Introduction

Recently, data from Telegram bots and Miniapps have shown a clear downward trend.

Once, Telegram Miniapps, fueled by the explosive growth of Clicker games, became a focal point in the blockchain space.

However, behind the prosperity lies a crisis.

The TON Foundation’s over-reliance on Clicker games for its support strategy, while bringing a surge in users and data in the short term, has also sown the seeds of ecosystem imbalance.

As users’ novelty fades, the homogeneity and lack of depth in Clicker games have gradually become apparent, and the entire ecosystem has started to feel the backlash.

Now that the tide has receded, it’s time for a deep reflection on the TON Foundation’s strategic mistakes and to find a new narrative that can drive the next phase of growth for the TON ecosystem.

We gather bot data from Telegram Apps Center, TON App, and The Open League (see appendix).

1. The Unstoppable Trend of MAU Decline

Over the past month, OGenLab has been continuously monitoring 820 Telegram projects.

From October 1 to October 31, the accumulated Monthly Active Users (MAU) reached 879,922,503, despite the data being not deduplicated.

However, behind this massive number, a concerning and rapid decline is hidden.

In just one month, the total MAU dropped by 295,971,112 (not deduplicated), a decrease of 33%.

This significant drop reveals the rapid decline in user engagement, indicating that the entire ecosystem is facing unprecedented challenges.

[Source: https://x.com/OGenLab/status/1854060874304221435]

Through the analysis of daily data, OGenLab found that this decline is showing an amplified trend. Large projects with over 5 million users initially saw a relatively slow decline in MAU, maintaining a degree of stability. However, over time, the rate of decline in these projects began to accelerate, and in the later stages, they led the drop, having a more profound impact on the overall MAU decline. This phenomenon suggests that even large-scale projects with significant user bases are struggling to withstand user attrition, highlighting deep-rooted issues within the ecosystem that need urgent attention.

2. Structural Changes Behind Project Ups and Downs

Among the 820 projects monitored by OGenLab, 249 saw growth and 491 experienced a decline in October.
From the bar chart analysis, it is clear that established projects with a long history, such as Hamster, Dogs, and Catizen, which have already issued tokens, experienced the most significant decline.
These once-popular projects are now facing a sharp drop in user activity and engagement, reflecting a weakening growth momentum and the fading novelty for users.

Source:[https://x.com/OGenLab/status/1854060874304221435]

Meanwhile, some emerging projects have shown positive growth, injecting new energy into the market. However, in terms of quantity and growth rate, the increase in these new projects is far from enough to offset the impact of the decline in older projects. Among projects with less than 1 million users, the number of declining projects still outpaces the number of growing ones. This indicates that even in the small and medium-sized project sector, the overall trend remains downward, with the market lacking sufficient new forces to reverse the situation. This phenomenon highlights structural issues within the TON ecosystem: the diminishing appeal of old projects, the insufficient growth momentum of new projects, and the urgent need for new stimuli and direction. The challenge now is how to maintain user stickiness while offering more innovative and valuable applications, which has become an urgent issue for the foundation and developers.

3. Migration of Project Scales and the Downgrading of User Demands

To gain a deeper understanding of the ecosystem’s changes, OGenLab divided the 820 monitored projects into several tiers based on monthly active users (MAU): above 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 throughout October, several notable trends were identified.

3.1. Migration from High-Tier to Lower-Tier Projects

• 50 million MAU Tier:

Number of projects: Decreased from 2 in Week 1 to 1 in Week 4. Migration: 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. Migration:

* 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, 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. Migration: On the one hand, projects from higher tiers are downgrading into this category; on the other hand, some of these projects themselves are further downgraded to the 2 million–5 million tier. Top-tier projects are sliding to lower tiers. The number of projects with over 50 million users has decreased from 2 to 1, showing a significant decline in the user activity of flagship projects. This trend has led to a reduction in high-tier projects and an increase in mid-tier projects, reflecting a top-down contraction in the ecosystem.

3.2. Significant Decline in Mid-Tier Projects

• 2 million–5 million MAU Tier:

Number of projects: Increased from 35 in Week 1 to 41 in Week 4, but the growth rate was slow. Migration: 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 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. Migration: A large number of projects have downgraded from higher tiers, while some of them have further downgraded to the 100,000–500,000 tier. Mid-sized projects have also been affected by the decline in user activity. The increase in project numbers is mainly due to downgrades from higher tiers, rather than organic growth. This shows that mid-tier projects are under increasing pressure to maintain their user base, with significant user loss.

3.3. Sharp Increase in Small-Tier Projects

100,000–500,000 MAU Tier:

* Number of projects: Increased from 142 in Week 1 to 181 in Week 4.
* Migration: Many projects have downgraded from higher tiers, especially from the 500,000–2 million and 2 million–5 million tiers. Additionally, some projects have 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 has grown from 84 to 161 projects.
* Migration: Many projects have downgraded from higher tiers, particularly from the 100,000–500,000 tier. At the same time, some projects have seen a decline in activity, leading to a sharp increase in projects in the lowest tier.

The increase in small-tier projects is not a sign of ecosystem prosperity, but rather a result of the overall decline in projects. Projects across all tiers are facing a decrease in user activity, and the influx of new projects is insufficient to make up for the user loss. The ecosystem is lacking fresh blood.

[Source: https://x.com/OGenLab/status/1854060874304221435]

The data above clearly reveals the comprehensive decline in project scales within the TON ecosystem. From top-tier projects to smaller projects, none have been able to avoid the impact of declining user activity. This trend reflects the current ecosystem’s lack of user stickiness and the absence of an innovation-driven force, highlighting the urgent need for new strategies and narratives to stimulate growth and regain user trust.

4. The Predicaments and Highlights of the OpenLeague Project

When examining the development of various projects within the TON ecosystem, we turned our attention to the OpenLeague project. Despite having a certain level of market recognition and a user base, it still cannot avoid the downward trend in user numbers, with some aspects even showing a more severe decline. Moreover, the project suffers from internal disparities, with varying quality among its offerings. However, it is worth noting that one or two standout projects have emerged, bringing hope to the entire ecosystem.

[Source: https://x.com/OGenLab/status/1854060874304221435]

The trend of user decline is more pronounced. Through data analysis of the OpenLeague project, we discovered the following:

• The overall decline in user activity: Compared to other projects, OpenLeague experienced a more significant drop in users, with active user numbers continuing to decrease. This may be related to the project’s lack of sustained innovation and user engagement mechanisms.
• Increased competition pressure: OpenLeague faces fiercer competition within the same category of competitive and gaming projects. The emergence of new projects has diverted users, leading to a reduction in its market share.

Uneven project quality:

• The ecosystem within OpenLeague is mixed, with sub-projects and activities of varying quality. Some 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 a poor user experience, and further accelerating user loss.

Highlights worth noting: Despite facing numerous challenges, there are still some standout projects within OpenLeague, such as “AKEDO Game” and “RentTycoon,” which showed significant growth on certain days and have continued to rise.

5. “One Whale Falls, Everything Lives or Eventually Goes to Zero”

To gain a deeper understanding of user dynamics within projects, we studied the changes in projects between two periods: the week from September 24th to September 30th (30 days ago) and the week from October 25th to October 31st (the most recent week). On one hand, this helps us observe the changes over a full month; on the other hand, since the official data provided is for Monthly Active Users (MAU), the closer the combined slope of the trends between these two periods is to zero, the higher the suspicion that the project is inflating its numbers and lacks real new user growth.

[Source: https://x.com/OGenLab/status/1854060874304221435]

For the two 7-day periods, we defined the following metrics:

M1 (user change from September 24th-30th): M1 is calculated as the number of valid users (non-empty and greater than 10) on the last day of the period minus the number of valid users on the first day of the period.

M2 (user change from October 25th-31st): Similarly, M2 is calculated as the number of valid users (non-empty and greater than 10) on the last day of the period minus the number of valid users on the first day of the period.

Additionally, we plotted a two-dimensional coordinate system with M1 on the x-axis and M2 on the y-axis, adding a reference line at x = -y for analytical purposes.

Quadrant Explanation

By plotting the data points of projects on the coordinate system, we can assess their user trends based on their quadrant and position.

• First Quadrant (M1 > 0, M2 > 0)

Meaning: The project has shown user growth in both the previous and the most recent week.

Interpretation: These projects likely have sustained growth potential, with steadily improving user activity, and should be closely monitored.

• Second Quadrant (M1 < 0, M2 > 0)

Meaning: The project had a decline in users during the previous week but saw growth in the most recent week.

Interpretation: If the data point is on the right of the x = -y line, it indicates that the project is turning around and may become a promising one. If it’s on the left, the growth isn’t enough to offset the previous decline, and the project may still be unstable.

• Third Quadrant (M1 < 0, M2 < 0)

Meaning: The project experienced user decline in both time periods.

Interpretation: These projects show a clear downward trend, with sustained decreases in user activity, and are at high risk of termination.

• Fourth Quadrant (M1 > 0, M2 < 0)

Meaning: The project grew in the previous week but declined in the most recent week.

Interpretation: If the data point is on the left of the x = -y line, it means the decline now exceeds the previous growth, and the project may be in a downward spiral. This requires attention.

Suspicion of Inflated Numbers
Projects with data points close to the origin and near the x = -y line, where the combined M1 and M2 slopes approach zero, suggest that the user change lacks real growth and that the project might be inflating its numbers, with few actual new users.

Potential Projects
Projects in the second quadrant, especially those to the right of the x = -y line, show significant recent user growth, even though they experienced some decline earlier. These are worth monitoring for potential rebound.

Risk Projects
Projects in the third quadrant, with sustained user decline, need to assess their viability and improve their strategies.

Projects to Be Cautious About
Projects in the fourth quadrant, especially those to the left of the x = -y line, show a significant recent decline and may be trapped in a cycle of ongoing user loss.

Based on the above content, we can summarize as follows:

• User growth projects (Quadrants I and II) deserve close attention, as these projects demonstrate the potential for sustained growth or a rebound.
• User decline projects (Quadrants III and IV) require in-depth analysis of the reasons behind the decline, and strategies should be adjusted promptly to recover users.
• Suspected fake volume projects should have their data closely monitored to ensure authenticity and maintain the healthy development of the ecosystem.

6. Summary

Currently, Telegram mini-programs are facing an unprecedented crisis, primarily in two areas: commercialization and content.

Commercialization: The current commercialization model mainly revolves around selling traffic and listing tokens, with the core focus being traffic monetization. However, the challenge now lies in the fact that token listing sellers and exchanges have already bought a wave of traffic, and the newly added traffic holds less appeal for them. Meanwhile, a large number of tokens have been generated in games, but they lack specific use cases and consumption mechanisms. Once players acquire tokens, their only option is to sell them, causing projects to quickly decline after listing tokens.

Content: At present, most of the leading games are focused on clickers and a series of viral tasks, with the games themselves lacking playability. Over time, users may form fixed stereotypes about Telegram games, attracting players who are mainly of the “earn to sell” type. To reverse this situation, it’s essential to create truly playable games, tear down the old framework, and rebuild user trust. If the next bright star in the Telegram ecosystem emerges, it will be a truly touching and outstanding game. We sincerely hope to see new creative content and innovative commercialization models that will breathe new life into these games and lead users into the real world of gaming.

OGenLab is a passionate game studio, standing at the forefront of emerging trends, pursuing the limitless possibilities of the future.

This analysis was first published on Twitter: https://x.com/OGenLab/status/1854060874304221435

Moving forward, OGenLab will continue to monitor the data pulse of Telegram and, in the near future, will conduct an in-depth analysis of projects on the TON blockchain. We have witnessed the downfall of giant projects and the rise of emerging forces, but this is not enough to light up the whole world. As the saying goes, “The mountains are steep and the waters are long, yet there is a glimmer of light at the end of the road,” we hope to see the prosperous future of Telegram applications soon.

References:

1. Telegram Apps Center: https://tapps.center/
2. TON App: https://ton.app/
3. The Open League: https://ton.org/open-league

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