The Decline of Telegram Mini Programs: The Deep-seated Reasons Behind the Comprehensive Drop in Data Metrics

Recently, the user data of Telegram bots and Miniapps has shown a significant downward trend. Once, thanks to the explosive growth of Clicker games, Telegram Miniapps 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. Although this has led to a surge in users and data in the short term, it has also sown the seeds of ecological imbalance. As users' novelty wears off, the issues of homogenization and lack of depth in Clicker games gradually become apparent, and the entire ecosystem begins to suffer backlash.

Now, as the tide goes out, it is necessary to deeply reflect on the strategic missteps of the TON Foundation and seek new directions that can lead the next phase of development for the TON ecosystem.

1. The trend of a significant decline in MAU is hard to stop.

Continuous monitoring of 820 Telegram projects over the past month shows that from October 1 to October 31, despite the inability to deduplicate data, the accumulated monthly active users (MAU) reached 879,922,503. However, behind this huge number lies a concerning sharp decline.

In one month, the total MAU decreased by 295,971,112( without deduplication), which corresponds to a drop of 33%. This significant decline reveals a rapid decrease in user activity, reflecting that the entire ecosystem is facing unprecedented challenges.

Through the analysis of daily data, it has been found that this decline shows a trend of amplification. In particular, large projects with more than 5 million users initially experienced a relatively slow decline in MAU, seemingly maintaining a certain level of stability. However, over time, the decline in these projects began to accelerate, even leading to a faster drop in the later stages, which had a more profound impact on the overall decline in MAU.

This phenomenon indicates that even large-scale leading projects struggle to withstand the impact of user loss, highlighting the urgent need to address deep-rooted issues within the ecosystem.

2. Structural Changes Behind Project Price Fluctuations

Among the 820 projects monitored, 249 projects showed an increase in October, while 491 projects showed a decrease.

It is clear from the analysis that the leading and historically established projects, represented by already issued tokens like Hamster, Dogs, and Catizen, have experienced the most significant declines. These once-glorious star projects are now facing a substantial drop in user activity and engagement, reflecting a weakening of their growth momentum and a fading sense of novelty among users.

At the same time, some emerging projects have 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 impact caused by the decline of older projects.

In projects with a user scale of less than 1 million, the number of projects that have declined still exceeds the number of projects that have increased. This indicates that even in the realm of small and medium-sized projects, the overall trend remains downward, and the market lacks sufficient new forces to reverse this situation.

This phenomenon highlights the structural problems present in the TON ecosystem: the appeal of older projects is gradually weakening, the growth momentum of new projects is insufficient, and the entire ecosystem urgently needs new stimuli 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 Scale and Degradation of User Demand

In order to gain a deeper understanding of the changes in the ecosystem, the 820 monitored projects are categorized into several tiers based on the monthly active users (MAU): over 50 million, 10 million to 50 million, 5 million to 10 million, 2 million to 5 million, 500,000 to 2 million, 100,000 to 500,000, 20,000 to 100,000, and below 20,000.

By observing the changes of these projects in October, some noteworthy trends were identified:

3.1 High-value projects flowing to lower tiers

• 50 million MAU tier: The number of projects decreased from 2 in the first week to 1 in the fourth week. From the third week to the fourth week, one project in the >50 million category was downgraded to the 10 million - 50 million category.

• 10 million - 50 million MAU tiers: The number of projects decreased from 18 in week 1 to 15 in week 4. From week 1 to week 2, 1 project was downgraded to the 5 million - 10 million tier; from week 2 to week 3, 2 projects were downgraded; and from week 3 to week 4, another 6 projects were downgraded.

• 5 million - 10 million MAU tier: The number of projects increased from 22 in the first week to 31 in the fourth week. On one hand, there is a downgrade of high-tier projects entering; on the other hand, some projects have further downgraded to the 2 million to 5 million tier.

It is clear 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 a significant decline in user activity for these flagship projects. 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.

The grade of the medium-sized project has declined significantly.

• 2 million - 5 million MAU tiers: The number of projects increased from 35 in week 1 to 41 in week 4, but the growth rate was relatively slow. From week 3 to week 4, 10 projects downgraded from the 5-10 million range to this range; at the same time, 10 projects further downgraded from this range to the 500,000-2 million range.

• 500,000-2,000,000 MAU tier: The number of projects increased from 78 in the first week to 99 in the fourth week. A large number of projects were downgraded from higher tiers, while some of their own projects were also downgraded to a lower range of 100,000 to 500,000.

Medium-sized projects have also not been spared from the impact of declining activity. The increase in the number of projects is mainly due to the downgrading of high-tier projects, rather than their own growth. This indicates that medium-sized projects are under increasing pressure to maintain their user base, with a noticeable phenomenon of user loss.

The number of small projects has increased significantly.

• 100,000-500,000 MAU tier: The number of projects increased from 142 in the first week to 181 in the fourth week. Many projects were downgraded from higher tiers, especially from the 500,000-2 million and 2 million-5 million tiers. In addition, some projects were further downgraded to the 20,000-100,000 and <20,000 tiers.

• 20,000-100,000 MAU and <20,000 MAU tiers: The number of projects at these two tiers has increased significantly. Among them, the projects in the <20,000 tier have risen from 84 to 161. Many projects have downgraded from higher tiers, especially from the 100,000-500,000 tier. At the same time, the activity of some projects has also declined, leading to a surge in the number of projects at the lowest tier.

The increase in the number of small projects is not a sign of ecological prosperity, but rather a result of the overall decline in projects. Projects at all levels are generally facing the issue of decreased user activity, and the influx of new projects is insufficient to make up for user loss, resulting in a lack of fresh blood in the ecosystem.

These data clearly reveal a comprehensive decline trend in the scale of TON ecosystem projects. From top projects to small-scale projects, none can escape the impact of decreased activity. This trend reflects the current lack of user engagement in the ecosystem and a lack of innovative driving force, highlighting the urgent need for new strategies and narratives to stimulate growth and regain user trust.

4. The Dilemmas and Highlights of the OpenLeague Project

When discussing the development status of various projects in the TON ecosystem, we have noticed the OpenLeague project. Despite having a certain level of recognition and user base in the market, it still cannot avoid the trend of user decline, and in some aspects, the decline is even more severe. Furthermore, there is a mix of quality within the project, leading to inconsistent standards.

However, it is worth noting that one or two standout projects have emerged, bringing hope to the entire ecosystem.

The downtrend for users is more apparent.

Through data analysis of the OpenLeague project, we found that:

• Overall user activity has declined: Compared to other projects, OpenLeague has seen a larger drop in users, with the number of active users continuously decreasing. 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.

• Ecological mix of fish and dragons: The quality of sub-projects and activities within OpenLeague varies, with some projects lacking 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 a poor experience for users during use, further accelerating user attrition.

Highlights worth paying attention to

Despite facing numerous challenges, there are still some outstanding projects in OpenLeague, such as "AKEDO Game" and "RentTycoon", which showed deeper green on certain days and continue to rise.

5. Project Change Trend Analysis

In order to gain a deeper understanding of the project's user dynamics, we studied the project changes over a week from 30 days ago (September 24 - September 30) and the most recent week (October 25 - October 31).

We have defined the following indicators for two 7-day periods:

M1 (User change from September 24 to September 30): During this period, M1 equals the number of valid users on the last day of the period (non-empty and greater than 10) minus the number of valid users 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 number of valid users (non-empty and greater than 10) on the last day of this period minus the number of valid users (non-empty and greater than 10) on the first day of the period.

By plotting the data points of the project on a coordinate system, we can assess the user trends of the project based on the quadrant and position in which they are located:

• First Quadrant (M1>0, M2>0): The project shows user growth in both periods, demonstrating sustained growth momentum.
• Second Quadrant (M1<0, M2>0): The project has recently begun to rebound and may become a potential project.
• Third quadrant (M1<0, M2<0): The project continues to decline, with a high risk of termination.
• Fourth Quadrant (M1 > 0, M2 < 0): The project has recently started to decline, and we need to be alert to the acceleration of user loss.

In addition, we also focused on the following types of special projects:

• Suspected projects of volume manipulation: Projects with data points close to the origin and located near x=-y may have volume manipulation behavior.
• Potential projects: Projects located in the second quadrant and to the right of x=-y show a rebound trend.
• Risk projects: Projects located in the third quadrant need to assess their viability and improvement strategies.
• Projects to be wary of: those located in the fourth quadrant and to the left of x=-y may fall into the dilemma of continuous user loss.

6. Conclusion

Currently, Telegram mini-program applications are facing unprecedented difficulties, primarily focused on commercialization and content.

In terms of commercialization, the existing model mainly relies on sales volume and token listings, with the core focus on monetizing traffic. However, sellers of token listings and exchanges have already purchased a wave of traffic, and the appeal for new traffic is insufficient. At the same time,