Some entrepreneurs often hear about "building a data analysis system" to build a super product, but they don’t know how to build a system. Today I will come to everyone to answer systematically. How to build a data analysis system is a must for a company to build a super product. Part of the preparation.
01
In the process of building a data analysis system, many people make mistakes
1) Can not find the point
Many people will lay down a large number of indicators in the process of data analysis. Which one to look at first, and which one to look at later, but can't tell the key points. It takes a lot of time to look at hundreds of indicators, let alone analysis.
2) Greed for everything, regardless of responsibilities
Regarding users, products, data, new media, activities, communities, channels, commodities, etc., as a set of indicators, these seemingly large and comprehensive aspects actually need to be subdivided, rather than all of them. Treat it as a set of indicators.
3) Fall into details, no goals
Many people habitually list indicators and split them according to time, channel, region, and user level. Finally, they find that there is no specific standard for the problem, or even no problem.
02
How to build a data analysis system correctly if you want to build a super product
1) Data analysis: You can't just list the data, but interpret the data, interpret the meaning behind the data, and find the corresponding product.
2) System: It means that data cannot be laid out without logic, but data is presented in a primary and secondary order, so that the key to the problem can be quickly found.
Only by connecting the data situation in series and applying it to product innovation can we build a real data analysis system.
03
Clarify goals and build the purpose of data analysis system
We must understand that the essence of data analysis is to serve users, as far as possible to let products bring value to users, do not waste user time, in order to bring a good user experience, thus creating a super product. Therefore, before building a data analysis system, we have to ask ourselves:
1) Who do we serve?
2) How to analyze data to better iterate the product
3) At what time can help users be provided and can interfere with them less?
4) Understand the market environment
This is the basic idea of building a data analysis system to create a super product.
04
How can companies build super products
Step 1: Find the core user group
This is very important. Even if it is the same problem, the needs of different user groups are different, but the enterprise cannot satisfy all user groups at the beginning. Therefore, it is necessary to distinguish which users are the core users of the enterprise, their needs and concerns What is the point?
Secondly, the division of labor between various departments is carried out to clarify the main product of the enterprise, and focus on one product for analysis.
Step 2: Perform data analysis
After clarifying the work between the various departments, subdivide them, match one big goal to multiple small goals, and sort the multiple small goals according to their size. Then there is the basic framework of the data analysis system. Follow this framework to sort out users. The demand and business situation will advance to the next step to iterate the product.
Step 3: Reduce obstacles
Many users use the product for the sake of convenience, check user stickiness according to the user's use of the product, review the situation, and summarize the problem. For example, why not do it well? In the specific process, which product functions have problems, or some data records are missing.
Step 4: Understand the market environment
Before creating a super product, a company must understand what the market you are entering, whether your product has a market, understand the data of the product in the market and analyze it, and find opportunities for product differentiation. This step is the key for companies to build super products.
Step 5: Perform a review
Based on the advantages of data, sum up experience, and conduct a review to avoid making mistakes, and only after a certain conclusion can the product be continuously upgraded. In the process of building super products, we must keep this standard in mind: clear goals, accumulate experience, and continue to iterate. This is the basic idea of building super products. Building a data analysis system is also the highest requirement. Under this principle, we can build data analysis like this system:
1) Set goals: track user groups on a daily, weekly, and monthly basis.
2) When there is a problem, first judge the priority and then check the details.
3) Solve the key problems first, explore the reasons, and finally solve the problems.
4) Guide follow-up based on experience, and develop effective methods deeply to create super products.
05
to sum up
The essence of building a data analysis system is to provide services to users from the perspective of users. Therefore, business managers need to spend more time on products and internal organization. However, most entrepreneurs prefer to follow the steps because they are too entangled in theory and methods. When encountering problems, I will not continue to process and communicate in detail. I will only check through various data analysis. In the end, I will only exchange the user's sentence: I don't understand this product.
Good product managers will be like doctors, even if they know many professional methods and have many professional tools, but in the process of treating others, what they struggle with is not the theory they have learned, but based on the patient's body Adjust the situation and keep asking them "Is this okay?" Is there anything uncomfortable? "Using professional methods to meet the individual needs of users is the core point of whether companies can create super products.