Unveiling the Three Core Money-Making Techniques for AI Viral Article Writing on Public Accounts
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Perhaps this is also the headache you often encounter when working on AI viral article writing projects for public accounts, unable to figure out why, and then considering taking a course, but the ones that catch your eye are too expensive... Some may give up, but those who persist often succeed and achieve substantial earnings.
Why do ordinary people always take longer to see results in projects compared to the experts?
Actually, it comes down to insufficient understanding of the project itself—specifically, not grasping the core money-making principles. Because of this, you might find yourself exerting effort aimlessly, trying various approaches without certainty about which is correct...
In reality, those who succeed in AI viral article writing have essentially mastered the following three core money-making techniques, which prevent them from feeling lost when encountering initial challenges like ordinary people do.
Account setup techniques + AI writing techniques + Ad revenue optimization techniques
Uncle Qi is someone who enjoys sharing. Due to space constraints, the following will only address the most common issues people face when setting up public accounts.
Consider this: If you are proficient in vertical content creation and AI writing tools in your field, what is the biggest gap between you and the experts in new account operations? That’s right—it’s the account setup techniques for public accounts.
Based on Uncle Qi’s interactions with many followers, most people fail to set up their accounts even after publishing dozens of articles... Naturally, they don’t achieve significant earnings. Without proper account setup, there’s no stable traffic from public account recommendations, making it difficult to produce viral articles.
Yes, you heard it right. In Uncle Qi’s view, public accounts now also emphasize the concept of account setup.
The standard for determining whether a new WeChat public account has officially launched is: assessing whether the account has entered the recommendation pool ↓ ↓ Specifically, this means the account will consistently receive recommendation traffic as long as it publishes vertical content.
Don't understand what this means? Keep reading with your questions in mind.
The principles and techniques for launching an account discussed below are not only applicable to this project but also universally applicable to any self-media WeChat public account. For example, Uncle Qi's new account gained nearly 2,000+ followers in about half a month.
The current traffic is quite good, thanks to the application of the principles and techniques for launching an account.
Moreover, the recommendation traffic for articles from this new account has already started appearing. However, due to certain issues, the account's recommendation has not yet entered the pool, which is also the direction Uncle Qi will optimize next.
Therefore, if you don't understand the principles and techniques for launching an account, you will encounter a series of problems, doubting and denying yourself before even earning revenue from traffic monetization...
Below, Uncle Qi will share insights on launching a new WeChat public account.
Regarding the application of the following techniques for launching a WeChat public account, the prerequisite is that your account and content dimensions meet the basic standards for accounts eligible for recommendation traffic on WeChat.
Uncle Qi especially emphasizes these three key content dimensions: content verticality, update frequency, and originality.
After understanding these hard requirements, let’s discuss the principles for launching an account:
1) Principles of Labeling for New Official Accounts
Have you ever wondered how the system recommends traffic for articles from a new official account with zero followers?
Of course, the recommendation algorithm for official accounts is a black box, and no one except the official team knows the specific details. However, based on Uncle Qi's experience in managing multiple official accounts and understanding of recommendation algorithms, the following points can be summarized:
① Content Labeling
Setting aside social chain recommendations, the core of the official account recommendation mechanism lies in the interest label matching algorithm. This involves extracting content labels and distributing content to users with similar reading interests. Therefore, it's essential to strategically place core keywords in the article's title and body that align with the account's content positioning.
The key to triggering recommendation traffic lies in: consistently updating original and vertical content. In other words, accumulating your steadily updated original vertical content in exchange for stable recommendation traffic from the platform. If you were the platform, wouldn't you hesitate to waste traffic on an inactive account that posts sporadically?
Perhaps you might say... I've been doing this, and after posting for a while, I did get recommended traffic, even had a viral hit... But after the viral hit, when I posted again, the readership dropped back to single or double digits...
This brings up factors like account entry into the recommendation pool, content quality, and whether the content gets recommended again. Setting aside content quality and re-recommendation issues, after managing multiple accounts in Uncle Qi's field, it was observed that there's also the phenomenon of account entry into the recommendation pool.
In essence, once an account is labeled, publishing vertical content will result in recommended traffic. However, if your public account hasn't accumulated sufficient weight or hasn't been labeled, the platform won't provide consistent and stable natural recommendation traffic. If this is unclear, think of it like Douyin's recommendation mechanism.
New accounts typically receive 300-500 initial natural traffic based on video content labels. If a video goes viral, the account may then be labeled. Subsequent content can expect natural traffic around 1k-5k, with popular content further boosting the account's weight, leading to positive growth in all metrics.
The recommendation mechanism for public accounts follows a similar logic.
Account Labeling
After reading the above, you should understand that labeling an account takes time, as it requires extensive data modeling. Achieving account labeling is the ultimate goal of account inclusion in the recommendation pool.
Key factors in account labeling include: content label + collection label accumulation, and the accumulation of a vertical audience.
Example of Account Collection Labels
After accumulating these core factors over time, your account's weight and labels will typically emerge. This leads to account inclusion in the recommendation pool, resulting in stable natural recommendation traffic. Those familiar with Douyin or video platforms will understand the significance of stable recommendation traffic.
Of course, if you stop posting for a while, your recommendation traffic may drop back to zero...
Next comes Uncle Qi's soul-searching question: Why do accounts posting similar content topics, sometimes even with identical titles, get 100K+ views while yours only gets thousands or tens of thousands?
Based on Uncle Qi's experience, there are two scenarios to explain this:
① Difference in follower base
If your account has fewer followers while the other is an established account with a large follower base, naturally the same viral-worthy content will perform differently when posted on your account versus theirs. Their audience is more vertically aligned and has a substantial baseline traffic volume, making it easier to trigger additional recommendation traffic compared to yours. Of course, there's also likely an algorithmic evaluation of recommendation traffic data.
② Recommendation traffic algorithm evaluation
If we're comparing newly established accounts where yours gets thousands of views while another gets 100K+, what does this indicate?
Let's take Douyin/Video Accounts as examples. As we know, these platforms have content performance metrics that determine traffic tiers. When a tier's metrics are met, the system continues pushing your content. The outcome could be: going viral across the entire platform, having recommendations terminated due to unmet metrics, or being limited by the vertical niche's user pool size. Therefore, once the public account recommendation mechanism is triggered, the initial traffic allocation will almost certainly involve algorithmic evaluation of recommendation metrics!
From operating multiple accounts, Uncle Qi has observed some articles receiving recommendation traffic for 5-6 days while others only get 2-3 days. Well...public account recommendation traffic is allocated by days, not by hours.
Of course, obtaining a large amount of recommended traffic can lead to an increase in revenue for traffic owners. However, from the perspective of follower growth, the situation is not so optimistic. The content tags and user interest tags still need continuous refinement by the WeChat Official Account system for better accuracy. Currently, once traffic increases, the precision of incoming users tends to deviate.
In summary, under rigid foundational conditions, once you understand the principles of content tags and account tag recommendations, you will realize why new accounts' content fails to enter the recommendation pool or why data returns to square one after a viral post. You will also understand why similar content topics can result in differences in readership and revenue.
Now that we know how to accelerate the process of account recommendation traffic, which is essentially accelerating the account labeling process, Uncle Qi will share techniques for growing new accounts—methods to speed up account labeling.
2) Techniques for Growing New WeChat Official Accounts
As mentioned earlier by Uncle Qi, there are two core factors affecting account labeling: content tags + collection tag accumulation and the accumulation of a vertical readership base for the account.
To accelerate account labeling, you can simultaneously work on these two factors:
- Content tag accumulation + collection tag accumulation
After confirming the account positioning and content direction, strategically layout core keywords in your articles. Over time, with continuous publishing, content tags and collection tags will accumulate. Once a certain threshold is reached, the system will recognize the account's content domain attributes and assign appropriate labels.
Content is the fundamental framework of self-media accounts. Avoid sacrificing quality for the sake of quantity accumulation. While stable content updates are slow, Uncle Qi's experience suggests that combining the following operations can accelerate the account labeling process.
② Accumulating a vertical readership for the account
What does this method mean? There are two operational levels.
First understanding: Accumulating article reading interaction data
Published articles need to accumulate reading and interaction data. New accounts typically have no weight or traffic when they start posting. Therefore, it's necessary to introduce cold-start traffic to the account's articles and build initial interaction data for the content.
For personal public accounts, methods to introduce article traffic include: sharing on moments, forwarding to mutual aid groups, industry exchange groups, big accounts promoting small accounts, reprints, etc. New accounts usually gain weight within 3-5 days, which may accelerate recommended traffic. In the early stages, don't worry too much about audience precision. The initial traffic introduction is aimed at activating the new account's weight. Moreover, the initially attracted non-precise audience will unfollow you as you continue to update your content.
Why is this the case? Uncle Qi has shared a screenshot of the frequent reader metrics. Do you understand now?
Second understanding: Increasing followers for public accounts
This is straightforward—precise users come with reading interest labels.
Building an account inherently requires focusing on follower growth metrics, especially when starting from zero followers with no existing authority. Accumulating precise followers significantly aids in boosting engagement metrics for your content. Over time, this process accelerates the labeling of your account. After gaining precise followers, both the audience's reading habits and content labels will synergistically enhance the account's performance.
If speed is a priority, paid methods can be used to grow followers. However, content quality remains crucial since users follow you primarily for the value you provide.
Through an in-depth understanding of this project's fundamentals, we've identified the first key to monetization: mastering the techniques for launching a new public account. By analyzing content and account label recommendations, we've thoroughly explored the strategies behind label-based recommendations. The conclusion is clear: account labeling is the core factor influencing the sustainability of recommendation traffic.
Finally, by strategically influencing the factors that affect account labeling, new accounts can quickly establish themselves and secure stable, continuous recommendation traffic.