Zhihu Institutional Account Operation Manual

Last year, I wrote Zhihu Institutional Account Operation Practice 1.0, which is divided into four parts: Positioning, Topic Selection, Creation, and SEO. Now, more than a year has passed, and some of the practical skills are a bit outdated, for example:

The 1.0 topic selection section is suitable for the early development stages of most institutional accounts, which is the stage of quickly laying out keywords. But as most of the keywords have been laid out, institutional accounts will face the embarrassment of having no questions to answer.

Similarly, in the 1.0 topic selection chapter, it is inefficient to use the Zhihu rating plug-in and Zhihu system recommendations to find topics, especially for companies that pursue efficiency.

Also, in the creation section of 1.0, only the formula for highly-praised answers and a simple explanation of the formula were provided, but there was no detailed answer on how to write content that users would like.

Today's article is a supplement to the above problems, divided into three parts:

1. Topic planning and optimization;
2. Content creation optimization;
3. Marketing tool optimization.

For easy comparison, the differences between the operations before and after optimization are listed.

1. Topic planning and optimization

1. Before optimization (applicable to the early stage of account development)

Building a keyword library is the first task after determining the account positioning. It can be done from three dimensions:

First, starting from the functional features of their own products , for example, ProcessOn is an online drawing tool that supports drawing dozens of drawing types such as flowcharts, mind maps, organizational charts, UML diagrams, etc. These drawing types themselves are the first batch of keywords, and then the first batch of keywords can find more long-tail words through tools such as 5118.

Second, start from the product's usage scenarios . For example, XMind's main keyword is mind mapping. It seems that there are few keywords, but it can be based on its own wide range of application scenarios, such as reading notes, meeting minutes, marketing planning, brainstorming, etc., and more long-tail words can also be derived from these words.

Third, starting from the keywords of competitors , for example, Graphite Docs’ competitors include Tencent Docs and Kingsoft Docs. Operations staff can continue to pay attention to what the official accounts of these competitors are answering, especially some comparative questions on Zhihu. We must especially manage and occupy these accounts carefully.

But when answering this kind of question, you need to be careful not to step on your competitors , as this will involve malicious commercial competition. Currently, the best institutional answer is from Alipay (as shown below), but if your company is not as well-known as Alipay, you can start with this sentence and then expand on the functional highlights of your product step by step.

2. After optimization (applicable to the middle and late stages of account development)

What should we do when we have answered all the questions in the previous three keyword libraries? There are three methods.

First, answer collection questions. For example, the previously mentioned ProcessOn, XMind, and Graphite Docs can all answer collection questions such as office efficiency software and office tools. Among them, ProcessOn and Graphite Docs can also answer online collaboration software, online efficiency tools, etc.

Second, convert answers into articles , reorganize previously verified popular answers with more detailed content, and aggregate articles on the same topic that were previously scattered under several questions;.

Third, convert text and pictures into videos . Convert previously verified popular answers into video tutorials (video content is the content format that Zhihu platform is currently focusing on promoting). Video answers will have a relatively high weight in the early stages and can easily reach the top of the Q&A table (this is a routine we have already verified).

Careful friends may find that the topics mentioned above are all regular topics (topics that can be published at any time), and in fact, you can also reasonably take advantage of hot topics. There are three types of hot spots suitable for institutional accounts. The first is major time nodes related to software usage scenarios, the second is the broadcast period of popular film and television dramas, and the third is about major industry conferences/speeches.

The first type is major time nodes related to software usage scenarios.

For example, XMind is a mind mapping software. Many students and professionals use it to study and prepare for exams. So we will choose to reserve relevant answers in advance before the final exam or a large-scale exam. Because when the exam is about to begin, these students or working people will go to Zhihu to "cram for the exam", and this is when the answers you prepared in advance will come in handy.

This routine has been tried and tested. More than ten answers of the same type with more than 5,000 likes have been produced before. It can also be verified by using 5118. For example, if you search for the keyword "mind map" during this period, you will find that the reading increase of Zhihu questions related to the final exams in subjects such as Mao Zedong Thought/Ideological and Political Theory/Marxist Philosophy/Modern History is very rapid (this will be discussed in detail in the third part of marketing tool optimization).

The second type is during the broadcast of popular TV series and movies.

For example, for popular historical dramas or suspense dramas, we can use mind maps to create timelines or sort out the relationships between characters. At this time, mind mapping tools such as XMind, MindMaster, and Mubu can come in handy.

During the period when "Awakening Age" was popular, an institutional account linked it to the timeline of modern Chinese history (product related), and the data was pretty good. "The Snowy Swordsman", which has sparked heated discussions since its recent launch, is a typical ensemble drama with intricate character relationships, which can also be sorted out into a corresponding character relationship diagram to attract traffic.

The third type is about major industry conferences/speeches.

For example, Liu Run’s annual speech that just ended some time ago, and the upcoming WeChat Open Class, Luo Zhenyu/Wu Xiaobo’s annual speeches, etc., you can organize the corresponding notes or mind maps in time after the meeting, and then reap a wave of traffic. As far as I know, the best one in this regard is Noteman.

2. Content Creation Optimization

1. Before optimization (creation method is not specific enough)

In the previous 1.0 version, I gave the general structure of Zhihu's highly-rated answers: highly-rated answers = giving the result directly + making a well-reasoned analysis + ending with an interactive post asking for three likes. The beginning and the end are not difficult to operate, but I didn't explain in detail how to operate the main content in the middle.

2. After optimization (more refined creation method)

The questions and answers of Zhihu institutional accounts generally have two directions.

One is that the question is directly related to the product/competitor , such as "Which one is better to use among Tencent Docs, Kingsoft Docs, and Graphite Docs?" This is suitable for introducing the full features of the product, especially highlighting the advantages and differences compared with competitors. It is a natural place for advertising.

But there won’t be too many questions like the above on Zhihu.

Because most of them are of the second category, problems related to product usage scenarios.

For this type of question, answers that simply introduce the software functions are definitely not acceptable, because they are not the kind of useful information that users on Zhihu like, and this type of content can easily be judged as marketing content by Zhihu officials or reported by users. The correct approach is to first solve the user's problem with practical information, and then add your own personal opinions.

Here are three examples:

The three examples above may seem unrelated, but in fact their answers roughly follow a formula, namely:

Article content length = number of type A × content length of type A

When the number of A's is small, you need to explain this kind of thing in sufficient detail and thoroughness. For example, for the first question, the whole article revolves around the Feynman technique and breaks it down from the shallow to the deep. But if the number of A's is large enough, then the content of a single A does not need to be written too much. For example, for the 6 ways of thinking, each way of thinking needs to be broken down, but not in such detail. For example, for the 20 must-have apps for installation, each app can even be simply mentioned with one or two functional highlights.

It is worth mentioning that when explaining concepts, don't be too serious. The method of explanation is generally from familiar to unfamiliar, from concrete to abstract.

For example, the following introduction to the "Feynman Technique". You may not know what the Feynman technique is at first, but you know that learning is through teaching, so let’s start with this familiar thing.

This may be the first time for everyone to come into contact with the "first principles". In comparison, Tesla founder Elon Musk may be familiar to everyone, so let's start with a sentence he said.

When explaining these concepts, you have to understand them yourself first, so that the content you write will appear more professional in the eyes of readers, and professional content is what Zhihu users like most.

3. Marketing tool optimization

1. Before optimization (depending on the mining judgment of operators)

Previously, we used some unofficial plug-ins and related recommendations, but none of them could show the number of views, followers, and answers of a certain question and answer on one screen at the same time. The operators needed to click in one by one and make a comprehensive judgment based on the data, which was inefficient.

2. After optimization (using mature marketing tools to improve efficiency)

It is impossible to see an overview of all the data using the previous method, but now with the help of 5118, this problem can be perfectly solved (for companies that want to invest heavily in the Zhihu channel, it is really worth buying 5118. If you are not willing to invest, the operators will suffer). 5118 has set up a special area for Zhihu. For Zhihu institutional accounts, you generally only need to use the "Zhihu Content Operation" menu on the left.

The first three columns of the "Zhihu Content Operation" menu are actually the same, but after clicking on them, the two columns will be sorted by the two dimensions of increased reading volume and increased number of followers by default.

Taking the "Zhihu Reading Skyrocketing List" as an example, the 5118 Zhihu section not only supports searching for all questions with keywords, but also supports simultaneous searches based on author name, recent reading volume/reading increment, number of followers/increase in number of followers, number of answers/increase in number of answers, number of first likes/increase in number of first likes, number of second likes/increase in number of second likes, popularity, and other dimensions.

The strategy for finding potential questions is the same as before, with high traffic and few answers . For example, this question about Mao Zedong Thought review materials has a high increase in readings recently (because it is approaching the final exams), and there are only 12 people who answered it. In this case, you must take up the position decisively. As long as your content is substantial enough, the traffic will be guaranteed.

However, some readers have reported that it is not reliable to find questions based on the recent increase in readings on 5118, and there is no traffic after answering them.

For this question, if you have followed the previous strategy completely and there are no major problems with the content, it is likely that the reading increase you saw is the total increase over a longer period of time, and the time point of your answer happened to be when its growth was nearing the end.

It has been observed that the reading increments of 5118 include updates 1 hour ago, 2 hours ago, 12 hours ago, 1 day ago, 2 days ago, 7 days ago, etc. You need to click on the corresponding reading volume to see the trend changes of this answer in the past 30 days.

▲Steady and continuous growth

▲The overall growth trend is increasing, but there will be some flat areas in the middle

Of course, you can’t search all the keywords every time you are looking for a topic, so every time you search for a keyword, when you encounter a suitable question, click the “+” on the right to add it to the “Question Monitoring” list. Next time you are looking for a topic, you can directly check it in the monitoring list.

The above is the Zhihu Institutional Account Operation Practical Manual 2.0. If you have any questions, please leave a message and we will answer all your questions.

Author: Nomadic Chronicles

Source: Nomadic Journal