Fenda was once very popular, but then faded out of users’ sight. Why?

In 2016, when knowledge payment platforms were on the rise, Fenda became extremely popular after being online for 42 days, but then it was quietly taken offline without any warning. After coming back online, it is no longer as glorious as before. By analyzing this paid voice Q&A product, let us explore how to create a popular knowledge payment platform.

1. Experience the environment

Device model: Huawei P9

System environment: EMUI 5.0 (Android)

Product version: Fenda v1.10.0

2. Product Introduction and Analysis Purpose

Product Introduction

Fenda was a paid voice Q&A platform that was once very popular in 2016. Celebrity experts in various fields and internet celebrities have joined this platform. Fenda has been online for 42 days and has 10 million users. It has produced 500,000 questions and answers, with more than 1 million users paying for the content, a transaction amount of more than 18 million, and a round A financing of 25 million US dollars, with a valuation of more than 100 million US dollars.

The figure below shows the trend analysis of user activity of Fenda APP since its launch until January 2017. According to the data from iResearch Qianfan in September 2016, its APP ranked 3579 in the entire network, 384 in the first-level field (education), and 25 in the second-level field (education platform). On August 10, 2016, Fenda quietly "went offline" and resumed operations on September 27 of the same year. The number of active users that month was 219,600, down 54.80% from the previous month.

Active users and field penetration trends (Source: Analysys Qianfan, data from July 2016 to January 2017)

Purpose of analysis

1. Understand the development of knowledge payment market and product industry;

2. Understand the characteristics of Fenda’s user positioning, product positioning, product functions, etc.;

3. Through analysis, we can find out the reasons why Fenda became popular overnight and then faded out of users' sight, and summarize the parts that are worth learning from and improving.

3. Market Analysis

The popularity of Fenda and the rise of knowledge payment platforms are inseparable from the market they are in. Next, let’s take a look at the market environment in 2016.

According to Analysys 2016 data, the following chart shows China’s GDP growth trend from 2005 to 2015. China's GDP continued to grow from 2005 to 2015. Although the growth rate slowed down after 2010, it still showed a relatively stable trend of economic development overall. Economic benefits are an important driving force for social development.

Source: Analysys 2016 data

In terms of China's per capita disposable income from 2012 to 2015, as can be seen from the figure below, compared with 2012, the per capita disposable income in 2015 increased by 33%, which can be said to be a huge increase. Only when residents have more disposable income can they be able to spend their income on areas other than ensuring food and clothing.

Source: Analysys 2016 data

As disposable income increased, the consumption structure of Chinese residents also changed significantly from 1990 to 2015, as shown in the figure below. In fact, compared to today, 1990 was a time of relative material poverty, and most residents at that time struggled only to maintain a basic livelihood. Today, it can be seen that the proportion of residents' spending on clothing and food has been greatly reduced. This is also in line with Maslow's five-level theory of needs. When residents meet basic physiological, safety and social needs, they will hope to be respected by others and improve themselves. It is essential to recharge your own knowledge reserves.

Source: Analysys 2016 data

Based on the above data and analysis, we can conclude that:

1. The income and consumption levels of Chinese residents have increased significantly, and users' consumption concepts have shifted and their consumption habits have undergone major changes (mainly reflected in the fact that, on the basis of being able to ensure food and clothing, they can spend more on education, entertainment and improving self-cultivation).
2. The formation of knowledge payment is inseparable from the popularization of mobile payment. The rapid development of the Internet industry and the steady improvement of scientific and technological levels have provided a perfect foundation for the knowledge payment platform. Moreover, the knowledge payment platform does not violate national policies and friendly social relations.

Combining the current social environment and the results obtained through the above data, the market analysis of knowledge payment platforms leads to the following conclusions:

1. The favorable overall social environment, rapid social and economic development and technological progress are the fundamental reasons for the rise of the knowledge payment platform market.
2. The public's willingness to acquire knowledge is increasing, but the quality of free knowledge sharing on the Internet is uneven and there is content overflow. The efficiency and quality of knowledge acquisition have declined drastically, cost and time are facing challenges, and the pain points of Internet knowledge sharing and acquisition have intensified. Users' willingness to pay and consumption perspectives for "content" and "knowledge" are changing, from being unwilling to pay to being willing to pay for similar products with significantly higher quality and better services.
3. For the younger generation, white-collar workers and the middle class, obtaining the most valuable information on the Internet with the highest efficiency makes knowledge available on demand. These are all potential paying users of the knowledge sharing economy, and have become the core driving force behind paid knowledge sharing.
4. Not only are there a large number of users who pay to obtain high-quality content and knowledge, but there are also a large number of potential knowledge sharers who also have the need to monetize knowledge sharing.

4. Industry Development

There is a slow transformation process in the knowledge sharing industry:

1. Static knowledge platforms, such as Baidu, Hudong Baike , 360 Baike , etc.;
2. Dynamic knowledge communities, represented by knowledge discussions such as Zhihu;
3. Knowledge payment platforms, such as Fenda, Himalaya FM, Zhihu Live, etc.

Its development to the paid stage is due to:

1. With the development of mobile Internet , vertical services and personalized needs have become possible. With the popularization of mobile payment, the concept of paying for knowledge is becoming more and more popular.
2. With years of operation experience of online knowledge communities represented by Zhihu, knowledge payment has emerged in an environment where knowledge sharing, online content, social e-commerce , mobile audio, mobile live streaming and other hot industries are intertwined. In terms of film, television, music and other content, a large number of users who are willing to pay for knowledge sharing in the paid market in the audio and video field have been cultivated. Moreover, the existing knowledge payment projects have good operating data. Payment incentivizes the production of high-quality content and also helps users screen information efficiently.

These two conditions continue to form a complete trading market and ecology, and the sudden emergence of knowledge payment is on the rise.

According to the data (iResearch 2016 data), the transaction volume of the sharing economy market in 2016 was approximately 3.452 trillion yuan, an increase of 103% over the previous year, of which the knowledge and skills sharing economy increased by 205% year-on-year.

Market size of paid knowledge platforms (Source: Analysys 2016 data)

The above table shows the market size of several well-known knowledge payment platforms in 2016. Both their users and corresponding payments have reached a considerable scale. Among them, Himalaya FM has the largest market share, with revenue exceeding 19.8 million yuan. The development of knowledge monetization platforms will continue to ferment and become one of the main platforms for knowledge sharing.

5. User Description

In order to understand Fenda’s user positioning, we conducted an analysis based on the following data obtained from iResearch Qianfan.

Source: Analysys Qianfan 2016.9 data

First of all, the male to female ratio of Fenda product users is about 1:1, with the number of females slightly exceeding that of males. This is determined by its product strategy and product positioning, which will be discussed later.

Source: Analysys Qianfan data from June 2016 to January 2017

From the above time-divided active user data, it can be seen that except for the small peaks during sleep time and between 8 and 9 pm, the user activity level is relatively even throughout the day. This fully demonstrates that users use this product in fragmented time and not for a specific period of time. This is also closely related to the one-minute voice answer setting in the product.

Source: Analysys Qianfan data from June 2016 to January 2017

In terms of the age distribution of product users, they are mainly concentrated in the 24-40 age group, among which the 31 to 35 age group shows a decreasing trend, while the number of users under 24 years old has increased. These are mainly the younger generation, white-collar workers and middle-level managers of companies, and of course some college students.

Source: Analysys Qianfan data from June 2016 to January 2017

In terms of geographical distribution, users are mainly concentrated in economically developed regions such as Beijing, Shanghai, Guangzhou, Shenzhen and first-tier cities. A developed economy is an important foundation for the development of knowledge payment platforms.

Source: Analysys Qianfan data from June 2016 to January 2017

Source: Analysys Qianfan data from June 2016 to January 2017

From the above two figures, the first one showing the average number of launches per user and the second one showing the average usage time per user, we can see that during Fenda’s development and heyday from June to August 2016, the average usage time per person was 3-4 hours, and the number of launches of the Fenda APP was approximately 20-25 times. After that, there was a sharp decline, partly because the Fenda product was taken off the shelves for a period of time during that period, but the performance was not satisfactory after it was put back online.

After analyzing the data of Fenda users’ product usage through several dimensions, we can draw a description of the users, which will help us conduct in-depth analysis of the product. The following is a user portrait and product usage scenario.

Usage scenarios and user portraits:

Xiaobai, female, 28 years old, white-collar worker in a company. During his daytime work, Xiaobai encountered a problem that he didn't understand. Open the Fenda app and search for relevant topics to see if anyone has asked similar questions. If so, spend 1 yuan to secretly listen to other people's answers. If no one has relevant questions, find a well-known answerer related to the question and see if the price set by the answerer is reasonable. If it is within an acceptable range, ask the answerer a question. If there is no answer to the relevant question or relevant answerer after searching, I will sadly close the Fenda APP and open Baidu to search.

6. Product Experience

Next, we will mainly understand and analyze product positioning, product functions and product performance.

6.1 Product Positioning

(1) Fenda’s current product positioning

A paid voice question and answer platform. The version that was first launched in May 2016 was positioned more towards "monetizing the influence of internet celebrities."

(2) Slogan

If you can’t find it, ask and get the answer. (Before the revision: Let influencers make money decently.)

(3) Target users

1. Valuable users who are responsible for answering questions
2. Consumers who asked questions

(4) User needs

Users hope to be able to obtain the most valuable and highest quality information with the highest efficiency by paying, or to have direct conversations with their favorite celebrities and internet influencers.

6.2 Product Features

6.2.1 Product Function Structure Diagram

6.2.2 Product Main Function Question Flowchart

6.2.3 Product Function Analysis

First, we divide product functions into two main categories: basic functions and special functions:

1. Basic functions : Search for topics and people that interest you, follow and listen to your favorite celebrities and influencers, ask paid questions to celebrities and influencers that interest you, and pay to eavesdrop when users see that the people they follow answer questions that interest them. You can share the problem to Moments , WeChat and Weibo, or report the problem. Celebrities and influencers set their own price threshold for answering questions and can choose the questions they want to answer. Users can earn a general amount by eavesdropping on others. If the question raised by the user is not answered within 48 hours, the answer amount will be refunded.
2. Special features : The first is quick questions . There are four optional question categories in the quick question column, namely: "Minor physical ailments, quickly ask the doctor", "Minor emotional troubles, experts to enlighten", "Big and small disputes, lawyers to judge" and "Parenting experiences, experts to give advice". In each category, there are corresponding experts and internet celebrities who answer the questions as certified answerers. Users pay 10 yuan for each quick question, and the certified answerer will answer the question quickly and the selected answer will receive a reward. Non-questioning users do not need to pay extra to eavesdrop on questions asked in Quick Questions, and can choose whether to like the answers. ; The second is the short lecture . In this column, internet celebrities or experts in various fields will give short lectures on a certain issue. The short lectures are a series of questions and the duration is between 20-30 minutes. Lectures can be tried out. Users can choose a small lecture hall of interest and pay to join. Then they can listen to the lecture content, discuss with other users participating in the same lecture hall in the small lecture circle, and ask questions to the speaker. Users can choose to buy 1-1000 copies of the lecture and give them to their friends, allowing their friends to listen to the lecture for free. The lecture-related content is diverse, and can be mainly selected under the two categories of workplace and emotions.

The descriptions of the above functions are relatively general. In order to explain the product functions in more detail, we will provide a more detailed and specific description of the product functions in combination with the product page information.

After opening the APP, the user enters the main page, which includes two sections: listening and short lectures.

In the listening section, the main functions for consumer users are asking questions and eavesdropping. The page information also includes recent popular stars and daily headlines Q&A, both of which increase the ease of use for users. But personalized recommendations are a little lacking. There is redundant content in the Fenda Novel and Novel columns on the page. The novel is already a first-level entrance and there is no need to waste page space.

(1) Question function

Users can search and browse the celebrities and internet celebrities they are interested in, and ask them questions by paying the corresponding amount. This function is the most core function of the Fenda product. Users can use Fenda to get close to the internet celebrities they follow and like. Through one-on-one question and answer sessions, you can directly experience the interaction with internet celebrities.

However, the flaw of this function is that the Q&A with internet celebrities that appear randomly on the homepage are not targeted. There is a high probability that users will see celebrity Q&A that they are not interested in. When users do not initially follow a person, we should focus on how to guide users to find, discover and follow their favorite stars or content.

(2) Eavesdropping function

For users who are not asking questions, they can pay one yuan to eavesdrop on questions that other users have asked to internet celebrities and have been answered. This feature was a popular feature of Fenda. Users generally have a strong interest in peeping into other people's privacy, and the introduction of this function satisfies this demand of users to a large extent. Moreover, the one-yuan setting is also in line with user psychology. With only one yuan, you can neither suffer any loss nor be cheated, but you can eavesdrop on the conversations between celebrities and strange users. For the user who asks questions, the benefits gained from eavesdropping can be shared equally with the person being asked. This can also, to a certain extent, encourage users to ask more questions, thereby increasing user activity and motivation.

However, this function also has corresponding flaws. At present, there are already a large number of users on Fenda who want to earn money by asking questions or eavesdropping. The motives of these users in asking questions are not pure and can easily spoil the overall product atmosphere. A corresponding measure is to recommend that Fenda add a question-and-answer scoring mechanism, whereby the questioner can rate the answered questions and the eavesdropper can also rate the overheard questions. Promote the healthy development of the question-and-answer atmosphere through a scoring system.

Enter the question details page, which mainly displays information such as the number of times the question has been heard and liked, the question value, and the question time. Among the more important functions are sharing, recommendations of internet celebrities and related questions.

(3) Sharing function

This function allows users to share questions on WeChat, Weibo and Moments if they like the question and answer. This function basically exists in all content apps. Firstly, it satisfies users’ needs to discover new things and share them with people around them. Secondly, it can also attract more users through users’ sharing. This is a reflection of the social nature of the product. In future product iterations, you can also consider adding Fenda’s own circle of friends and increase sharing with Fenda friends to achieve interaction between users.

(4) Recommended features

The recommendation function helps users discover more content of interest, thereby increasing user usage time and user stickiness. The logic is: if you click to enter the content details page, there is a high probability that you are interested in the question. Therefore, based on this assumption, similar internet celebrities and related hot questions and answers can be recommended to users. However, the recommendation function is not very perfect at present. The recommended people and topic questions and answers are not very relevant to the original questions and answers, and users will not have the desire to click on them. The recommendation algorithm needs to be improved.

Enter the question details page, where the main information includes detailed information of the person being asked, the amount of money required to ask the question, the probability of the question being answered, whether to follow the person being asked, whether to choose whether to make the question public, and the question and answer history of the person being asked.

(5) Listen and cancel functions

Similar to following and unfollowing on Weibo. Users can access the question page of a specific internet celebrity through various channels and choose whether to listen based on the relevant information. After listening, the Q&A status will appear on the listening homepage. If users follow a celebrity and find that he or she is different from what they imagined, they can stop following his or her updates. Provide users with the ability to make their own choices.

(6) Question-related functions

There is a required amount to ask a question, the possibility of the question being answered, the choice of whether to ask a question publicly or privately, and information on asking a question. The settings in this part are thoughtful for users. When considering whether to ask a question, users will consider how much it costs, whether the question is worth it, and whether the question will be answered. User privacy has been taken into consideration and users can choose to ask questions privately. These settings are very relevant to user psychology and have corresponding functional introductions.

(7) Historical question and answer query function

At the bottom of the page will be displayed the historical interactions between the person being asked and other users, as well as the number of people who have listened to the question. It can help users judge the activity of the person being asked a question on the Fenda platform, and learn the scope of the questions he or she answers to determine whether they need to listen. Historical questions and answers can be sorted by default, latest and popular, and can also be searched by keywords . Users can quickly find questions that interest them, and can also select the questions and answers they want to eavesdrop on based on their popularity.

Another column on the APP homepage is the short lecture column. This column is different from listening. It appears in the form of a small classroom. Internet celebrities serve as lecturers and ordinary consumers serve as students. They can choose the lectures they are interested in and like to listen to.

(8) Select the short lecture function

The short lecture column is classified into two major categories at the top of the page, and users can choose to enter the corresponding category to select the short lecture course. But in fact, there are only about 10 lectures in each of these two categories, and not all lecture courses are included. It is easy for users to mistakenly think that all small lectures are classified under these two tags. Next is the browsing page for the short lecture course. Although each short lecture has the number of participants marked, the content of the lecture, the lecturer and the lecturer’s last reply time can help users judge whether they are interested. However, it does not have a sorting function. Users do not know whether the novels are arranged according to popularity, time, or other methods, which makes it inconvenient for users to search. In addition, the search function in the product is only used to search for people and topics, and cannot be used to find the content of the novel. The novel module is not easy to use.

Select a specific novel to enter the novel's details page. This page mainly contains the content of the lecture, detailed information of the speaker and the function of purchasing the lecture.

(9) Audition function

The lecture content summary and speaker information on the lecture details page can further help users determine whether the content meets their needs. The audition function is a win-win setting. On the one hand, users can deepen their understanding of the real content through audition. On the other hand, after listening to a part of the content, you can use the user's curiosity to increase the possibility of user purchase.

(10) Gift function

The gift giving function is also a special feature. When users see something they like, they want to share it with their friends, and the gift function enables not only sharing but also gift giving. If users like the content of the novel, they can purchase the corresponding shares and give them to their friends according to their needs. The choice of the gift quantity is also very free. It greatly enhances the sociality and entertainment of the product. However, it is recommended to add a discount function for purchasing multiple copies, for example, you can enjoy a corresponding discount if you buy more than five copies. It is similar to the group buying function that users often use and can promote user consumption.

The above picture still shows the drop-down display part of the novel details page.

(11) Lecture display function

Since the short lecture is in the form of a lecture hall, it is analogous to classroom learning in real life scenarios, and its lecture content is also divided into corresponding sections. Users can clearly understand the series of lecture contents in the lecture, and each lecture lasts 2-3 minutes, so users can make full use of fragmented time to listen.

(12) Small talk circle function

The Lecture Circle is similar to the Moments, which allows users participating in the same lecture to communicate here, and the speaker will also reply here. This function is very unique and is equivalent to classroom and after-class discussions in real life scenarios. Users post their thoughts and experiences from their studies, and other users can like or comment on them. It is suitable for the scenario of attending classes. On the one hand, it strengthens the interaction between the lecturer and the user, and also strengthens the interaction between users. Based on this, I also like Fenda to add a friend function to facilitate further interaction between users.

The difference between the quick questions page in the APP and the short lectures lies mainly in the word "quick".

(13) Quick Question Function

Users can choose the section corresponding to the content they want to inquire about. Each corresponding section has experts and masters in the corresponding field to answer the questions. Users post questions in the corresponding module. The price of each question is fixed at 10 yuan. Such questions can be answered in text or voice form. Other users can listen for free without paying to eavesdrop. Each question will only appear on the publishing platform for 48 hours. During this period, experts in the corresponding field can answer the question. Users select answers they think are useful, and the answerers of the selected answers can share the 10 yuan reward equally.

This feature is consistent with its slogan "Questions and answers that cannot be found in Baidu search ", and is committed to providing users with professional answers to various questions. Compared with Baidu Zhidao, its questions and answers are more professional and authoritative, and the content quality is higher. However, the imperfection of this function is that since the number of consumer users and valuable users is not large, most of the questions cannot be properly answered here. The possibility of users getting satisfactory answers to their questions by searching here is also relatively low. Fenda needs to further expand its user base and data volume to fundamentally improve this problem.

Enter the search page, there is also a search icon in the upper right corner of the homepage.

(14) Search function

This function is achieved through the following points:

1. Keyword search can find related people and topic content. Judging from Fenda’s layout and strategy, it should be more pan-entertainment than vertical operation. So I tried searching for a product on it and only one relevant person was shown. It is recommended to add fuzzy search and guess what you are looking for to provide users with multi-faceted guidance.
2. Classification: There are classifications of people and topics on the search page, which makes it convenient for users to search for related topics and people according to the knowledge categories they are interested in.
3. Provides a wonderful collection, through which users can quickly know the answerers who received the most rewards or are the most popular this week. Users all want to join in the fun. By knowing what other users are paying attention to, users can be better guided to find the content they need.
4. Since Fenda is a product of the bank, Fenda also supports one-on-one meetings with experts in the bank. However, the cost is not low. For ordinary users, it is not cost-effective to spend such an amount to meet with an expert. At the same time, the meeting amount is set at around 1,000, which I personally feel is not appropriate. The pricing of this fee is rather awkward. It is not excessive for a meeting with a truly great expert to cost tens of thousands of yuan. It is recommended to increase pricing and shift from personal user consulting to corporate user consulting.

Enter my page, which mainly contains personal information.

(15) Function to modify personal information

By clicking to open Fenda, you can enter the personal information modification page. I think this function is not reasonable enough. First, clicking on the avatar and nickname does not allow users to modify their personal information, which makes users feel very inconvenient; second, after users have activated Fenda, the button still shows "Activate Fenda" instead of "Settings", which makes users confused about whether they have already activated Fenda.

(16) Coin splitting function

Cents can be used to ask questions, eavesdrop, ask quick questions, and participate in lectures. But in fact, during use, you can pay directly with WeChat even if you don’t have coins. From this perspective, splitting coins is a waste of time. You can get 400 points when you open Fenda for the first time, but there will be no other channels to earn points through activities after that. It is recommended to add tasks such as daily check-in. By participating in activities, you can earn certain points and increase user participation and stickiness. In addition, you can enable the function of giving away 10% more coins for large WeChat recharges of more than 100 yuan, which distinguishes between paying directly with WeChat and paying with coins. Once users top up their account, they will use the product more frequently. Opening a membership system is also a feasible consideration. Users who recharge a certain amount of money to become members will have corresponding membership medals, member-specific discounts, etc. As your membership level increases, the benefits will also increase. By setting up a user development system, the user usage time and frequency can be greatly increased.

(17) I listen, People I listen to, etc.

This type of function allows users to quickly find the people they listen to and their listening history, and makes it easier for users to recall past questions and answers.

The above pictures show the framework layer functions of Fenda. Some settings are not reasonable and appear to be redundant and complicated. Some details need to be improved. The layout of the page, the placement of buttons, tables, and text areas, have not yet reached the maximum effect of these elements. Combined with the page information, we will further conduct an experience analysis of the product functions.

6.3 Product Performance

The entire product adopts a relatively simple style, mainly red and white, with green embellishments. White is used as the main background, and red is used to distinguish important guidance or text explanation parts. The voice part adopts the mainstream green color, and the interaction method is also relatively simple, which is easy for users to get started quickly and reduces the user's learning cost.

VII. Conclusion

Through the description and analysis of Fenda in the above sections, we briefly summarize this product.

First, let’s analyze the reasons why it achieved such a brilliant result within 42 days of its launch in 2016:

1. Fenda seized the critical moment of the rise of paid knowledge platforms;
2. While providing professional knowledge Q&A, Fenda also seized the opportunity of the internet celebrity economy, using the resources accumulated by Guokr.com to invite a large number of internet celebrities to join, making the product a hit on WeChat Moments.
3. Compared with text Q&A, voice is non- imitable and one-way, which enhances the experience of users directly facing internet celebrities, experts and masters.

Secondly, based on the above analysis, if I were the product manager of Fenda, I would give the following product optimization suggestions:

(1) Although Fenda became popular overnight due to the influence of internet celebrities and big Vs , if it wants to develop in the long term, it must weaken the effects of internet celebrities and big Vs, and should encourage and cultivate more daily users to conduct high-quality Q&A. Here are the reasons:

1. First of all, considering that Fenda’s slogan is: “If you can’t find it, go to Fenda”, but so far due to the one-sidedness of internet celebrities and big V answerers, many contents cannot be found on Fenda, and finally users will turn to Baidu. Therefore, grassroots users must also be allowed to join the question-answering process in order to produce better quality questions and answers.
2. Secondly, users brought by the internet celebrities and big V effects will also give up using Fenda as the internet celebrities and big V users fade away. Once the internet celebrities you like stop answering questions for a long time, this part of users will also disappear. This is actually a decentralized process, and only in this way can Fenda's conscientious development be promoted.

(2) Since we want to encourage everyday users to become answerers, we must add a corresponding hierarchy system. The ranking system is divided into two parts. One is that the questioner scores himself to improve his own level on the platform, weakens the focus on big Vs, and tries to select high-quality content from ordinary answerers. Second, the eavesdropper gives a score and rating, for example, 1-5 points to indicate the quality of the content of the questioner and the answerer respectively. This move can also avoid the current situation where many questioners deliberately come up with clever questions to attract a large number of eavesdroppers and thus earn a large amount of rewards, but the questions are actually meaningless.

(3) Strengthen the control and optimization of product content quality. The most popular parts of the current Q&A content are the emotional column and the privacy issues of some internet celebrities, while the questions raised in other columns are rarely answered. This APP will continue to develop into an emotion and gossip column, but the popularity of both is unlikely to last long. It is rare for gossip hot searches on Weibo to stay on the hot search list for two consecutive days. It is necessary to accurately identify one's own positioning and deepen vertical development.

(4) Regarding user activity, there are also two suggestions. First, the current recharge of coins is directly linked to WeChat, with a few yuan for a few hundred coins, and there is no other way to increase the amount of coins. It is recommended to add a sign-in mechanism. Signing in every day will add five coins, and continuous sign-ins can get more rewards. Of course, the coins can also be linked to the user's answers. The higher the level, the more coins you get for signing in. Secondly, you can join the Fenda membership mechanism. Members can get special member labels and can enter the member-only mall to choose gifts for their favorite answerers to promote overall user activity.

Finally, in order to analyze the Fenda product, I also experienced several other knowledge-based paid products, such as Get and 36Kr . Compared with Fenda, these two products are more vertical and sophisticated. As for Fenda, it is actually developing towards pan-entertainment.

Knowledge payment emerged in 2016, and in the future there should be a larger user base and more development possibilities. No matter what kind of knowledge-based paid product it is, the most important thing is to find the right product positioning and user needs. In combination with the current development trend, we will leverage the power and operate accordingly.

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