How to value Xiaohongshu?

How long have you not downloaded a new non-tool APP on your phone? Today, Xiaohongshu is the third-party content platform with the largest user base besides Alibaba, ByteDance, and Tencent. This article analyzes the valuation logic of Xiaohongshu, let's take a look.

Think back, how long has it been since you downloaded a new non-tool app on your phone?

Since the birth of Douyin and Kuaishou, the mobile Internet market seems to have entered a platform period of stock game, and it is difficult for a national-level product with great imagination and a surge in users to emerge in the market.

Correspondingly, the capital market has also become relatively transparent in pricing most mobile Internet platform companies. After all, there has been no record of any company with national-level products being listed on the A-share or Hong Kong stock markets in the past two years. And Xiaohongshu may be the hottest target of the undercurrent.

According to data from QuestMobile in 2024, Xiaohongshu is currently the third-party content platform with the largest user base besides Alibaba, ByteDance, and Tencent.

Figure: 2024 Spring Track User Scale TOP1, APP Monthly Activity List, Source: Questmobile Jinduan Compilation

At the end of April, there were rumors in the market that Xiaohongshu had raised funds in the Pre-IPO round. Although the company quickly denied it, the intention of the popular company, which has been in existence for ten years, to go public is already obvious to everyone. The most important issue for the listing is how Xiaohongshu, as a leader in the content community with a strong label color, should be priced?

Today we will talk about the pre-issue of Xiaohongshu's valuation: the valuation logic of content communities with different business models. One thing that needs to be made clear is that before the specific financial report is disclosed, Xiaohongshu is still shy and shrouded in mystery to the market.

Therefore, due to the limitations of traditional sophisticated valuation methods (such as net present value), we decided to use a rougher industry valuation and comparison method to roughly sort it out.

01 Anchored by user scale

Valuation based on user scale, user growth rate and customer acquisition cost is a valuation logic native to the Internet era and is also the core basis for valuation of most platform-based Internet companies.

The theoretical basis for user scale valuation comes from Metcalfe's Law proposed by Robert Metcalfe, the founder of 3Com, in 1993: The value of a network is equal to the square of the number of nodes in the network, and the value of the network is proportional to the square of the number of users connected to the network, which can be expressed as:

V=K×N² (K is the value coefficient, N is the number of users.)

According to Metcalfe's Law, under the same business model (same K value), the core factor that determines the value of an Internet company is the number of users, and the number of users has the characteristic of geometric growth. The more interactions a single user has, the greater the value.

Of course, the absolute number of users cannot directly reflect the development potential of a company. With the development of multi-terminal interfaces of the mobile Internet and the continuous expansion of its scale, the growth rate of value brought by the user base is actually lower than the growth driven by the business model. If we still simply judge the value by N parties, it is obviously biased.

Currently, in the evolution of valuation of Internet companies, valuation logic based on the number of users has emerged under different incisions, such as customer acquisition cost and retention rate under the SaaS model.

We believe that the core still lies in the synergy of business models and the growth rate of user scale. The higher the synergy of business models and the faster the growth rate, the higher the valuation (short videos to pictures and texts, Pinduoduo to traditional e-commerce). Therefore, we prefer another expression: V=K*K1…*N*(1+user growth rate).

Based on this, let us examine the variable of the value coefficient K.

02 Value coefficient of advertising business

At present, the business models of mainstream content communities are mainly divided into three directions: advertising, e-commerce (including self-operated live streaming), and paid content, and Xiaohongshu mainly involves the first two.

Let’s talk about advertising first. The current valuation ceiling of the advertising business is outside of advertising. Taking the four listed content community targets similar to Xiaohongshu as an example, Weibo and Zhihu, which have lower unit user value (market value/MAU), have lower corresponding business model value coefficients.

Weibo's latest financial report disclosed that advertising business accounted for 86%, and Zhihu's advertising business and membership business accounted for 81%, which is relatively certain but lacks imagination.

In contrast, Bilibili and Kuaishou have a broader business model and a faster growth rate.

Bilibili's advertising business only accounts for 29% of its overall business, while membership value-added and gaming businesses account for 70%. The commercial value coefficient that a single user can utilize is higher.

The same is true for Kuaishou. Although the advertising business accounts for 57%, a portion of the internal circulation advertising revenue serves its own e-commerce business, and the e-commerce business is growing rapidly, which provides sufficient room for market thinking.

Figure: Calculating unit user contribution by user scale and market value, source: Choice financial client, Jinduan calculation

From this form we can also roughly see the value of different business models. Based on this, we add data on user interaction time (the longer the usage time, the easier it is to generate trade behavior).

Taking Weibo, which has the highest proportion of advertising business, as an example, due to the shortage of commercial links, Weibo's ARPU is about 0.7 yuan. According to QuestMobile data, the average usage time of Weibo is about 45% of Kuaishou (about 58 minutes), and the economic output per minute is 0.012 yuan, which roughly represents the economic value of pure advertising business.

Using the same caliber to calculate Bilibili, the economic output per minute of advertising business is 0.047 yuan, about 4 times that of Weibo. Using the same caliber to calculate Kuaishou, the economic output per minute of advertising business (only calculating the external circulation, estimated at 50% of marketing revenue) is 0.09 yuan, about 2 times that of Bilibili.

The advertising value coefficient of video is about 4 times that of pictures and texts. Excluding the impact of ad load, the impact of video length on marketing revenue is not obvious.

03 E-commerce business value coefficient

Let's talk about e-commerce. First of all, a complete e-commerce chain can drive the advertising value of the content platform. Continuing the single user marketing value data of Kuaishou mentioned above, Kuaishou's internal circulation (mainly contributed by internal merchants and anchors, which can be understood as e-commerce driving advertising) accounts for about 50% (estimated at 15% growth rate of the external circulation). The economic output of a single user minute contributed by Kuaishou's complete e-commerce chain (internal circulation advertising) is about 0.09 yuan, which is about twice that of Bilibili.

Secondly, on this basis, in the horizontal value comparison of content e-commerce with a complete chain, the supply and demand matching efficiency determines the industry value of content e-commerce. On the one hand, efficient supply and demand matching efficiency can enhance the value of content and raise the commercial value of marketing business. On the other hand, under the condition of limited content supply, more efficient matching efficiency will enhance the user experience of content users.

According to Huachuang Securities' calculations, Kuaishou, which is represented by the short video model, will have an ad load of about 9% in 2023, while according to Wandian.com, Bilibili, which is represented by medium and long videos, will have an ad load of about 5%. Adding the marketing value contributed by the closed loop of the e-commerce chain, the difference between Kuaishou's marketing revenue and Bilibili's user minute economic output is exactly 4 times.

Finally, if we use the current average valuation of 10-13x for the leading e-commerce platforms (Alibaba, JD.com, and Pinduoduo), we can also get the same valuation range: Among the current mainstream e-commerce platforms, Douyin has the highest monetization rate of about 6%, followed by Pinduoduo's main site at about 5%. Taobao and JD.com (self-operated businesses), which have been hit hard by the two, have taken the initiative to reduce their profits to protect their revenues, and their monetization rates are about 4.2% and 3.2% respectively. Kuaishou started late and its monetization rate in the first quarter of this year was only about 1.5%.

In the first quarter of this year, Kuaishou's e-commerce GMV was 288.1 billion yuan, and the monetization rate was about 1.5%. The average profit of the e-commerce platform was around 50%. It can be inferred that the profit contributed by e-commerce was about 2.16 billion yuan. 10-13xPE corresponds to 21.6-28 billion yuan respectively, which is comparable to the actual market value level.

In summary, using the content community analogy to look at Xiaohongshu's valuation model, it can be summarized as: V=K1 (advertising 3x)*K2 (video ecology 4x)*K3 (e-commerce advertising 2x)*K4 (carrying rate)*N*(1+user growth rate) as shown in the figure below.

Figure: Valuation logic of content communities based on user value, source: Jinduan Research Institute

Of course, it is difficult for all valuation models to be universal. Most Internet companies have subtle differences in their business models, which we call uniqueness x in the valuation model. Some differences will significantly affect the valuation level. For example, the uniqueness of Douyin under its algorithm advantage still far exceeds its overseas performance of its peers, which will give it a valuation performance far higher than its peers.

As for Xiaohongshu, its most typical unique features are two: first, the special user structure that the company has always promoted, with a high proportion of users in high-paying groups (female, first-tier cities); second, the so-called ability to create trends. Brands born based on the "grass-planting" economics are far superior to traditional content communities and content e-commerce. These are all manifestations of the uniqueness of its valuation.

Due to limited space, in the next report, we will use the above model as a framework to specifically calculate the valuation of Xiaohongshu: combined with its own unique X factors, we will explore what its reasonable valuation level is.