7 operational ideas for community operations (Part 1)

The essence of a community is actually users + content + community culture , which are also the three core elements of a community. When it comes to community, whether it’s content or users, what matters is being down-to-earth and speaking human language, which is also a challenge to the operator’s capabilities.

And you must know that the community is a platform for users with certain labels and barriers to exchange value. For example, WeChat community, Knowledge Planet community, Tieba, Zhihu community and so on.

After understanding the nature and characteristics of the community, let's get to the point. This article will start from the following points:

1. Acquisition of early seed users

2. Content community building and content system labeling

3. How to plan the content ecology of UGC/PGC

4. How to achieve mass production of early community content and output of high-quality content

5. User classification operation

6. Content system tags

7. New Dilemmas and Thoughts on Community Operations

Because there is a lot of content, this sharing is divided into two parts (this part is the second part), and the first part is "Community Operations - 7 Operational Ideas on the Road to Growth (Part 1)".

1. "How to achieve mass production of early community content and output of high-quality content"

After talking about how to create and plan high-quality content, the next thing is how to maintain and enable users to output content, especially the initial demand for quantity and excellent content quality.

Regular content is branded, and branded content is rewarded. Generally, during the cold start phase, operators are required to take charge and contribute content themselves. Both original and collected ones are acceptable.

In the early stage, UGC and U classification should be done well

On the one hand, there are industry big names who need content output from some experts and KOLs. They are the weather vanes and will play a leading role in the entire community. The content output by these people is professional and readable, and is the reason for other middle-level and low-level users to stay.

Establishment of community system

What content is encouraged? What content is blocked? Content screening mechanism? Ensure that good content is well displayed and junk content is dealt with in a timely manner. This is the basis for ensuring the normal operation of the community.

Establishment of user incentive system

1. Activities

Organizing activities from time to time to encourage users to produce content can also strengthen product brand memory.

2. User Level

The establishment of a sense of achievement and rewards. A novice user can improve his level in the community by continuously contributing good content (such as getting likes from others, etc.). This is very important. This is the establishment of an ecosystem. Only when there are people at the top of the pyramid will the bottom users have the motivation to run and continuously contribute content. In this regard, I can even say that I have found some very high-quality and loyal users, upgraded their levels, allowed them to have certain management rights in the community, and we all manage the community together.

2. User Classification Operation

User stratification is particularly critical in community operations, with 20% of highly sticky users driving 80% of ordinary users. So we mainly focus on these 20% sticky users. Because they are the most important people who decide whether we can grow bigger and better in the future. Especially in the early layout, let’s continue to take Zhihu as an example. Zhihu’s early seed users were all invited. The 200 seed users influenced tens of thousands of people, and then these tens of thousands of people were screened.

In fact, most ordinary users are using communities, but they are not good at sharing, and the sharing ratio is very low. This also indirectly shows that the tolerance of most users will not be transformed into contributing users.

Generally, I divide users into four categories: big V users/professional users, active users, ordinary users and passers-by users

1. Big V users/professional users:

First of all, the platform needs to have a way to define big V users. What kind of users can become big V users and be supported by users as professional? (The professional terms here are represented by institutions)

Generally, scarcity is created. Normally, 10-20% of the total users is enough.

Since he is a big V, there must be some different permissions and services. Here I divide it into basic services and customized services.

Basic services: such as the privilege of pinning content, birthday gifts, personalized homepage, etc.

Customized service: Try to meet the requirements of big Vs within the scope of cost and technology. For example, if the stocks purchased in the simulation trading are suspended and can no longer be traded, ordinary users can only wait for the trading to resume. The big V can directly find the operation staff, and the operation staff can ask the technical brother to open the back door. It can also bring unique privileges to users.

Build contact channels for big V users, such as QQ groups and WeChat groups, to provide timely services and feedback.

2. Active users:

Active users are not difficult to define, and they are often active in the community, such as daily logins, spam posts, active time, etc.

This group of users mainly relies on community mechanisms to stimulate. For example, the attractiveness of community content, the stimulation of activity mechanisms, etc.

Active users are most likely to be cultivated into big Vs, so we need to pay attention to the potential stocks among this type of active users. Generally, there are three criteria for identification: high-quality creative content, particularly active recently, and rapid fan growth and high attention.

Generally speaking, the strategy we should adopt for these users is to give them unprecedented privileges, such as the growth of fans, likes and comments brought by high-quality exposure.

3. Ordinary users:

Guide some active users who frequently log in to the community but only browse to contribute content

4. Passerby users

I registered based on a certain scenario, but I downloaded it just because a friend mentioned it, or I downloaded it just because it was recommended to me, but I don’t know much about the community and products.

3. Content system tags

In recent years, various labels have emerged based on big data algorithms. The fundamental purpose of labels is to solve the problem of limited content exposure. Tag-based recommendations can effectively expose content to corresponding target users.

The fundamental purpose of content recommendation tags is to accurately recommend content to target users, allow target users to consume it, and provide positive feedback to community authors, thereby maintaining the creative enthusiasm of community authors.

Generally speaking, there are three typical recommended application scenarios for tags.

1. Recommend new user content based on tags

When new users register, they select content tags that they are interested in. When they use the product, content with the same tags can be recommended to new users. Different users choose different tags, so the content recommended to them is also different. In this way, more content can have the opportunity to be exposed to new users, thereby improving exposure coverage. (Exposure coverage = number of exposed contents/total amount of contents)

2. Recommend related content based on tags

The tags of the content are displayed on the content details page. When users want to see more content with the same tag, they only need to click the tag to expose more content. A single tag can form a direct connection between content, and extending it to a complete tag system can allow all content to form a content network.

3. Personalized content recommendation based on tags

Content generates content features through tags and matches them with user preferences. This is a content distribution method that is tailored to each individual. In this way, a large amount of mid- and low-end content that was previously not discovered by users can be recommended to suitable users, thereby achieving exposure of more content.

4. New Dilemma and Thinking about Community Operation

As the community develops, various problems have gradually arisen:

1. How to lower the threshold for content creation and expand the number of users who share and create content?

2. How to create a unique community atmosphere and differentiate it from other communities?

3. How to create hot topics and operate activities to trigger secondary creation and empower the community?

4. With an increasing number of creators, how can we distribute traffic without reducing their enthusiasm?

5. As the amount of content continues to increase, how can we reduce the labor cost of screening and controlling content?

6. Relying on product functions, build publishing tools that are more suitable for ordinary users to make creation easier, with the goal of “everyone can create”?

7. Continuously improve and enrich the user tag dimensions, use algorithms to make personalized recommendations, and continuously reduce the negative impact of unbalanced content traffic distribution

These are all worth our constant thinking.

At different stages, we also need to constantly learn from the strategies and methods of our peers or existing product communities on the market.

The above is some of my own experience, I hope it can help everyone.