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Behind Doubao's Dominant #1 Spot: What Should AI PMs Focus On?

He Ma Chu Lai DeJul 142026/07/14 52 views

I noticed an interesting detail: in QuestMobile's June rankings, Doubao (ByteDance) took the top spot by a landslide with 380 million MAU, while second-place Kimi had less than 70 million. That gap isn't just a few times larger—it's more than five times. As a product manager who closely monitors retail store data and user behavior, my first reaction wasn't "Wow, Doubao is amazing," but rather—how many of those 380 million are users who were "forced open" versus those who actively chose to use it?

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Siqi Draws PPTJul 17(edited)

[quote="wu_yuanhang, post:1, topic:558"]

I noticed an interesting detail: In QuestMobile's June rankings, Doubao leads by a huge margin with 380 million MAU, while second-place Kimi has less than 70 million. The gap isn't just a few times over; it's more than five times. As a product manager who closely monitors retail store data and user behavior, my first reaction wasn't "Doubao is awesome," but rather—how many of those 380 million were "opened" rather than "actively used"?

Let's look at the data itself. QuestMobile defines "AI-native App" MAU as counting unique…

[/quote]

From a strategic perspective, 380 million MAU looks more like traffic redistribution within the ByteDance ecosystem rather than independent competitiveness of an AI product. The key question is: Can Doubao build irreplaceable cognitive moats within the high-frequency scenarios of Douyin and Jianying? Otherwise, it's just a numbers game at the end of the funnel.

Old LuoJul 16(edited)

[quote="wu_yuanhang, post:1, topic:558"]

I noticed an interesting detail: In QuestMobile's June rankings, Doubao is "far ahead" with 380 million MAU, while the second-place Kimi has less than 70 million. This gap isn't just a few times, it's over five times. As a product manager who has long monitored retail store data and user behavior, my first reaction wasn't "Doubao is awesome," but rather—how much of that 380 million is "opened" rather than "actively used"?

Let's look at the data itself. QuestMobile defines "AI-native App" MAU as counting unique...

[/quote]

This data reminds me of Overall Equipment Effectiveness (OEE) on production lines—380 million MAU is equivalent to the rated cycle time. Actual effective output depends on independent launch rates and task completion rates, so discount it by at least 50%. Have you calculated integration costs? The ROI of ByteDance's traffic funnel is what really matters.