As an operator, how to quickly build a systematic knowledge system

Why do we need a systematic system? Because operations is a multi-disciplinary profession, ranging from marketing , user psychology to content writing and data analysis . All-encompassing. Because it is complex, it is complicated.

I have to admit that new operators need to do [odd jobs], such as customer service reception, copywriting, report calculation, etc. I have also done the above work day after day. The growth of many people also stops during this period.

There are already a lot of relevant operational knowledge, mind maps, and book recommendations on the Internet, but I don’t think they are very effective. It is difficult for newcomers to understand systematic content at a high level. When you explain retention and activation of content operations, they will understand the concept but still have only a vague understanding of the specific applications. You explain the channels for event operations, but it is still not familiar with CP, CTR, CPC, etc.

This is the reason why I still don’t understand after reading a lot of operation books, not to mention that the knowledge in books will also become outdated. What I emphasize today is how to build your own system from point to surface. This is a personal methodology, and you can regard it as my technique. I dare not say that it is a panacea, but I hope it can be of some help to everyone.

One day we were discussing merchandise activities in the group. The event had flaws, mainly because the process and details of the event were not clearly explained. This was not discovered until a colleague gave feedback after the event was released, and the feedback was from a colleague who was not in product operations .

(The picture is a screenshot from the group)

This sentence is very simple, and I wrote it down: If you don’t understand the first step, you won’t continue, and you won’t pay.

I will use this example to explain the construction of an operations knowledge system.

Skills in building an operational knowledge system

There are mainly three techniques: abstraction, association, and deduction.

Technique 1: Abstraction

What is abstraction? This is how I define it: it reflects the essence or laws of an object by analyzing and summarizing multiple instances. Apples are to fruit; grapes are to fruit; clothes are to clothing; hats are to clothing. The latter parts of the short sentence are concepts abstracted from the former, and are a highly qualitative summary of the former.

Let’s go back to the example at the beginning: if you don’t understand the first step, you won’t continue and you won’t pay.

If users report related issues, how do they describe them?

If the activity is not explained clearly, everyone will encounter this series of questions, right? The problems seem unrelated. But it can be summed up in one sentence: If you don’t understand the first step, you won’t continue and you won’t pay.

Abstract text can be more professional. For example, if you want to publish a book to make money, then optimize it: the user's mind will always be cautious about doubtful things. It can deceive a lot of reposts and likes.

In this learning method, abstraction = generalization.

Why master abstraction? Because people are good at thinking from the top down, not from the bottom up. Abstraction makes it easier to build systems from high-level concepts.

How to abstract? It is to strip away all irrelevant representations of things. Product terms, confirmation of receipt, how to pay, are there any traps? All these users’ messy questions can be summarized in one sentence: Do you understand?

Newcomers to the workplace are not very good at abstract thinking, so it is not a good habit not to talk about experience and work methods and not to think deeply. If you have actually worked in customer service, you will know that feedback issues are done every day, but few people can summarize the problems. If we report four or five issues today and seven or eight issues tomorrow, how many people can conclude that users don’t understand the activity page?

Go back to the initial planning of the event, plan the page, consider the details of the terms, consider the instruction documents, and consider the placement of the button page. No matter how it is designed or planned, the core process idea is: If I were a user, would I understand it?

Putting "Can I understand it" into the user's perspective and then breaking it down into details for planning is the watershed between good operations and ordinary operations.

Can we go to a higher level of abstraction?

able!

Some users don’t understand the first step, some users do, some users don’t continue, and some users insist on continuing. A higher level of abstraction is to generalize more user types.

This leads to a higher level of abstraction: when users buy a product, 20% will make up their mind to buy it, 20% will close the page and leave without hesitation, and 60% are in an intermediate state of hesitation.

This sentence illustrates three situations. If they don’t understand the first step, they won’t continue and won’t pay. This corresponds to 60% of users, also known as hesitant users. 20% of impulse users are price-insensitive or hardcore users, commonly known as "buy, buy, buy" users. The 20% of non-purchasing users can be either rational users or non-demand users.

In the first step of abstraction, we summarized the doubts about user behavior and unified them into one thing: not understanding. In the second step of abstraction, we summarized the types of user behaviors, but without understanding them, they became just one of the types. This knowledge system has three layers, each layer is more detailed than the previous one.

Can it be summarized at a higher level? Actually, it is possible. We can also summarize the purpose, elevate the purchase of goods to user behavior, or further subdivide the operation steps, etc. A reliable knowledge system must be a top-down pyramid structure.

Abstraction is a typical empiricist orientation, which emphasizes utilization, review and summary, with the aim of building a complete knowledge system. New operators say they don’t understand the operation system. First, operations are inherently complex, and second, they don’t know how to abstract. The knowledge points are independent fragments rather than structures.

Next, let's talk about association, which is a good friend of abstraction.

Tip 2: Relevance

Let’s start with a fun example:

Apples, oranges, socks, bananas, cabbage, tomatoes, scarves, eggs, grapes, watermelons, lemons

Can you memorize them and repeat them accurately in ten seconds? It's difficult, isn't it?

Let's change the way we look at it and see the following:

Try to remember it again. Do you find it much easier?

The brain is chaotic, but very sensitive to connections. At first it was difficult to remember these eleven seemingly random things, but I was able to classify them into fruits, clothes, and vegetables. It is much more convenient. Associations not only strengthen memory and learning, but also enhance cognitive abilities.

• Hey, how do I pay for this? Which button should I click?
• How do I confirm receipt after paying?
• Is there something wrong with the terms?
• Can I receive the goods here by courier? How long will it take?

A careful study will reveal that the emotions of these users are all doubtful and unresolved, and there are traces and connections between them. Association is the basis of abstraction, because only when things are related can they be explained at a higher level.

From a higher level of abstraction, 20% of users who buy immediately are impulsive, irrational, or fanatical, etc., while 20% of users who do not buy are rational, calm, or rejecting. 60% of middle-level users are confused, worried or hesitant.

Although users have different mindsets and react differently, there are outward manifestations of emotions when it comes to purchasing products. This gives us the basis for abstraction.

Association is to find the patterns between things and classify them. The difference between it and abstraction is that abstraction is the summary of the upper and lower structures, while association is the connection between parallel structures.

Once emotions are classified and associated, the abstraction becomes bounded. If it is difficult for us to abstract a knowledge point, then consider starting from the association and finding the connection between things. This is a quick and abstract approach.

In the operation system, user behavior, user psychology, user logic, etc. are all universal. It can be used as a basis for abstract and associative thinking.

Associations can also expand the boundaries of abstraction and diverge thinking. For example, we have impulsive, rational, and doubtful emotions. So will users feel greedy? Of course it is possible. For example, product discounts and promotions may convert part of the 60% into impulse. This is another use of association.

Abstraction and association are one and the same, and they are good friends. In short, if you want to master the theoretical knowledge of operations, first look at whether there are any connections, commonalities or rules between the fragmented knowledge, and then try to summarize them at a higher level.

Skill 3: Deduction

The above examples can be roughly understood as induction, that is, many examples are summarized into principles. We have evolved from the initial examples into a structured knowledge. The next step is interpretation.

Induction and deduction are two schools of thought in philosophy, as follows:

• Sparrows can fly, wild geese can fly, seagulls can fly, they are all birds, so all birds fly. This is induction.
• All birds can fly, because sparrows, wild geese, and seagulls are all birds, so they can fly. This is deduction.

Of course, I am not capable of talking about philosophy, and my interpretation here is a simplified version. That is, you need to apply abstract and associative knowledge systems to practice.

The key is to use it.

Even if you have a theory or have learned some superficial theories, it is actually not of much use because you don’t know how to apply them and cannot bring out the value of the knowledge. This is the reason our ancestors taught us to draw inferences from one example.

Let me repeat the theory: when users buy a product, 20% will make up their minds to buy it, 20% will close the page and leave without hesitation, and 60% are in an intermediate state of hesitation.

Now think about what scenarios in operations can be explained by this theory?

• Do I participate in Taobao Double Eleven ? What type of user am I?
• When a user downloads an APP, are they also divided into 20%, 60%, and 20%?
• When users invest in financial management , are they also divided into 20%, 60%, and 20%?

Practice more scenarios at work and you will find the shadow of the system. For example, when users invest in financial management, 20% of them who are willing to buy will definitely have emotions such as greed, demand, and expectation. Users who hesitate to buy will definitely have doubts about safety and rationality. Not buying it means you are either too conservative or you don’t like it. The logic is the same as that of purchasing goods. So as an operations planner, how do you dispel users' doubts? Does the page design take these points into consideration? How can we convert more users to purchase?

As you become more proficient in application, your knowledge system will become more powerful. Good theories should be used constantly. After reading the same pile of books, a top student can get 100 points, while an ordinary person can only get 70 points. Were the academic masters the ones who invented the knowledge theorems in these books? No, they just use it.

The same is true for operations knowledge, and it is even more difficult because no book can truly explain operations thoroughly, so operations is a job that emphasizes practical experience. Good operations are not about how many years you have worked or how many books you have read, but about what knowledge you should use at a certain moment.

I emphasize deduction, which means putting theoretical knowledge into a broader and more practical scenario.

• The first is to observe vertically to see whether the operating system you have summarized is correct and whether it can be further explored or corrected.
• The second is to observe horizontally and learn, to see how other products are applied, how other products are designed, how I can digest the knowledge in the books and use it myself, and what can I learn?

We can think of learning as an input and output system. Deduction is continuous input, putting the problems encountered in reality into our own knowledge system, and finally constantly testing the cases.

Experience determines the lower limit of the depth of the knowledge system, while the upper limit is determined by application skills and learning.

Abstraction, association and deduction are a trinity of skills. I dare not say how powerful it is, but I believe it will still be helpful for learning knowledge. If there is a better skill than this, it is the desire to keep learning.

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