The core of traffic flow is to optimize key indicators such as playback volume, likes, comments, and completion rate.

Author: SunnyZ

In my previous article, I mentioned that I would write about the operation and traffic flow of TK because there have been too many projects coming to collaborate with TK recently. To put it bluntly, the traditional old methods of Web3 are no longer sufficient [namely task platforms, collaborative PR, AMAs, or KOLs], and the exchange volume of ton has already reached a bottleneck. At this time, TikTok [hereinafter referred to as TK], as the largest traffic pool, has become a battleground. Effectively utilizing TK's KOLs can sometimes yield much better conversion results than Twitter. TK is still a huge traffic gap, and I personally believe that this year marks the beginning of the integration of Web3 and TK. If we do not seize this wave of growth in TK, we are likely to miss out on this new wave of traffic. Let’s take a look at how to operate accounts and what strategies to use to gain traffic.

Two Characteristics of Traffic

Currently, TK is akin to Kuaishou in 2019, and the precision of traffic is such that TK's video data is still far from sufficient. Therefore, the hashtags of influencers are not yet well-developed. Currently, TK's streaming method is different from Douyin; it does not prioritize pushing to private pools but directly promotes in the same public pool. Thus, for us looking for influencers across borders, "vertical influencers" is currently a false proposition in TK. In the process of traffic conversion, we must first understand the two characteristics of TikTok traffic: precision and immediacy.

1. Precision

We know that in the conversion funnel, traffic must come before conversion. Therefore, before considering how to convert, we need to solve two problems: first, how to acquire traffic, and second, how to acquire precise traffic. From the perspective of precision, traffic can be divided into precise traffic and non-precise traffic. Comparatively, acquiring traffic is not the most difficult part; acquiring precise traffic is the biggest challenge faced by projects, and only precise traffic can allow us to complete the closed loop. For most traffic flow behaviors, the value of precise traffic is thousands of times higher than that of non-precise traffic. When our project team is doing TK traffic flow, we must find the precise KOLs in our niche; even if they have fewer followers, if the conversion effect is good, we can "spend little to look impressive."

2. Immediacy

From the perspective of traffic immediacy, once the traffic of the video is pushed to a large number of TK users, these users will only see the video at the moment it is pushed. This moment is considered "traffic passing through our video." The probability of these users revisiting the video in the future is negligible, so the traffic pushed to our video by the system is only valuable "while passing through." Regardless of how many followers a TK account has or how many views a short video has, once that traffic has passed, it is merely a number.

To address these two characteristics of TK traffic, if we want to achieve conversion in TK's vast traffic pool, we need to solve it from two aspects. The first aspect is to learn to filter traffic. Since the precision of traffic is very important, we first need to learn how to filter traffic to find the precise traffic pool, which is an essential skill for every TK operator. During the distribution of TK traffic, the system will distribute content to corresponding TK users based on different video or live stream content, so the core way to filter traffic is to optimize content. There are many tools and methods for this; the simplest include language tools, cultural tools, music tools, etc. We can use these tools to control the direction of video traffic. For example, if the project party wants to advertise in Thailand, then users from other regions are not precise for us, so we can insert Thai language copy into the video content, which greatly increases the chance of filtering out traffic from other regions. The second aspect is to prepare the conversion chain in advance. Due to the immediacy of traffic, we need to prepare the conversion chain and the "pool" to receive it before the traffic arrives. So what methods can be used to receive traffic? If we expect to complete the full token trading loop within TK, we can have influencers place the project party's token trading link in their pinned information or redirect to CEX or DEX, and then check the conversion rate through a single link. The TK platform always pursues "future" traffic; the traffic that has "passed" is almost worthless. Regardless of how good the past data of an influencer is, that is all sunk cost. Even if an influencer's video shows 10 million views, that traffic will not bring new traffic to new project parties in the future; that number only represents traffic that has come before. Therefore, from the traffic perspective, what we need is always the next wave of traffic.

So where does traffic come from:

There are many sources of short video traffic, such as recommended traffic, follower traffic, homepage entry, search entry, music entry, tag entry, etc. Among these, the most valuable traffic in TikTok short videos is undoubtedly the system-recommended traffic, commonly referred to as "For You" traffic. The more traffic this channel has, the better the platform judges the video quality, leading to further recommendations and greater potential for playback volume. When assessing whether the source of traffic for a short video is healthy, we generally require that the proportion of "For You" traffic be greater than 30%. If it is below 30%, we need to consider whether the video or account is being limited in traffic. [Data source: Sky]

Logic of TK Short Video Recommendation Algorithm

Before discussing the operation methods of TK accounts, we first need to understand the logic of TK short video recommendation algorithms. Everyone knows that TK will push content that interests you based on your behavior and preferences.

In summary, the core of traffic flow is to optimize key indicators such as playback volume, likes, comments, and completion rate. What is the essence of optimizing these indicators? It is optimizing content. As long as the content quality is up to par and the audience's preferences are accurately grasped, the video will naturally gain more traffic.

The video traffic recommendation on the TK platform is conducted in stages. In the first-level traffic pool, a video will receive 200 to 500 views. Specifically, after a video is published, the platform will first push it to 200 to 500 viewers. The platform will then evaluate the video's popularity based on the interaction behaviors of these viewers (likes, comments, shares, etc.).

If the feedback is good, the video will enter the second-level traffic pool, with views reaching around 2000. If the video continues to perform well in the second pool, it will advance to the third-level traffic pool, where views may reach 5000 or even tens of thousands. This process will continue until the video performs poorly in a certain traffic pool, at which point recommendations will stop.

It is worth noting that the first-level traffic pool is usually aimed at users in the account's location. For example, if the account's IP address and data location (i.e., the country/region of the TikTok account) are in the United States, the first-level traffic pool will primarily push to American viewers. However, starting from the second-level traffic pool, regional restrictions will gradually disappear, and the video will have the opportunity to gain global traffic.

So, what is the key to acquiring traffic? The answer is content. Even if the account's location and first-level traffic pool are in the United States, as long as the video content caters to the preferences of Southeast Asian viewers, the system will recommend it to users globally who are interested in Southeast Asian culture, thus making it easier to gain traffic from the Southeast Asian region.

Of course, when managing traffic, it is essential to remember: traffic is essentially random. This is a common characteristic of all traffic. Our task is to continuously reduce this randomness and transform the uncertain random game into a controllable probability game.

Data feedback is key to optimization and iteration. By deeply analyzing data, we can better understand the essence of things. Data analysis is also indispensable when operating TK accounts, as it helps us gain deeper insights into the platform and clarify optimization directions.

TK Influencer Collaboration

How to select KOLs? Many Crypto KOLs have a lot of followers, but their engagement data is average. Here, different configurations can be made based on project strategies. For example, if the project party has a relatively large promotional event, they can configure 1-2 major KOLs and several smaller KOLs; choosing the right hashtags can easily help them go viral.

Of course, there is another strategy, which is to target and burst a specific person's TK following list. If you know the following list of a prominent influencer, you can directly select which KOLs to work with.

Wherever there is traffic, there is value. Since the environment for acquiring traffic is variable and not singular, being able to stably acquire traffic amidst these changes is both an important and challenging ability.

The first step in collaborating with influencers is to find them. We need to conduct a preliminary screening of TK influencers based on characteristics such as target categories, audience groups, and marketing objectives. Here are four main methods:

1. Find through the TK App Directly searching for influencers through the TK App is one of the most basic and effective methods. Search for keywords related to the product on TikTok, find relevant videos, and filter out content that performs well (e.g., significantly higher playback volume than similar videos), then visit the creator's homepage to make contact. This method can help find a large number of influencers who already have a certain follower base in related fields.

Influencer homepages usually provide contact information: some will directly leave a business negotiation email; if there is no direct contact information, they often have a landing page link on their homepage, which can be found in "About Us" or "Contact Us." You can also leave a message in the video comments section and wait for the influencer to contact you.

2. Actively connect through TK Influencer Plaza This method is more direct and precise than searching directly on TK, but currently, there are relatively few influencers in the Influencer Plaza;

3. Follow influencers who collaborate with competitors;

4. Find Crypto KOL MCNs, as they are often more professional and familiar with KOLs;

Many project parties actually do not think clearly about their collaborations. They do not have predetermined promotional goals or their goals are not quantifiable. Before collaborating with influencers, it is essential to determine the promotional goals for this collaboration, which means understanding what effects you hope to achieve through this collaboration, whether it is to increase brand exposure, increase follower count, boost token trading volume, or find quality customers, etc. After determining the promotional goals, it is crucial to set several quantifiable indicators to measure whether this promotion has met expectations. If quantifiable indicators are not set, it will ultimately lead to uncertainty in optimizing strategies or results that do not align with expectations, such as intending to increase sales but instead increasing exposure, which can be counterproductive.

TK Data Analysis

In TK data analysis, we mainly focus on two types of indicators: video indicators and account indicators.

Video indicators include: completion rate, like rate, comment rate, share rate, traffic source, as well as playback volume, total playback duration, average playback duration, audience distribution, and proportion.

Account indicators include: follower-to-like ratio, follower distribution, number of follows, number of followers, number of likes, number of videos published, time of first video publication, recent publication frequency, and gender distribution, etc.

By analyzing these indicators, we can comprehensively assess the performance of an account, applicable to both our own accounts and other quality accounts.

Video Indicators

First, we will analyze the indicators from the video dimension, examining what issues each important indicator reflects, the measurement standards for these indicators, and how to optimize videos based on these indicators. However, it is important to note in advance that the data forms will vary for videos with different purposes, types, and categories. For example, some videos may have a high number of likes, while others may have a higher comment interaction rate, and some may focus on sharing and dissemination. The measurement standards for the indicators recommended below are generally applicable across most categories, so remember to be flexible when referencing them.

Completion Rate

The completion rate refers to the proportion of viewers who watch the video to 100% of its progress compared to all viewers. The completion rate is one of the most important indicators among many video metrics and is a key factor affecting video playback volume. For project parties, how long users are willing to spend on your product is a critical indicator. The completion rate of videos on the TK platform is strongly correlated with the time viewers spend. A high completion rate indicates that viewers are interested in the video's content and are willing to spend time watching it. The platform often considers such videos to be relatively high quality and will further recommend them. Based on practical data, the e-commerce industry generally sets the minimum benchmark for completion rates at 30%. If the completion rate is below 30%, it is deemed unacceptable, and the video must be optimized【Source: Sky】.

From the audience's perspective, what circumstances lead viewers to not finish watching a video and swipe away? Generally, there are several reasons:

(1) The first three seconds of the video are not engaging enough. The viewer drop-off rate is often highest in the first three seconds, so we can examine whether the content in the first three seconds is eye-catching and whether there is significant room for optimization.

(2) The main content is revealed in the first three seconds. Many creators know that the first three seconds of a video must be captivating, so they cram the main and exciting content into those first three seconds, leading viewers to have low expectations for the subsequent content. When viewers have no expectations, they will naturally choose to swipe away.

(3) The pacing is sluggish. On the TK platform, viewers have limited patience for each video. If the pacing is weak and fails to fully engage the viewer's senses, it will lead to traffic loss. This is especially true for medium to long videos, which require a strong sense of rhythm and high content density to make viewers feel that every second spent on the video is worthwhile. Therefore, if the completion rate is below 30%, the above three points can be primarily referenced for optimization.

Based on these principles, project parties can observe whether the influencer's follower count, post data, and like count match, which can help identify influencers who can genuinely drive sales.

Like Rate

Like rate calculation formula: Like Rate = Total Likes / Total Views.

Compared to the completion rate, the like rate has a smaller impact on playback volume, but it is still a metric worth optimizing. When the like rate is below 4%, there is room for optimization. From the audience's perspective, they will like a video in two situations: (1) The video has collectible value. Many people see good videos while scrolling through TK, and if they do not like or save it in time, it becomes difficult to find that video later. Therefore, enhancing the practical value of the video can encourage viewers to like, save, and rewatch it. (2) The video is highly entertaining. Interesting content can stimulate viewer interest, which is a key factor affecting the like rate. If the like rate is low, efforts can be focused on enhancing the video's entertainment value. Here, we can look for influencers who create very engaging videos.

Comment Rate

Comment rate calculation formula: Comment Rate = Total Comments / Total Views.

If the comment rate is below 0.4%, there is room for optimization. Here are three methods to improve the comment rate:

Share Rate

Share rate calculation formula: Share Rate = Total Shares / Total Views.

Similar to Twitter, a good post requires that likes, comments, and impressions match up.

Account Indicators

Follower-to-Like Ratio

At the account dimension, the first indicator worth focusing on is the follower-to-like ratio, calculation formula: Follower-to-Like Ratio = Total Followers / Total Likes.

The follower-to-like ratio can intuitively reflect the stickiness of the account's followers. If the ratio is too low, it indicates that the account's follower stickiness is low, and the content attracting viewers only stays at the video level without rising to the influencer's persona or account level. The standard for determining the follower-to-like ratio is generally that a ratio greater than 1:6 indicates high follower stickiness and precise followers; a ratio below 1:6 suggests that the video has some room for optimization. For example, some accounts have a follower-to-like ratio of 1:15 or 1:20, which is a typical sign of low follower stickiness.

Follower Distribution

The second indicator is follower distribution. We often simply divide it into gender distribution, regional distribution, and age distribution. When selecting crypto influencers, the ratio of influencers should be configured based on the type of your project.

Acknowledgments

Many thanks to the friends who provided various information support for this article! Since I have not participated much in TK operations myself, much of the content in this article references Sky's book and the experiences of my friend Mengmeng, who is actively involved in TK operations. I also recommend that those who want to learn TK operations read more and learn more. The KOL cases mentioned in the article come from Wayne, and if you need resources from TK influencers in the cases, feel free to contact me. I also welcome everyone to exchange ideas with each other. My TG: SunnyZ_Crypto【Please excuse the slow replies】

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