In the past few years, because of the popularization of mobile Internet, many companies can get good profits even if they do it casually, but with the fierce competition in the market and the growth to the peak, various enterprises have begun to realize the importance of refined management and pay more attention to data. This article explains the data analysis of Shuhe in operation, hoping to help you better do a good job in refined operation.
Recently, I started a job search every few years, and I just took this opportunity to sort out the various methods that I have summarized in various sections of my work in the past.
Today I want to share the content related to operations, because different products are driven by different things according to my understanding, such as Xiaomi's Su7 recently, he designed the product as if he thought about how to do the publicity and operation, and his model is similar to the Laifen I shared last time, which is very interesting. Recently, I heard an interesting point of view that a product that understands product design is not necessarily a good product, and a product that understands operation is not necessarily a good product, that is, a person who understands the product and knows how to operate is a really good product person.
Operation contains a lot of parts, this time the main focus is on how to do data analysis in the operation, because in the past, because the market was very large because of social reasons, so many enterprises even if they did extensive experience and management still got good benefits, but now the environment of various enterprises began to realize the importance of fine management, pay more attention to data, although this article will not be how data drives the fine operation of enterprises, but if the enterprise is also a product, the operation thinking of the product can not be used in the business operation!
There is also an interesting topic, how operations drive product design, and I plan to open a new document to talk about it later.
1. Product thinking > data thinking
When we design a product and function, we usually go through the following steps, according to the general model, the product function design should include the amount of data, but in most cases, because of the company's culture, product characteristics, etc., the data is not easy to monitor or everyone does not pay attention to it, resulting in a lot of people who have been making products for several years still do not realize the importance of data:
2. What are the data indicators and how to design them?
2.1 What indicators will be paid attention to in general operations?
What is the use of data, according to my understanding, is to divide many people into different groups through data, and then the company will be managed according to the overall characteristics, and the goals of management will be different due to the difference in product life cycle and product type.
Here's a simple list of metrics you need to get:
Notes:
- User stratification: Distinguish who the core users are, because they are the group you need to focus on, because after all, 20% of users generate 80% of the company's profits
- For example, if a consulting platform recently added some new consulting directions and found that the number of inquiries increased by 20% this month, it is necessary to analyze whether it is caused by seasonal factors and whether it is because of some drainage operations that have led to the increase in the total number of users, and what is the proportion of users who use the new consulting content
- Be clear about what you want, because with expectations you have the direction of optimization. This value usually requires a certain amount of industry accumulation, so you can ask relevant people or read some industry reports such as iResearch Consulting and other products.
2.2 How do you design what data needs to be acquired and in what circumstances?
Because of this big guy's article, I think it's very well written, so I won't go into too much detail about this module, you can take a look at the big guy's document: https://zhuanlan.zhihu.com/p/293279922, he explains the whole process in great detail and professionally from the business goal - > user path - > data indicator system design - > buried solution design - > requirements document output.
3. How does case + data analysis guide operational and product decision-making?
Background:
Suppose there is a psychological testing platform, which currently mainly generates revenue by selling a single psychological counseling test, and now wants to make a function to increase user retention and increase product revenue
Problems found:
Through the analysis of data analysis and the analysis of historical data in 2023, it is found that the average unit price of paying personnel = 14.37, the number of annual paying people is 11470, and those who are willing to pay for the test are inclined to do the second test, and the interval between the two tests is less than 5 days, and the price of the product tested by those who are willing to test multiple times is generally higher than that of those who only conduct one test.
Analyze the problem:
Ideal: User retention, we want users who originally planned to do it only once, and users who are willing to do it a second time, and users who test multiple times in 5 days and are willing to buy a higher price product, we want them to test a higher price product
Proposed Solution:
Cost:
Considering that the psychological test product is a product that can be used repeatedly after a test, the cost of the product itself is not high, but the more people who use it, the smaller the cost of the product to each user, so the design of the product scheme does not need to consider the construction cost of the psychological test questionnaire, and the main focus should be on the functional design and R&D cost.
Psychology:
Human beings like discounts, and there are factors such as the barrier to entry effect, so different membership products can be designed for them to buy according to the type of user
Product design:
For users who have never made a purchase, they can use social networking such as inviting others to discount, or building a psychological community, and get points for psychological test opportunities by sharing personal daily experiences (but you can't give away the test for free, it is best to let users pay even if they only pay 0.99) and other strategies that can be considered, which can be used to increase the user's customer unit value and retention rate
For those who only do one test and are price sensitive, a new 14.8 yuan monthly membership allows users to test all products worth 0-10 within a month, and in order to prevent users from testing others, they can require each test question to be tested only once.
For users who have done test questions for many times in a row and the price of the questions is relatively high, 29.8 monthly membership products have been added
For users who have never made a purchase, of course, in addition to the membership mechanism, there are also social networks such as inviting others to discount, or building a psychological community, and obtaining points for psychological test opportunities by sharing personal daily experiences and experiences is also a strategy that can be considered to increase the user's customer unit value and retention rate.
Productization:
After setting the functional direction, you need to combine the functions to prototype the product and the indicators that need to be monitored, such as the number of purchasers, and the products purchased, and also need to evaluate the role of the new functions, such as the month-on-month GMV change rate, mainly as shown in the following business indicators:
References:
https://zhvanlon.com/p/293279922
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