China internet app data diverged in June: AI and ByteDance ecosystem remained strong, while cross-border e-commerce and long video came under pressure

Overview

This report is Nomura’s monthly tracking of China internet and new media app performance in June 2026, covering metrics such as MAU, DAU, total usage time, average daily usage time per DAU, and platform camp share. Overall, China’s mobile internet market remains resilient in aggregate, but different segments are clearly diverging: native AI apps and office AI agents continue to grow rapidly, and ByteDance is widening its lead in user time share; cross-border e-commerce is seeing slower overseas growth due to European policy barriers; traditional app scenarios such as long video, live streaming, search, and online travel remain weak.

Core views

Core views include: first, China’s monthly active smartphone user base remains stable, with June MAS up 1.2% YoY to 1.28 billion and total monthly usage time up 8.6% YoY; second, competition among AI chatbots is shifting from consumer user acquisition to enterprise AI agents, with competition in consumer chatbots expected to cool, marketing spending to decline, and user engagement growth to slow; third, ByteDance apps’ share of usage time among Top-50 apps rose to 40.1%, significantly above Tencent’s 29.7%; fourth, user declines for Temu and Shein in Europe indicate that policy resistance in cross-border e-commerce is beginning to show up in user data; fifth, in local services, Douyin’s standalone local services app “Dou Sheng Sheng” is rapidly catching up to Dianping in DAU, though its usage time still remains significantly below Dianping’s.

Analysis framework

The report is mainly based on third-party data from QuestMobile, Sensor Tower, and Analysys, comparing YoY and MoM changes in DAU, MAU, MTS, and DTSD across various apps, and breaking down trends by app category and internet group camp. The analysis focuses not on financial forecasts, but on the signaling value of user scale, engagement, traffic share, and policy environment changes for platform competition dynamics.

Methodology notes

• user behavior trackingMAU/DAU/MTS/DTSD app data framework

  Measures app scale and stickiness through monthly active users, daily active users, total usage time, and average daily usage time per DAU.

  The report analyzes user scale and user engagement separately, using DAU/MAU to observe the user base, and MTS and DTSD to assess changes in time share and stickiness.

• competitive landscape analysisinternet camp usage time share comparison

  Compares the time share of top apps across camps such as ByteDance, Tencent, Baidu, and Alibaba.

  Top-50 apps account for about 93% of total mobile usage time in China, so camp usage time share can serve as a high-frequency indicator of platform ecosystem competitiveness.

• policy impact analysiscross-border e-commerce regulatory barrier tracking

  Policies such as Europe removing tax exemptions for low-value cross-border goods and imposing additional tariffs affect user growth.

  The report links the decline in Temu and Shein users in the European market to tighter regulation of imported goods, highlighting the need to monitor how platforms respond to higher policy barriers going forward.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• ByteDance ecosystem

  benefits from growth in short video, short dramas, AI applications, and office applications

  Strengths

  Doubao leads in DAU, Red Fruit Free Short Drama is growing rapidly, and ByteDance’s Top-50 time share has risen to 40.1%.

  Weaknesses

  Part of the growth depends on traffic distribution and a low base, so the sustainability of rapid growth still needs to be observed.

  Comparison

  Its time share has already exceeded Tencent’s, and it has stronger growth momentum in AI and short dramas.

  Risks

  Cooling competition in AI chatbots may lead to slower user engagement growth on the consumer side.

• Tencent ecosystem

  WeChat maintains the top time share, and WorkBuddy leads in office AI agents

  Strengths

  WeChat’s usage time share is 19.3%, WorkBuddy’s monthly visits rose to 21 million, and WeCom DAU grew 10% YoY.

  Weaknesses

  Tencent Video, QQ, and some traditional entertainment apps performed weakly.

  Comparison

  Tencent’s Top-50 app time share is 29.7%, below ByteDance’s 40.1%.

  Risks

  Declining time spent on long video and aging social apps may drag on ecosystem growth.

• Alibaba ecosystem

  Qwen, QoderWork, DingTalk, Taobao, Amap, and Fliggy are all included in the tracking

  Strengths

  Qwen posted high YoY DAU growth, QoderWork monthly visits rose from 2.15 million in March to 7.88 million in June, and Amap’s YoY DAU growth offset part of the decline in usage time.

  Weaknesses

  Qwen has a high proportion of light users, Taobao DAU declined 2% YoY, and Fliggy MTS fell 11% YoY.

  Comparison

  Office AI agent visits are below Tencent WorkBuddy and ByteDance TRAE IDE.

  Risks

  Insufficient user stickiness and loss of core e-commerce users may affect monetization efficiency.

• PDD/Temu

  domestic Pinduoduo is stable, while overseas Temu is under pressure

  Strengths

  Pinduoduo’s domestic app DAU grew 3% YoY, and DTSD grew 3% YoY.

  Weaknesses

  Temu global MAU declined 2% YoY in June, and seller DAU fell 11% YoY.

  Comparison

  Temu’s overseas growth is weaker than before and, like Shein, is under pressure in the European market.

  Risks

  Policies such as Europe removing tax exemptions for low-value cross-border goods and imposing additional tariffs may continue to suppress user growth.

• Meituan/Dianping

  the core local services platform is being challenged by Douyin’s local services app

  Strengths

  Dianping DAU is still about 32 million, and DTSD is 8.3 minutes, significantly higher than Dou Sheng Sheng’s 4.5 minutes.

  Weaknesses

  Dianping’s June DAU fell 2% MoM, and total usage time for the Meituan app declined 8% YoY.

  Comparison

  Dou Sheng Sheng DAU has reached 65% of Dianping’s, up rapidly from 15% in March.

  Risks

  Douyin’s traffic support may continue to erode the entry advantage of local services.

• China Internet & New Media sector

  overall mobile internet traffic is stable but structurally diverging

  Strengths

  Total usage time grew 8.6% YoY, and segments such as AI, short dramas, and digital freight still have growth.

  Weaknesses

  Many traditional segments such as long video, live streaming, search, and online travel saw declines in DAU or MTS.

  Comparison

  High growth is concentrated in a small number of ecosystems and new app formats, while traditional apps have less growth elasticity.

  Risks

  Peaking user growth, regulatory barriers, declining marketing spending, and weakening user stickiness may weigh on sector valuations.

Key data

• China MAS1.28 billionUp 1.2% YoY in June 2026.
• Total monthly mobile usage time in Chinaup 8.6% YoYSlower than the 10.1% YoY growth rate in May 2026.
• Doubao DAU167 millionUp 3.3x YoY and 6% MoM in June 2026, ranking first among native AI chatbots.
• DeepSeek DAU32.4 millionUp 1% YoY and 6% MoM in June 2026.
• Qwen DAU29.3 millionUp 84x YoY and 5% MoM in June 2026, but light users accounted for 55%.
• Tencent WorkBuddy monthly visits21 millionUp from 8.85 million in March 2026, maintaining the No.1 position among office AI agent platforms.
• ByteDance Top-50 app time share40.1%Was 33.3% in June 2025 and exceeded Tencent’s 29.7% in June 2026.
• WeChat usage time share19.3%Ranked first in mobile user usage time in China in June 2026.
• Douyin usage time share19.0%Second only to WeChat; Douyin Lite was 6.3%.
• Temu global MAUdown 2% YoYTurned from 2% YoY growth in May to decline in June 2026, mainly dragged by weaker performance in Latin America and Europe.
• Shein global MAUup 5% YoYJune 2026 growth slowed significantly from 14% YoY in May, with declines in Europe partly offset by growth in Brazil and India.
• Dou Sheng Sheng DAU21 millionUp 32% MoM in June 2026, about 65% of Dianping’s DAU, a significant increase from 15% in March.

Impact & implications

The core investment implication of the report is that platform traffic and user time are concentrating toward AI, short video/short dramas, and platforms with strong ecosystem synergies. Large internet companies such as ByteDance, Tencent, and Alibaba have advantages in the AI agent market thanks to super apps and office/business ecosystems. Meanwhile, cross-border e-commerce and traditional content/service apps face pressure from policy, user stickiness, and slowing growth, meaning that future valuation and earnings expectations will need to rely more on paid conversion, monetization efficiency, and cost control.

Risks

• Tighter regulation of cross-border e-commerce in Europe, including the removal of tax exemptions for low-value goods and additional tariffs, may continue to affect user growth for Temu and Shein.
• As AI chatbots shift from the consumer side to the business side, consumer user engagement and marketing spending may slow.
• Traditional apps such as long video, live streaming, search, and online travel are seeing declines in DAU or usage time, indicating growth pressure in mature segments.
• Some app growth is driven by a low base or light users, and there is still uncertainty around monetization quality and retention.
• Competition in local services is intensifying, and Douyin’s traffic support may alter the entry advantage of Dianping and Meituan.

What to watch

• Changes in MAU, order conversion, and seller activity for Temu and Shein under Europe’s new regulatory environment.
• Whether DAU and DTSD for AI apps such as Doubao, DeepSeek, and Qwen continue to grow in sync, especially whether Qwen’s share of light users can decline.
• Monthly visits and enterprise scenario penetration for office AI agents such as WorkBuddy, TRAE IDE, and QoderWork.
• Whether ByteDance’s Top-50 app time share continues to stay above Tencent’s and widen the gap.
• Whether the DAU gap and DTSD gap between Dou Sheng Sheng and Dianping continue to narrow.
• Whether traditional segments such as long video, online reading, live streaming, music, and online travel see a recovery in user stickiness.