Introduction
Recently, data for Telegram bots and Miniapps has shown a clear downward trend.
Once upon a time, with the explosive growth of Clicker games, Telegram Miniapp became the focus of the blockchain field.
However, behind the prosperity lies a crisis.
The TON Foundation has overly relied on Clicker games in its support strategy. While this has brought a surge in users and data in the short term, it has also sown the seeds of ecological imbalance.
As users' freshness fades, the homogenization and lack of depth in Clicker games gradually become apparent, and the entire ecosystem begins to suffer backlash.
Now, as the tide recedes, it is necessary to deeply reflect on the strategic errors of the TON Foundation and seek new narratives that can lead the next phase of TON ecosystem development.
We counted BOT sources from Telegram Apps Center, TON App, The Open League (see appendix)
1. The trend of significant decline in MAU is hard to stop.
In the past month, OGenLab has continuously monitored 820 Telegram projects.
From October 1 to October 31, although data cannot be deduplicated, the cumulative monthly active user count (MAU) reached 879,922,503.
But behind this huge number hides a concerning sharp decline.
In one month, the total MAU decreased by 295,971,112 (not deduplicated), equivalent to a 33% drop.
This significant drop reveals a rapid decrease in user activity, indicating that the entire ecosystem is experiencing unprecedented challenges.
[Source: https://x.com/OGenLab/status/1854060874304221435]
Through daily data analysis, OGenLab found that this decline shows an amplifying trend. Especially for large projects with over 5 million users, the initial MAU decline speed was relatively slow, seemingly maintaining some stability. However, over time, the decline speed of these projects began to accelerate, even leading to a later acceleration in the overall MAU decline, having a more profound impact. This phenomenon indicates that even large-scale leading projects find it difficult to withstand the shock of user loss, highlighting deep-seated issues within the ecosystem that need to be addressed.
2. Structural changes behind project fluctuations.
Among the 820 projects monitored by OGenLab, 249 projects showed an increase in October, while 491 projects experienced a decline.
From the analysis of the bar chart, it is clear that the leading and historically established projects—represented by those that have already issued tokens such as Hamster, Dogs, Catizen—have seen the most significant declines.
These once-glorious star projects are now facing significant declines in user activity and engagement, reflecting a weakening of their growth momentum and fading user freshness.
[Source: https://x.com/OGenLab/status/1854060874304221435]
At the same time, some emerging projects provided positive growth, injecting new vitality into the market.
However, in terms of quantity and growth rate, the increase from these new projects is far from compensating for the decline caused by old projects. Among projects with a user base of less than 1 million, the number of declining projects still exceeds the number of rising projects.
This indicates that even in the small and medium-sized project domain, the overall trend is still downward, with the market lacking sufficient new forces to reverse this situation.
This phenomenon highlights the structural problems existing in the TON ecosystem: the appeal of old projects is gradually diminishing, and the growth momentum of new projects is insufficient, indicating that the entire ecosystem urgently needs new stimulation and direction.
How to provide more innovative and valuable applications while maintaining user stickiness has become an urgent issue for foundations and developers.
3. The migration of project scales and the downgrade of user demand.
To better understand changes in the ecosystem, OGenLab categorized the 820 monitored projects into various tiers based on monthly active users (MAU): over 50 million, 10 million-50 million, 5 million-10 million, 200,000-500,000, 50,000-200,000, 10,000-50,000, 20,000-100,000, and below 20,000.
By observing the changes in these projects in October, several noteworthy trends were discovered.
3.1. High-tier projects flowing to lower tiers.
>50 million MAU tier:
Number of projects: decreased from 2 in week 1 to 1 in week 4.
Flow: From week 3 to week 4, 1 project in the >50 million tier downgraded to the 10 million-50 million tier.
10 million - 50 million MAU tier:
Number of projects: decreased from 18 in week 1 to 15 in week 4.
Flow:
From week 1 to week 2, 1 project downgraded to the 5 million-10 million tier;
From week 2 to week 3, 2 projects downgraded to the 5 million-10 million tier;
From week 3 to week 4, another 6 projects downgraded to the 5 million-10 million tier.
5 million - 10 million MAU tier:
Number of projects: increased from 22 in week 1 to 31 in week 4.
Flow: On one hand, projects in high tiers are downgraded;
On the other hand, some projects further downgraded to the 200,000-500,000 tier.
It is evident that top projects are sliding down to lower tiers.
The number of projects with over 50 million users decreased from 2 to 1, indicating that the user activity of these flagship projects is declining sharply.
This trend has led to a decrease in the number of high-tier projects and an increase in mid-tier projects, reflecting that the ecosystem is undergoing a top-down contraction.
3.2. The decline of medium-sized projects is significant.
200,000 - 500,000 MAU tier:
Number of projects: increased from 35 in week 1 to 41 in week 4, but the growth rate is relatively slow.
Flow:
From week 3 to week 4, 10 projects downgraded from the 5 million-10 million tier to this tier; at the same time, 10 projects further downgraded from the 200,000-500,000 tier to the 50,000-200,000 tier.
50,000 - 200,000 MAU tier:
Number of projects: increased from 78 in week 1 to 99 in week 4.
Flow: Many projects downgraded from higher tiers, and some projects also downgraded to the lower 10,000-50,000 tier.
Medium-sized projects also could not escape the impact of declining activity.
The increase in the number of projects is mainly due to the downgrade of high-tier projects, rather than their own growth. This indicates that medium-sized projects are under increasing pressure to maintain user scale, with significant user loss.
3.3. The number of small projects has increased significantly.
100,000 - 500,000 MAU tier:
Number of projects: increased from 142 in week 1 to 181 in week 4.
Flow: Several projects have downgraded from higher tiers, especially from the 50,000-200,000 and 200,000-500,000 tiers. Additionally, some projects further downgraded to the 20,000-100,000 and <20,000 tiers.
20,000 - 100,000 MAU and <20,000 MAU tiers:
Number of projects: The number of projects in these two tiers has significantly increased. Among them, the <20,000 tier projects increased from 84 to 161.
Flow: Many projects downgraded from higher tiers, especially from the 10,000-50,000 tier. At the same time, there are also projects with declining activity, leading to a surge in the number of lowest-tier projects.
The increase in the number of small projects is not a sign of ecological prosperity, but rather a result of the overall decline of projects.
Projects at all tiers generally face the problem of declining user activity, and the influx of new projects is insufficient to compensate for user loss, indicating that the ecosystem lacks fresh blood.
[Source: https://x.com/OGenLab/status/1854060874304221435]
The above data clearly reveals the overall downward trend in the scale of TON ecosystem projects.
From top projects to small projects, none can escape the impact of declining activity.
This trend reflects the current ecosystem's lack of user stickiness and innovation driving force, urgently needing new strategies and narratives to stimulate growth and regain user trust.
4. The dilemmas and highlights of OpenLeague projects.
In discussing the development of various projects within the TON ecosystem, we have focused on OpenLeague projects. Despite having a certain level of recognition and user base in the market, it still cannot escape the trend of user decline, and in some aspects, the decline is even more severe.
Moreover, there is a mix of quality within the projects, with inconsistencies.
However, it is worth noting that one or two highlight projects still stand out, bringing hope to the entire ecosystem.
[Source: https://x.com/OGenLab/status/1854060874304221435]
The trend of user decline is more evident.
Through data analysis of OpenLeague projects, we found.
Overall user activity is declining: Compared to other projects, OpenLeague's user drop is more significant, and the number of active users continues to decrease. This may be related to the project's lack of sustained innovation and user engagement mechanisms.
Increased competitive pressure: OpenLeague faces more intense competition among similar competitive and gaming projects. The emergence of new projects has diverted users, leading to a reduction in its market share.
Project quality varies significantly.
A mixed ecosystem: The quality of sub-projects and activities within OpenLeague varies, and some projects lack clear positioning and high-quality content, making it difficult to attract and retain users.
User experience needs improvement: Some projects have shortcomings in design and functionality, leading to poor user experiences during use, further accelerating user loss.
Highlights worth paying attention to.
Despite facing numerous challenges, there are still some outstanding projects within OpenLeague, such as 'AKEDO Game' and 'RentTycoon', which have shown deeper green on certain days and continue to rise.
5. A whale falls, and everything lives or returns to zero.
To gain a deeper understanding of project user dynamics, we studied the changes in projects between the week 30 days ago (September 24 - September 30) and the most recent week (October 25 - October 31).
On one hand, this helps us observe the trends over the entire month;
On the other hand, since the official data is monthly active users (MAU), if the sum of the slopes of trends for these two periods is closer to 0, then the project is suspected of fake volume and lacks new users.
[Source: https://x.com/OGenLab/status/1854060874304221435]
Analysis method: For the two 7-day time periods, we defined the following metrics:
M 1 (User change from September 24 to September 30): During this period, M 1 equals the valid user count (non-empty and greater than 10) on the last day of the period minus the valid user count (non-empty and greater than 10) on the first day of the period.
M 2 (User change from October 25 to October 31): Similarly, M 2 equals the valid user count (non-empty and greater than 10) on the last day of this period minus the valid user count (non-empty and greater than 10) on the first day of the period.
In addition, we plotted a two-dimensional coordinate system, using M 1 as the x-axis and M 2 as the y-axis, and added a reference line x=-y to assist in analysis.
Coordinate quadrant explanation: By plotting the data points of projects in the coordinate system, we can assess the user trends of projects based on their quadrant and position.
First quadrant (M 1>0, M 2>0)
Meaning: Projects showed user growth in both the week 30 days ago and the most recent week. Interpretation: These projects may have sustained growth momentum, with user activity steadily increasing, warranting attention and follow-up.
Second quadrant (M 1<0, M 2>0)
Meaning: Projects saw a decline in user numbers in the week 30 days ago but grew in the most recent week. Interpretation: If data points are on the right side of x=-y, it indicates that the project has begun to turn around and is likely to become a potential project. If located on the left side of x=-y, it indicates that the growth is not enough to compensate for the previous decline, and the project may still be in an unstable state.
Third quadrant (M 1<0, M 2<0)
Meaning: Projects experienced user decline in both time periods. Interpretation: These projects show a clear downward trend, with user activity continuously decreasing, posing a high termination risk.
Fourth quadrant (M 1>0, M 2<0)
Meaning: Projects saw growth in the week 30 days ago but declined in the most recent week.
Interpretation: If the data point is located to the left of x=-y, it indicates that the project's decline exceeds previous growth, and users may enter a spiral decline, which needs to be taken seriously.
Suspicion of fake volume projects
Data points close to the origin and near x=-y indicate that the sum of M 1 and M 2 is close to zero, suggesting that the user changes in the project lack real growth, possibly indicating fake volume behavior, with actual new users being few.
Potential projects
Projects located in the second quadrant and to the right of x=-y, although previously experiencing a decline, have shown significant user growth recently, indicating a rebound trend and worthy of further attention.
Risk projects
Projects located in the third quadrant, with a continuous decline in users, need to assess their viability and improve strategies.
Projects to be wary of
Projects located in the fourth quadrant and to the left of x=-y have recently experienced a significant drop and may be caught in a dilemma of continuous user loss. From the above content, we can summarize:
User growth projects (first quadrant and second quadrant) deserve special attention, showcasing sustained growth or rebound potential.
User decline projects (third quadrant and fourth quadrant) require in-depth analysis of the reasons for the decline and timely adjustments in strategy to regain users.
Suspected fake volume projects need to enhance data monitoring to ensure data authenticity and maintain the healthy development of the ecosystem.
6. Summary
Currently, Telegram mini-program applications are facing unprecedented dilemmas, mainly concentrated in two areas: commercialization and content.
In terms of commercialization:
The current commercialization model mainly relies on selling volume and listing tokens, focusing on traffic monetization.
However, the current challenge is: sellers of listed tokens and exchanges have already purchased a wave of traffic, and the new traffic is not attractive enough to them.
At the same time, a large number of tokens were generated in the game, but there is a lack of specific application scenarios and consumption mechanisms. After players acquire tokens, their only choice is to sell them, leading to rapid declines after the project lists the tokens.
Content aspect:
Currently, the vast majority of leading games are based on clicker mechanics and a series of viral tasks, lacking playability.
Over time, users may form ingrained stereotypes about Telegram games, attracting players who are primarily 'EarntoSell' types.
To reverse this situation, it is necessary to create truly playable games, rebuild from the ground up, and restore users' trust. The next brilliant gaming star will rise in the sky of Telegram, which will be a truly touching masterpiece. We sincerely hope to see new content ideas and new commercialization models that will revitalize these games and lead users to a real gaming world.
OGenLab is an enthusiastic game studio, standing at the forefront of emerging tracks, pursuing infinite possibilities for the future.
This analysis was also first published on Twitter: https://x.com/OGenLab/status/1854060874304221435
In the future, OGenLab will continue to monitor the data pulse of Telegram and will soon conduct in-depth analysis of the project’s on-chain data on TON.
We have witnessed the fall of giant projects and the rise of emerging forces, yet this is not enough to illuminate the whole world. As the saying goes, 'After the mountains and rivers are heavy, doubts about the road are gone, the willows darken and flowers bloom anew,' we hope to see the prosperous scene of the Telegram application soon.
Reference materials:
1. Telegram Apps Center: https://tapps.center/
2. TON App: https://ton.app/
3. The Open League: https://ton.org/open-league
