Telegram mini-program applications are currently facing two dilemmas: commercialization and content.
Written by: Shisi Jun
Recently, the data for Telegram bots and Miniapps has shown a clear downward trend.
Once upon a time, driven by the explosive growth of Clicker games, Telegram Miniapp temporarily 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, which, while bringing a surge of users and data in the short term, has also sown the seeds of ecological imbalance.
As users' novelty fades, the homogenization and lack of depth in Clicker games gradually become apparent, causing the entire ecosystem to suffer backlash.
Now that the tide has receded, there is a need for deep reflection on the strategic missteps of the TON Foundation and to find a new narrative capable of leading the next stage of the TON ecosystem's development.
We counted BOT sources from Telegram Apps Center, TON App, The Open League (see appendix)
1. The trend of significant MAU decline is unstoppable.
Over the past month, OGenLab has continuously monitored 820 Telegram projects.
From October 1 to October 31, although the data cannot be deduplicated, the accumulated monthly active users (MAU) reached 879,922,503.
However, behind this huge number lies a worrisome sharp decline.
In one month, MAU decreased by a total of 295,971,112 (not deduplicated), equivalent to a 33% drop.
This significant drop reveals a rapid decrease in user activity, reflecting that the entire ecosystem is experiencing unprecedented challenges.
[Image source: https://x.com/OGenLab/status/1854060874304221435]
Through daily data analysis, OGenLab found that this decline shows an amplifying trend.
Especially those large projects with over 5 million users, the initial decline in MAU is relatively slow, seeming to maintain some stability.
However, over time, the rate of decline for these projects began to accelerate, even leading the decline in the later stages, having a more profound impact on the overall MAU decline.
This phenomenon indicates that even large-scale leading projects struggle to withstand the impact of user loss, revealing deep-seated issues within the ecosystem that urgently need to be addressed.
2. Structural changes behind project fluctuations
Among the 820 projects monitored by OGenLab, in October, a total of 249 projects showed an increase, while 491 projects experienced a decline.
The analysis of the bar chart clearly shows that the leading and historically established projects—represented by already issued tokens like Hamster, Dogs, Catizen—are experiencing the most significant declines.
These once-celebrated star projects now face significant declines in user activity and engagement, reflecting a weakening of their growth momentum and a fading of user novelty.
[Image source: https://x.com/OGenLab/status/1854060874304221435]
Meanwhile, some emerging projects have provided positive growth, injecting new vitality into the market.
However, in terms of quantity and growth rate, the increase of these new projects is far from enough to make up for the impact of the decline of old projects.
In projects with user scales below 1 million, the number of declining projects still exceeds the number of rising projects.
This indicates that even in the mid-to-small scale project sector, the overall trend remains downward, and the market lacks sufficient new forces to reverse this situation.
This phenomenon highlights the structural issues present in the TON ecosystem: the appeal of old projects is gradually diminishing, the growth momentum of new projects is insufficient, and 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. Migration of project scales and degradation of user demand
To gain a deeper understanding of changes in the ecosystem, OGenLab categorized the 820 monitored projects according to monthly active users (MAU) into several tiers: over 50 million, 10 million - 50 million, 5 million - 10 million, 2 million - 5 million, 500,000 - 2 million, 100,000 - 500,000, 20,000 - 100,000, and below 20,000.
By observing the changes in these projects in October, we discovered some trends worth noting.
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 direction: 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 direction:
From Week 1 to Week 2, 1 project downgraded to the 5-10 million tier;
From Week 2 to Week 3, 2 projects downgraded to the 5-10 million tier;
From Week 3 to Week 4, another 6 projects downgraded to the 5-10 million tier.
5 million - 10 million MAU tier:
Number of projects: Increased from 22 in Week 1 to 31 in Week 4.
Flow direction: On one hand, there is a downgrade from high-tier projects; on the other hand, some projects have further downgraded to the 2 million - 5 million tier.
It is evident that top projects are sliding down to lower tiers.
The number of projects with over 50 million users has decreased from 2 to 1, indicating that the user activity of these flagship projects is significantly declining.
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. Medium-tier projects show significant downgrades
2 million - 5 million MAU tier:
Number of projects: Increased from 35 in Week 1 to 41 in Week 4, but the growth rate is relatively slow.
Flow direction: From Week 3 to Week 4, 10 projects downgraded from the 5 million - 10 million tier to this tier; simultaneously, 10 projects further downgraded from the 2 million - 5 million tier to the 500,000 - 2 million tier.
500,000 - 2 million MAU tier:
Number of projects: Increased from 78 in Week 1 to 99 in Week 4.
Flow direction: A large number of projects have downgraded from higher tiers, while some projects have downgraded to the lower 100,000 - 500,000 tier.
Medium-sized projects have also not escaped the impact of declining activity.
The increase in the number of projects is primarily due to the downgrading of high-tier projects rather than their own growth. This indicates that medium-tier projects face increasing pressure to maintain user scales, with significant user loss.
3.3. Significant increase in the number of small projects
100,000 - 500,000 MAU tier:
Number of projects: Increased from 142 in Week 1 to 181 in Week 4.
Flow direction: Many projects have downgraded from higher tiers, especially from the 500,000 - 2 million and 2 million - 5 million tiers. Additionally, some projects further downgraded to the 20,000 - 100,000 and below 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 direction: Many projects have downgraded from higher tiers, especially from the 100,000 - 500,000 tier. At the same time, some projects have seen a decline in 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 ecosystem prosperity but a result of the overall project decline.
Projects across all tiers generally face the problem of declining user activity, and the influx of new projects is insufficient to compensate for user loss, leaving the ecosystem lacking fresh blood.
[Image 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-tier projects to smaller projects, none can escape the impact of declining activity.
This trend reflects the current ecosystem's insufficient user stickiness and lack of innovative driving force, urgently needing new strategies and narratives to stimulate growth and regain user trust.
4. The dilemmas and highlights of OpenLeague projects
In exploring the development status of various projects within the TON ecosystem, we focused on the OpenLeague project. Despite having a certain level of market recognition and user base, it still cannot avoid the trend of user decline, and in some aspects, it has declined even more severely.
Additionally, there is a mix of quality within the projects, leading to uneven quality.
However, it is worth noting that one or two standout projects have emerged, bringing hope to the entire ecosystem.
[Image source: https://x.com/OGenLab/status/1854060874304221435]
The trend of user decline is more pronounced
Through the data analysis of OpenLeague projects, we found.
Overall user activity is declining: Compared to other projects, OpenLeague's user decline is more significant, and the number of active users continues to decrease. This may relate 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 is uneven
The mixed ecosystem: The quality of sub-projects and activities within OpenLeague varies; some projects lack clear positioning and high-quality content, making it difficult to attract and retain users.
User experience needs improvement: Some projects have deficiencies in design and functionality, leading to poor user experiences and further accelerating user loss.
Highlights worth attention
Despite facing numerous challenges, there are still some outstanding projects in OpenLeague, such as 'AKEDO Game' and 'RentTycoon', which have shown deep green on certain days and continue to rise.
5. A whale falls and everything is born or ultimately returns to zero
To gain deeper insight into the user dynamics of the projects, we studied the changes in projects from 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 changing trends over the course of a month;
On the other hand, since the official data is the monthly active user count (MAU), the closer the sum of the slopes of the trends in these two periods is to 0, the higher the suspicion that the project is manipulating traffic and lacks new users.
[Image source: https://x.com/OGenLab/status/1854060874304221435]
Analysis method
We defined the following indicators for two 7-day periods:
M1 (User change from September 24 to September 30): During this period, M1 equals the effective user count on the last day of the period (non-empty and greater than 10) minus the effective user count on the first day of the period (non-empty and greater than 10).
M2 (User change from October 25 to October 31): Similarly, M2 equals the effective user count on the last day of this period (non-empty and greater than 10) minus the effective user count on the first day of this period (non-empty and greater than 10).
Additionally, we plotted a two-dimensional coordinate system, using M1 as the horizontal axis and M2 as the vertical axis, and added a reference line x=-y for analysis support.
Explanation of coordinate quadrants
By plotting the data points of projects on the coordinate system, we can evaluate the user trends of projects based on their quadrant and position.
Quadrant I (M1>0, M2>0)
Meaning: The project showed user growth in both the week 30 days ago and the most recent week.
Interpretation: These projects may possess sustained growth momentum, with steadily increasing user activity, making them worthy of attention and follow-up.
Quadrant II (M10, M2>0)
Meaning: The number of users in the project decreased in the week 30 days ago but increased in the most recent week.
Interpretation: If the data point is on the right side of x=-y, it indicates that the project has begun to reverse its decline and may become a potential project.
If located on the left side of x=-y, it indicates that the growth is insufficient to compensate for previous declines, and the project may still be in an unstable state.
Quadrant III (M10, M20)
Meaning: The project experienced user decline in both time periods.
Interpretation: These projects show a clear downward trend, with continuous declines in user activity, posing a high risk of termination.
Quadrant IV (M1>0, M20)
Meaning: The project saw user growth in the week 30 days ago but declined in the most recent week.
Interpretation: If the data point is on the left side of x=-y, it indicates that the project's decline has exceeded previous growth; users may be entering a downward spiral, warranting caution.
Suspected traffic manipulation projects
Data points close to the origin and near x=-y indicate that the sum of M1 and M2 is close to zero, suggesting that the project's user changes lack real growth, and there may be traffic manipulation behavior, with actual new users being few.
Potential projects
Projects located in Quadrant II and on the right side of x=-y, despite previous declines, have recently shown significant user growth, demonstrating a rebound trend that is worth further attention.
Risk projects
Projects in Quadrant III show a continuous decline in users and need to assess their viability and improvement strategies.
Need to be alert to the project
Projects located in Quadrant IV and on the left side of x=-y have recently seen a significant drop, potentially falling into a continuous loss of users.
Through the above content, we can briefly summarize:
User growth projects (Quadrant I and II) are worth focusing on, as these projects demonstrate potential for sustained growth or rebound.
User decline projects (Quadrant III and IV) require in-depth analysis of the reasons for the decline and timely adjustments to strategies to regain users.
Suspected traffic manipulation projects need to strengthen data monitoring to ensure data authenticity and maintain healthy ecosystem development.
6. Summary
Currently, Telegram mini-program applications are facing unprecedented difficulties, mainly focused on two aspects: commercialization and content.
Commercialization aspect:
The current commercialization model mainly revolves around selling volume and coin listing, focusing on traffic monetization.
However, the challenge at this stage is that sellers and exchanges of coin listings have already purchased a wave of traffic, making the new traffic less attractive to them.
Meanwhile, a large number of tokens are generated within the games, but there is a lack of specific application scenarios and consumption mechanisms.
Once players obtain tokens, their only option is to sell, leading to a rapid decline of the project post-coin listing.
Content aspect:
Currently, the vast majority of leading games are primarily Clicker-based and involve a series of viral tasks, lacking playability in the games themselves.
If this continues, users will form a fixed stereotype of Telegram games, and the players attracted will mostly be of the 'Earn to Sell' type.
To reverse this situation, it is necessary to create truly playable games, to reconstruct from scratch, and to rebuild user trust. The next brilliant gaming star in the Telegram sky will be a truly touching masterpiece.
We sincerely hope to see new content ideas and new commercialization models that can revitalize these games and lead users into a true gaming world.
OGenLab is a passionate 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
References:
1. Telegram Apps Center: https://tapps.center/
2. TON App: https://ton.app/
3. The Open League: https://ton.org/open-league
