Author of the article: Cube Labs

Source: Cube Labs

In my previous article, I mentioned that I would write about TikTok's operations and traffic investment because there have been so many projects coming forward to collaborate on TikTok recently. To put it bluntly, the traditional Web3 methods are no longer sufficient [i.e., task platforms, PR collaborations, AMAs, or KOLs], and the token exchange has reached a bottleneck stage. At this time, TikTok [hereinafter referred to as TK] as the largest traffic pool has become a battleground. How to effectively utilize TikTok's KOLs for conversion is sometimes much better than Twitter. TikTok remains a massive traffic reservoir, and I personally believe that this year marks the year of the integration between Web3 and TikTok. If we do not seize this wave of growth in TikTok, we are likely to miss this new traffic round. Let's see how to operate accounts and what strategies to use to gain traffic.

Two characteristics of traffic

Today's TikTok is equivalent to Kuaishou in 2019 regarding traffic precision. TikTok's current video data is far from enough, so the hashtag system for influencers is still not complete. Currently, TikTok's streaming mode is different from Douyin; it does not prioritize pushing to private pools but directly promotes in the same public pool, which makes finding influencers across borders similarly challenging. 'Vertical influencers' is currently a misleading concept on TikTok. In the process of traffic conversion, we first need to understand two characteristics of TikTok traffic: precision and immediacy.

1. Precision We know that in the conversion funnel, there must be traffic first before conversion. Therefore, before considering how to convert, we must address two issues: one is how to obtain traffic, and the other is how to obtain precise traffic. From the perspective of precision, traffic can be divided into precise traffic and non-precise traffic. Comparatively speaking, obtaining traffic is not the hardest part; obtaining precise traffic is the biggest challenge faced by the project. Only precise traffic can allow us to complete the closed loop. For most traffic behaviors, precise traffic can be worth thousands of times more than non-precise traffic. When our project party does TikTok traffic investment, we must find precise KOLs in our niche; even if they don't have many followers, good conversion effects can allow us to 'spend little to achieve great results'.

2. Immediacy From the perspective of traffic immediacy, when a video is pushed to a large number of TikTok users, these users will only see the video at that moment, which is viewed as 'traffic passing through our video'. The probability of these users revisiting the video in the future can be ignored, so the traffic pushed to our video by the system is only valuable 'while it is passing through'. Regardless of how many followers a TikTok 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 TikTok traffic and achieve conversion in the vast traffic pool, we need to address two aspects. The first aspect is to learn to filter traffic. Since the precision of traffic is very important, we must first learn how to filter traffic to find a precise traffic pool, which is a necessary skill for every TikTok operator. During the distribution of TikTok traffic, the system distributes to corresponding TikTok users based on the content of different videos or live streams, so the core method of filtering traffic is to optimize content. There are many tools and methods, the simplest being language tools, cultural tools, and music tools. We can use these tools to control video traffic direction. For example, if the project side wants to target Thailand, then users from other regions would be considered imprecise for us. We can insert Thai language text into the video content, significantly increasing the likelihood of filtering out traffic from other regions. The second aspect is to prepare the conversion pathway in advance. Given that traffic has immediacy, we must prepare the conversion pathway and the 'pool' to receive traffic before it arrives. So what methods can be used to receive traffic? If we expect to complete the full token trading loop within TikTok, we can have influencers include the project party's token trading links in their pinned information, or direct them to CEX or DEX, and then check the conversion rate via a single link. TikTok platform always pursues 'future' traffic; traffic that is already 'past' is almost worthless. Regardless of how good an influencer's past data is, it is all sunk cost. Even if an influencer's video shows 10 million views, this traffic will not bring new traffic to the new project. This number only represents traffic that has come in the past. Therefore, from the perspective of traffic, what we need is always the next wave of traffic.

So where does the traffic come from:

There are many sources of traffic for short videos, such as recommended traffic, fan traffic, homepage access, search access, music access, tag access, etc. Among these, the most valuable traffic on TikTok short videos is undoubtedly the traffic recommended by the system, commonly referred to as 'For You' traffic. The more traffic from this channel, the better the platform judges the video quality, leading to increased recommendations, and thus greater potential for views. When we assess whether the source of traffic for a short video is healthy, we generally require that the proportion of 'For You' traffic is 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]

The logic of TikTok short video recommendation algorithms

Before discussing TikTok account operation methods, we first need to understand the logic of TikTok's short video recommendation algorithms. Everyone knows that TikTok pushes content that you are interested in based on your behavior and preferences.

Overall, the core of traffic investment is optimizing key metrics such as views, likes, comments, and completion rate. So what is the essence of optimizing these metrics? 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 TikTok platform's video traffic recommendation is done in stages. In the primary traffic pool, videos will receive 200 to 500 views. Specifically, after publishing a video, the platform will first push it to 200 to 500 viewers. The platform will then evaluate the video's popularity based on these viewers' interaction behaviors (likes, comments, shares, etc.).

If feedback is good, the video will enter the secondary traffic pool, with views reaching around 2,000. If the video continues to perform well in the secondary pool, it will be promoted to the tertiary traffic pool, where views may reach 5,000 or even tens of thousands. This process will continue until the video performs poorly in a certain traffic pool, at which point the recommendations will stop.

It is worth noting that the primary traffic pool usually targets 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 primary traffic pool will mainly push to US audiences. However, from the secondary traffic pool onward, geographic restrictions gradually disappear, and the video has the opportunity to gain global traffic.

So what is the key to gaining traffic? The answer is content. Even if the account's location and primary traffic pool are in the United States, as long as the video content caters to the preferences of Southeast Asian audiences, the system will recommend it to users worldwide who are interested in Southeast Asian culture, thereby making it easier to gain traffic from Southeast Asia.

Of course, when managing traffic, it's important to remember: traffic inherently has randomness. This is a common characteristic of all traffic. Our task is to continuously reduce this randomness and turn the uncertain random game into a controllable probabilistic game.

Data feedback is the key to optimization and iteration. By deeply analyzing data, we can better understand the essence of things. In operating TikTok accounts, data analysis is also indispensable; it helps us gain a deeper understanding of the platform and clarify optimization directions.

TikTok influencer collaboration

How to select KOLs, many crypto KOLs have many followers, but their interaction data is average. Here, different configurations can be made based on project strategies. For instance, if the project has a large promotional activity, one or two large KOLs can be configured, along with several smaller KOLs, and if the hashtags are chosen well, it will be very easy to go viral.

Of course, there is another strategy, which is to directly target a specific individual's TikTok following list. If you know the list of a top influencer's following, you can directly choose which KOLs to select.

**Where there is traffic, there is value.** Since the environment for obtaining traffic is variable rather than singular, being able to steadily acquire traffic amid such changes is a vital and challenging ability.

The first step in collaborating with influencers is to find them. We need to conduct a preliminary screening of TikTok influencers based on characteristics such as target category, audience group, and marketing objectives. The following introduces four main methods:

1. Find influencers directly through the TikTok app. Searching for influencers directly through the TikTok app is one of the most basic and effective methods. On TikTok, search for keywords related to products, find relevant videos, filter out content that performs significantly better than similar videos, and then go to the creator's homepage to contact them. This method can help find many influencers who already have a certain follower count in related fields.

Influencers' homepages usually provide contact information: some will directly leave a business negotiation email; those without direct contact information often leave 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 the TikTok influencer square. This method is more direct and precise than searching directly on TikTok, but there are relatively few influencers currently in the influencer square.

3. Focus on influencers collaborating with competitors

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

Many project parties actually collaborate without much thought, failing to determine promotional goals or having quantifiable targets. Before collaborating with influencers, it's crucial to set clear promotional goals for this collaboration, such as whether the aim is to increase brand exposure, follower count, token trading volume, or find quality clients, etc. After determining the promotional goals, it’s essential to set several quantifiable metrics to measure whether the promotion has met expectations. If no quantifiable metrics are set, it can lead to uncertainty in optimizing strategies or results not aligning with expectations, such as intending to increase sales, but instead only increasing exposure, which can be counterproductive.

TikTok data analysis

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

Video metrics include: completion rate, like rate, comment rate, share rate, traffic sources, as well as views, total play duration, average play duration, audience distribution, and proportions.

Account metrics include: follower-to-like ratio, follower distribution, 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 metrics, we can comprehensively assess the performance of an account, applicable to both one’s own account and other quality accounts.

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

Video metrics include: completion rate, like rate, comment rate, share rate, traffic sources, as well as views, total play duration, average play duration, audience distribution, and proportions.

Account metrics include: follower-to-like ratio, follower distribution, 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 metrics, we can comprehensively assess an account's performance, applicable to both one's own account and other quality accounts.

Video metrics

We first analyze the metrics at the video level, examining what issues each important metric reflects, what the measurement standards are, and how to optimize videos through these metrics. However, it is important to note in advance that different purposes, types, and categories of videos will exhibit different data forms. For instance, some videos may have high like counts, others may have high comment interaction rates, while some videos focus on sharing and dissemination. The following recommended metric measurement standards are generally applicable to most categories, and flexibility should be exercised when referring to them.

Completion rate

The completion rate refers to the proportion of viewers who complete 100% of the video viewing progress among all viewers. The completion rate is one of the most important metrics among many video metrics and is a key factor affecting video views. For project parties, how long users are willing to spend on your product is a crucial metric. The completion rate of videos on the TikTok platform is strongly correlated with the time viewers spend. If the completion rate is high, it indicates that viewers are interested in the video's content and are willing to spend time watching it. The platform often considers such videos relatively high quality, leading to further recommendations.

Based on the summary of practical data, the e-commerce industry generally sets the minimum benchmark for determining whether the completion rate is up to standard at 30%. If the completion rate is below 30%, it is considered unacceptable, and the video must be optimized. [Source: Sky] At this point, thinking from the audience's perspective, what situations would lead viewers to not want to finish the video and swipe away? Generally speaking, there are several reasons: (1) The first three seconds of the video are not engaging enough. The audience's drop-off rate is often highest in the first three seconds, so we can examine whether the content of the first three seconds is eye-catching and whether there is significant room for improvement. (2) The content is fully revealed in the first three seconds. Many creators understand that the first three seconds of a video must be captivating, thus cramming the main and exciting content into those three seconds, leading to viewers having low expectations for the subsequent content. When viewers have no expectations, they will naturally choose to swipe away.

(3) Slow rhythm. On the TikTok platform, the audience's patience for each video is limited. If the video's rhythm is weak and fails to adequately capture the audience's senses, it will lead to traffic loss. Particularly for medium to long videos, it is essential that the video possesses a strong rhythm and high content density, making each second spent on the video feel worthwhile to the audience. Therefore, if the completion rate is below 30%, the above three points can be used as primary references for optimization.

Based on these principles, project parties can observe whether the number of an influencer's followers matches their post data and like counts, thus finding influencers who can genuinely generate leads.

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 views, 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 are likely to like a video in two cases: (1) The video has collectible value. Many people find good videos when scrolling through TikTok, and if they don't like or save it in time, it becomes difficult to find the video later. Therefore, improving the practical value of videos can motivate viewers to like, save, and watch repeatedly. (2) The video is highly entertaining. Interesting content can stimulate audience interest, which is a key factor affecting the like rate. If the like rate is low, focus on enhancing the video's entertainment value. Here we can look for influencers who produce very smooth 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.

In fact, like Twitter, likes, comments, and impressions must match to be considered a good post.

Follower-to-like ratio of account metrics

At the account level, the first metric worth focusing on is the follower-to-like ratio, calculated as: Follower-to-like ratio = Total followers / Total likes. The follower-to-like ratio can intuitively reflect the stickiness of an account's followers. If the follower-to-like ratio is too low, it indicates that the account's follower stickiness is low, and the content that attracts viewers only remains on the video level, without rising to the level of the influencer's persona or account. The determining standard for the follower-to-like ratio is generally greater than 1:6, indicating high follower stickiness and precise followers; below 1:6 indicates there is 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 metric is follower distribution. We often simply divide it into gender distribution, regional distribution, and age distribution. When selecting crypto influencers, it's essential to configure the ratio of influencers based on the type of the project.

Acknowledgments

Many thanks to the friends who provided various information support for this article! Special thanks to MetaEra for their strong support. Because I personally have not participated much in TikTok operations, much of this article's content references Sky's book and the experiences of friends like Mengmeng who actively engage in TikTok operations. I also recommend that those who want to learn TikTok operations read more and learn more. The KOL examples in this article come from Wayne, and if needed, please feel free to contact me regarding the TikTok influencer resources mentioned in the case.