proportion of continuous logins× purchase rate × per capita output value)
The following uses a specific user operation case to illustrate the application of the dismantling model.
Operation scenario: The sales volume of an e-commerce APP product in April is 600w, and the goal is to increase the sales to 700w in May.
- Sales of new users and sales of existing active users increase
- Sales of new users are declining and sales of existing active users are increasing
- Sales of new users increase and sales of existing active users decrease
In view of the above three situations, the three-level indicators of new and old users can be analyzed respectively, and the sales indicators can be disassembled;
- New users: downloads, registration rate, first-time view ratio, first-time purchase rate, per capita output value
- Existing users: the number of existing users, the proportion of continuous logins, the purchase rate, and the per capita output value
1) Based on the indicators of the dismantled model above, fill the business data into the model (non-real business data, for reference only)
Question: The sales volume in April is 600w, and the company wants to increase sales by 700w in May by planning activities, so how to improve performance through user operation?
2) Sort out the indicators that can improve operations
- Direction 1: Increase the number of new downloads from various channels
- Direction 2: Increase the registration rate of new users
- Direction 3: Increase the purchase rate of new users
- Direction 4: Increase the purchase rate of old users
- Direction 5: Increase the average order value of new users
- Direction 6: Increase the unit value of old users
Note: Due to limited resources, it is impossible to improve all indicators, and it is necessary to evaluate the most effective indicators or user groups to carry out the formulation of operation strategies;
3) Evaluate the effectiveness of the improvement indicators
Evaluation logic: Considering the scale, market conditions and cost of the platform, the increase in the registration rate of new users/the purchase rate of new and old users is about 10%;
6 user operation strategies are sorted out as follows (the following business data is non-real platform data and is for reference only)
Through the above strategies, the target of 700W can be achieved, but the maximum benefit evaluation needs to be done:
(1) The first 4 projects need to be added to the market to attract new users, the cost of investment is too large, and the existing maintenance cost is high, which can be excluded;
(2) Project 5 needs to increase the purchase rate of old users from 60% to 70%, which is basically difficult to achieve for mature products, and the cost and difficulty are very large;
(3) Direction 6 will increase the unit price of old users by 3.5 yuan, the total sales increase will be very obvious, and the implementation direction of the operation strategy is more feasible (under the condition that the user path function of the e-commerce platform cannot make a big breakthrough in a short period of time)
Conclusions of the evaluation: items 6> 5> 1/2/3/4
4) Develop operational improvement strategies
Through the above dismantling and analysis, increasing the unit value of old users can greatly increase the overall sales, and the team can concentrate resources to focus on improving the average purchase amount and purchase frequency of users.
(I won't expand it here, but the strategy is mainly executed by platform type, which can be continuously controlled through A/B testing and user experiments, and it is necessary to pay close attention to data changes, and the data cycle is as detailed as possible to "hours")
Conclusion
By dismantling the model to determine the feasibility of landing and the user group that maximizes the benefit, it is a more systematic and scientific way of thinking for user operation, which can continue to iterate the user operation system in practice and achieve twice the result with half the effort.
This article was originally published by @大灰熊 on Everyone is a Product Manager and is not allowed to be reproduced without permission
The title image is from Unsplash and is licensed under CC0
The views in this article only represent the author's own, everyone is a product manager, and the platform only provides information storage space services.