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Operator: Good day, ladies and gentlemen. Thank you for standing by. Welcome to Alibaba Group's September Quarter 2025 Results Conference Call. [Operator Instructions] I would now like to turn the call over to Lydia Lu, Head of Investor Relations of Alibaba Group. Please go ahead.
Lydia Lu: Thank you. Good day, everyone. Welcome to our September quarter 2025 earnings conference call. With me today from Alibaba are Joe Tsai, Chairman; Eddie Wu, Chief Executive Officer; Toby Xu, Chief Financial Officer; Jiang Fan, Chief Executive Officer of Alibaba E-commerce Business Group. I would like to remind you that this call is also being webcast on our corporate website. A replay of the call will be available on our website later today. Just a few forward-looking statements before we begin today. Today's discussions may contain forward-looking statements, particularly statements about our business and financial results that are subject to risks and uncertainties, which could cause actual results to differ materially from those contained in the forward-looking statements. Please refer to the safe harbor statements that appear in our press release and investor presentation provided today. Please note that certain financial measures that we use on this call are expressed on a non-GAAP basis. Our GAAP results and reconciliations of GAAP to non-GAAP measures can be found in our earnings press release. With that, I'm going to turn the call over to Eddie.
Yongming Wu: [Interpreted] Welcome to Alibaba Group's quarterly earnings call. Over the past quarter, Alibaba delivered steady and healthy growth. Our total revenue increased 15% year-over-year, excluding Sun Art and Intime. Our continued investment in core businesses is yielding results with China e-commerce CMR growing 10% and Cloud Intelligence revenue rising 34%.
Yongming Wu: Let me walk you through the latest developments across our AI + Cloud and consumption businesses. Sustained strong demand for AI and rising usage of public cloud drove Alibaba Cloud's 34% revenue growth this quarter, while revenue from external customers accelerated by 29%. AI-related products continued to post triple-digit year-over-year growth for the ninth consecutive quarter. In the cloud computing market, 2 major trends are becoming increasingly apparent. First is AI applications scale, more developers and enterprise customers are choosing vendors with full stock AI technology portfolios. Second, Customers are deepening and broadening their use of AI, which is significantly increasing demand for compute, storage and other traditional cloud services. Together, these forces are accelerating revenue growth driven by external customer demand. This quarter, we continued to strengthen our full stack AI capabilities, spanning high-performance AI infrastructure, foundation models and AI development frameworks. Our flagship model, Qwen3-Max ranks among the global leaders in benchmarks for real-world coding tasks, agent tool use capabilities and other specialized valuations. Our full stack AI capabilities are now a defining competitive advantage. Alibaba Cloud is gaining market share across multiple segments. In the hybrid cloud market, Alibaba Cloud has become a key player, growing more than 20% year-over-year, outpacing the industry and steadily expanding market share. Our financial cloud business is also growing faster than the market with market share continuing to rise. In China's AI cloud market, we are also the clear leader with a market share larger than the combined total of the second to fourth largest providers. Recently, businesses such as the NBA, Marriott, China UnionPay and Bosch have partnered with Alibaba Cloud on AI initiatives.
Yongming Wu: Last week, we officially launched the Qwen app, which aims to be the most advanced personal AI assistant system powered by our latest models. In the first week of its public beta, the Qwen app has already surpassed 10 million in new downloads. The launch of the Qwen app marks Alibaba's commitment to both AI for enterprise and AI for consumer. In enterprise-focused AI, our goal is to build a world-leading full-stack AI provider serving businesses across all industries. For consumers, we aim to build native AI-first applications by leveraging our best-in-class models and Alibaba's extensive ecosystem. On the one hand, Qwen3-Max's intelligence and world-class tool use capabilities combined with Alibaba's rich consumer and lifestyle use cases contributed to exceptional user retention in the Qwen apps beta release. We believe this is the right moment to scale our consumer AI efforts. On the other hand, the synergy between AI and the broader Alibaba ecosystem is a powerful multiplier. Alibaba is the only company in China with both a leading large model and extensive lifestyle and commerce use cases. Qwen will gradually integrate e-commerce, map navigation, local services and more becoming an AI-powered entry point for everyday life. With AI innovation and ecosystem collaboration reinforcing each other, we're confident in our ability to deliver substantial user value.
Yongming Wu: In consumption, we continue to deepen collaboration across businesses and the benefits of our large integrated platform are becoming increasingly evident. This quarter, China E-commerce CMR grew 10%. Our Quick Commerce business saw a significant improvement in unit economics with greater fulfillment efficiencies, stronger user retention, higher average order value and expanding scale. The growth of quick commerce business contributed to rapid growth in Taobao app's monthly active consumers and supported CMR expansion. Brands on Tmall are also accelerating their adoption of on-demand retail. As of October 31, approximately 3,500 brands on Tmall have onboarded their offline stores to our quick commerce business. Going forward, we will further enhance synergy between quick commerce and the broader Alibaba ecosystem, continue improving unit economics and meet consumers' fast-growing demand for immediate access to diverse products and services. On October 1, Amap's daily active users reached a historical high of 360 million. In September, we launched the Amap Street Stars feature which has significantly boosted user engagement. In October, Amap Street Stars averaged more than 70 million daily active users with average daily user reviews more than triple the amount of the same period last year, indicating strong future growth potential. Amap Street Stars has built a trust-based rating system for local offline services using user consented metrics such as the users credit rating. We believe that enhancing consumer trust is essential to strengthening consumer confidence, enabling merchants to focus on operations while giving consumers greater peace of mind, supporting the healthy and sustainable growth of the local offline services sector. Looking ahead, we'll continue investing decisively in our 2 core strategic pillars: AI plus cloud consumption. We will advance both enterprise and consumer-focused AI, unlock deeper synergies across Alibaba's businesses and use these entrants to drive Alibaba's long-term growth and carry the company to the next level. Thank you. I will now hand over to Toby.
Toby Xu: Thank you, Eddie. We are continuing our focus and discipline on AI plus cloud and consumption and we see strong momentum from these strategies with gains in technology, market share, consumers and user engagements. Now let's look at the financial results. On a consolidated basis, total revenue was RMB 247.8 billion. Excluding revenue from Sun Art and Intime, revenue on a like-for-like basis would have grown by 15% year-over-year. Total adjusted EBITA decreased 78%, primarily due to our strategic investments in quick commerce business to grow its user base and transaction volume, partly offset by double-digit revenue growth in China E-commerce Group and Cloud Intelligence Group and improved operating efficiencies across various businesses including AIDC and Hujing DME. Our GAAP net income was RMB 20.6 billion, a decrease of 53%, primarily attributable to the decrease in income from operations. Operating cash flow was RMB 10.1 billion, a decrease of RMB 21.3 billion compared to the same quarter last year. The year-over-year decrease was mainly attributed to our increased strategic investments in quick commerce business. Free cash flow was an outflow of RMB 21.8 billion which reflected our significant investments in quick commerce business and AI plus cloud infrastructure, we are reinvesting our free cash flow to create a winning quick commerce business and to be a leader in AI. Our strong balance sheet backed by USD 41 billion in net cash gives us confidence for this reinvestment strategy.
Toby Xu: Revenue from Alibaba China E-commerce Group was RMB 132.6 billion, an increase of 16%. Customer management revenue increased 10% primarily due to the improvement of take rate, which benefited from the increasing penetration of Quanzhantui and the addition of software service fees. Revenue from our quick commerce business increased 60%. During the quarter, we executed our plan to grow the scale of our quick commerce business, improve user experience and narrow UE loss. The adjusted EBITA from Alibaba China E-commerce Group was RMB 10.5 billion. Excluding loss from our quick commerce business, our Alibaba China E-commerce Group EBITA would have grown at mid-single-digit year-over-year for the quarter. Going forward, this adjusted EBITA may fluctuate quarter-over-quarter due to intense competition and a significant investment in user experience.
Toby Xu: Revenue from AIDC grew 10%. AliExpress, in particular, has developed AliExpress direct model that leverages local inventories in over 30 countries. AliExpress has also enhanced the range of our product offerings by launching the Brand+ program, providing go-to-market solutions to Chinese brands going overseas. A combination of logistics optimization and investment efficiency enhancement resulted in AIDC's adjusted EBITA profit of RMB 162 million this quarter. Looking ahead, while we continue to enhance operating efficiency, AIDC adjusted EBITA may fluctuate quarter-over-quarter due to tactical investments in select markets.
Toby Xu: Our cloud business delivered another quarter of accelerated growth as both growth of cloud segment revenue and revenue from external customers accelerated to 34% and 29%, respectively. This momentum was primarily driven by public cloud revenue growth, including the increasing adoption of AI-related products. AI-related product revenue continue to grow at triple-digit pace. AI-related product revenue this quarter accounted for over 20% of revenue from external customers with its contribution continue to increase. We are seeing accelerated adoption of our AI products across a broader range of enterprise customers with a growing focus on value-added applications, including coding assistance. The adjusted EBITA margin remained relatively stable at 9%. We will continue to invest in customer growth and technology innovation to increase adoption of AI infrastructure cloud and strengthen our market leadership.
Toby Xu: All other segment revenue was a decrease by 25% and mainly due to the disposal of Sun Art and Intime businesses. All other adjusted EBITA was a loss of RMB 3.4 billion, primarily due to the increased investment in technology businesses, partly offset by the improving operating results of other businesses. Hujing DME has achieved profitability for 3 consecutive quarters. The all other segment comprises a set of innovative initiatives, including several strategic AI-driven technology infrastructure and businesses, including our foundation model and AI apps. We are excited to continue investing in these initiatives for future growth. Thank you. That's the end of our prepared remarks, we can open up for Q&A.
Lydia Lu: Thank you, Toby. Hi, everyone. You're welcome to ask questions in Chinese or English. A third-party translator will provide consecutive interpretation for the Q&A session. The translation is for convenience purpose only. In the case of any discrepancy, our management's statement in the original language will prevail. . If you are unable to hear the Chinese translation, bilingual transcripts of this call will be available on our website within 1 week after the end of the meeting. [Foreign Language]. Operator, please go ahead with Q&A session. Thank you.
Operator: [Operator Instructions] Your first question today comes from Gary Yu at Morgan Stanley.
Gary Yu: Congratulation on a strong set of results. My question is related to cloud business. How should we look at the growth outlook going forward? Should we continue to expand growth to accelerate? And on the demand side, given we don't have a big AI company like in the U.S., how should we look at the key drivers driving the external revenue growth going forward?
Yongming Wu: [Interpreted] Thank you for those questions. Let me start with the first one. Certainly, we see that customer demand for AI is -- remains very strong. In fact, we're not even able to keep pace with the growth in customer demand as in orders in terms of the pace at which we can deploy new servers. So we certainly do see the demand for AI is accelerating. In terms of where that demand is coming from, it's really coming from all aspects of enterprise operations as AI adoption continues to not only accelerate but deepen with applications across product development throughout manufacturing processes and also in terms of supporting the enterprises and customers use their products. So in all of those places AI adoption continues to deepen. And of course, all of this activity around model training and inference requires the use of compute as well. So essentially, we're talking about a huge potential and continually growing demand among real customers engaged in real world use cases. Therefore, our conviction in future AI demand growth is strong.
Operator: Your next question comes from Kenneth Fong at UBS.
Kenneth Fong: Congrats on the strong performance in our quick commerce initiative. Can management share some key progress for quick commerce and synergy to our core e-commerce so far. Given the synergy, what's the outlook for December quarter CMR and EBITA for our core e-commerce?
Unknown Executive: [Interpreted] Thank you for your question. Over the past few months, we've focused on optimizing our unit economics in quick commerce, while maintaining our market share. And we believe we've made significant progress on this front. The order mix has improved and the economies of scale from growing order volume has driven clear reductions in logistics costs. Since November, the per order UE loss for quick commerce has been cut by 50% compared to July, August. So on this basis, quick commerce has maintained stable order share with GMV share holding steady and trending upward. And we're also seeing a meaningful uplift in related physical e-commerce categories. Let me expand a bit further on those points. First, in terms of order mix optimization, over the past 2 months, the share of higher average order value, higher AOV orders has increased. According to the latest data, non-beverage orders now account for over 75% of total orders. Most recently, AOV for quick commerce has grown by double digits compared to August which has contributed to an increase in quick commerce's overall GMV share. On the second point about logistics as the order volume scales, quick commerce is realizing very clear economies of scale in fulfillment logistics. Delivery speed is now faster than the same period last year, while average logistics cost per order has declined significantly. In fact, the average cost per order is now lower than it was before we started making large-scale investments in quick commerce. So these 2 factors together have enabled us to achieve our near-term target, namely cutting by half the per order loss versus July, August. And importantly, during this phase of narrowing UE losses, both user retention and purchase frequency have outperformed expectations. Beyond food delivery, we're also seeing rapid growth in retail categories via quick commerce, clearly driving growth across related categories and businesses, especially groceries, health care products and the supermarket segment within physical e-commerce. For example, Freshippo and Tmall Supermarket quick commerce orders are up 30% from August. Over recent months, we've also actively onboarded merchants and brands onto Taobao Instant Commerce, and we will further accelerate integration and synergy between key retail categories and quick commerce model going forward. So in summary, we firmly believe that the quick commerce model holds immense potential for synergy with the broader Alibaba ecosystem. In Phase 1, we successfully achieved rapid scale expansion. In Phase 2, UE optimization is progressing in line with our expectations, laying a solid foundation for the long-term sustainability of the quick commerce business and reinforcing our confidence in sustained long-term investment in quick commerce. In the next phase, we will continue to refine the user experience through operational upgrading with a focus on serving high-value users and to focus on expanding retail categories. Quick commerce is a core strategic pillar in the Taobao Tmall Group's platform upgrade. Our goal is to generate RMB 1 trillion in GMV for the platform within 3 years, thereby driving market share gains across the related categories.
Toby Xu: [Interpreted] Thanks. This is Toby. Let me take the second part of your question about CMR and EBITA. So as Jiang Fan has just shared with you, quick commerce is having a very significant effect in terms of enhancing user engagement as well as driving transactions in relevant categories. So that, of course, has a positive impact on CMR. So the main thing that we need to do in this next phase is to better integrate and achieve synergies across conventional e-commerce and quick commerce so as to more fully realize that impact. However, we are in an investment phase right now. So this is relevant to EBITA. I think likely, the September quarter will be the quarter during which the scale of those investments are the highest. And as efficiency improves and UE improves and as the scale of this business stabilizes we can expect to see, I think, by next quarter a significant sizing down in the scale of those investments. Of course, having said that, we will dynamically adjust the pace and size of our investments in line with market competition. When it comes to CMR and the e-commerce business, there will be an impact from the base effect in respect of the payment processing fee as well as the rollout of QZT. We started charging the payment processing fee in September of last year. And so starting from next quarter, we did expect to see a slowdown in growth due to that base effect but as we've consistently emphasized, our primary and foremost objective is to secure market share for the medium and long term. And during this process, we will continue to decisively invest in consumers and merchants, and we will resolutely move ahead with business model upgrading of our e-commerce platform. And during that process, you can therefore expect that there will be short-term fluctuations in CMR and in EBITA.
Operator: Your next question comes from Alex Yao at JPMorgan.
Alex Yao: [Interpreted] Thank you very much for the opportunity. So as Jiang Fan just said, we've now completed the first phase of these investments, we're now in the second phase where we are enhancing efficiency. So my question is, as the efficiency is optimized and we obtain cost savings what are we going to do with those cost savings? How will the benefits of those cost savings be allocated or distributed across the value chain among the different key stakeholders? Say, assume, for example, that we're going to continue to maintain the same level of intensity with respect to subsidies to consumers and there's this ongoing incremental improvement in the financial performance of the business then what will that mean in terms of subsidies for merchants? The cost savings will need to be allocated or distributed somehow across the key stakeholders, the consumer merchant and platform. And then so if we don't decrease those subsidies to consumers and we continue to follow the same path that we're on now and rely on optimization of user mix as well as try to increase in order share and driving higher basket sizes, what does that mean for UE? And how much scope is there going forward for UE growth?
Fan Jiang: [Interpreted] Yes. This is Jiang Fan. Let me take this question. And it's actually related to, in part, some of the things that I was sharing with you a bit earlier. So what we've been doing in this period of time is enhancing user experience and at the same time, increasing the average order value. So that means that the revenues attributable to each order will increase, because our revenues are proportionate to average order value. I also spoke earlier about how we've optimized logistics -- fulfillment logistics efficiency, and we'll continue to drive improvement there with scale. So I think going forward, there is still considerable scope there on the one hand in respect of consumers because over the past few months, it's really been primarily new consumers in this business. And what we're doing is converting those users into users with a higher level of stickiness across the platform as a whole. And through that process, we'll continue to increase average order size, average order value and to modify the ways in which we provide subsidies. Also, if you look at traffic on the Taobao app over the past few months, including on the quick commerce channel, which has rapidly increased to the point where it now has over 100 million daily users on the channel. I think it speaks to the fact that there's considerable potential for monetization -- further monetization. And I think that, that's an opportunity also to improve UE in the future. Now having said that, again, the market is a highly competitive market. So we will be looking at those opportunities, but adjusting our approach dynamically in line with market dynamics.
Operator: Your next question comes from Ronald Keung at Goldman Sachs.
Ronald Keung: [Interpreted] So I'd like to ask about CapEx over the next 3 years. And I'm wondering what your thinking is as you sit here today regarding the [RMB 380 billion] figure, I think you previously mentioned, in particular, because over the past 4 quarters, I believe, [RMB 120 billion] has already been spent. So how should we be thinking about CapEx going forward and the incremental revenue being driven by that CapEx and how to evaluate the correlation between CapEx and the expected incremental revenue?
Unknown Executive: [Interpreted] Thank you for your question. So the [RMB 380 billion] CapEx figure that we had previously mentioned was a planned figure for a 3-year period. But based on what we're seeing now, and as I just mentioned, the pace at which we can add new servers is insufficient to keep up with the growth in customer orders. So looking at the CapEx situation from where we're at today and of course, there are also supply chain issues to consider as well the pace in which we can build up IDCs and launch new servers is also part of that consideration. But essentially, we're working as fast as we can to be able to satisfy all of that customer demand. In that context, if we're not able to satisfy all of our customer demand especially well with the current pace of investment, then we wouldn't rule out further scaling up that CapEx. But again, that is somewhat dependent on supply chain and availability. But in overall terms, certainly, we will be investing in AI infrastructure aggressively in order to meet the demand of customers. So in big picture terms, I would say that the [RMB 380 billion] figure we had mentioned previously, might be on the small side, certainly in terms of the customer demand that we're currently seeing. The second part of the question had to do with the incremental revenue being driven by these capital expenditures. And if there's some kind of ratio that we can calculate between X amount of CapEx investment and X amount of incremental revenue. And I don't think it's really possible to make that kind of estimate at least for the time being because overall, the AI sector is still in the early phases of its development. And if you look at the different ways that our AI infrastructure is currently being used, that's in flux and spans several different areas, for example, we have servers that are directly rented to customers for training. We have servers that are directly rented to customers for inference. And we're also, of course, using servers ourselves of Bailian for inference as well as for internal applications within the Alibaba Group, like Amap, like Taobao, like Qwen and Quark and transforming these applications into member services or membership-based products for our users. So overall, our AI products and AI infrastructure being used in all these different ways, different kinds of applications, resulting in different revenues and different gross margin levels. So I think in terms of that kind of ratio, you were asking about whatever it is. It certainly wouldn't be stable at this point. I think in the long term, though, what we care about more is that our infrastructure is serving high-quality tokens and providing good cost effectiveness with those tokens.
Operator: Your next question comes from Ellie Jiang at Macquarie.
Ellie Jiang: [Interpreted] This is more of a follow-up question. The company is a full-stack AI service provider and obviously is currently in an important investment cycle. And we can see that the investments you're making cover a number of different segments in the value chain. So considering the instability in the supply chains that are ongoing at present, I'm wondering how you consider the allocation of our resources because you have the model-as-a-service, the MaaS layer. We also continue to build up underlying capabilities, fundamental capabilities. And on the user-facing side, we have apps, including Tongyi or Qwen and Amap products like that, that were iterating rapidly and scaling up to users. So I'm just wondering in the present macro environment, how should we think about -- how should we evaluate the return on invested capital, ROIC, in respect of AI and including both training and inferencing?
Yongming Wu: [Interpreted] Thank you. Let me take that question. Indeed, as a full stack AI service provider, we are currently in a very important investment cycle for AI and investing in our products as well as in our infrastructure. So there are several different places where we're investing and we do have some internal thinking about how we prioritize them, and I can share, I think, some of those considerations with you. First of all, I would say the most critical of those priorities, the first thing that we need to ensure is that we are able to continually train our own foundation models. Because in the AI space overall, the ability of our AI infrastructure to be able to acquire more customers or to be able to acquire more high-value use cases relies on our ability to continually iterate and upgrade our foundation models. We need to be doing that in order to be able to unlock new demand and to acquire new customers by unlocking new risk cases. After that, after unlocking new higher-value use cases, then the next thing is to look at the amount of token consumption as well as token quality as well as the willingness of customers to pay for those tokens and that willingness is going to continue to strengthen gradually. So I would say that, that is one of the highest priorities when it comes to allocating those investments. Another priority is around inference, I'm thinking primarily of inference on -- as a service on Bailian. That is also a relatively high priority area for us because we've created the Bailian platform in order to be able to serve customers all around the world. We want to ensure that those AI resources are available 24 hours a day and are being utilized 24/7 with high efficiency. So the key there is to ensure that one AI server can run at full capacity 24 hours around the clock and thereby to generate more tokens. So Bailian is a very critical resource pool for us, and it's a relatively high priority. Separately, of course, we have internal use cases for AI inferencing. And indeed, we also have external customers who are leveraging our inferencing services to their demand. So that's also part of the picture. But when it comes to these external customers, we also had some criteria for prioritizing different external customers. If an external customer is utilizing all of our services across cloud, all of Alibaba Cloud services, spanning storage, spanning big data and all of these other things, then, of course, that customer would be accorded a higher level of priority. If you have a customer that's merely renting a GPU to meet some very simple inferencing needs then the demands of those customers would accordingly be given a slightly lower level of priority. Moving on to the second question, which I thought was a really good one. I think there are 2 pieces to this issue. The first is the supply side. Second is -- first is the demand side. Second is the supply side. So if we look at the foundation models and this could be video generation models. They could be omni-modal models going forward, but the capabilities continue to increase and be enhanced. And we're not yet seeing any issues in terms of scaling law. Nobody's hit the wall yet, so to speak, in the industry. We continue to make a lot of progress on the very important breakthroughs in terms of model capabilities. As the models become more powerful than the AI models will be able to do more things in the world of being able to serve larger variety of different use cases. And that will result in these models serving a lot of tasks, as the capabilities increase, they become stronger. As these tasks become more deeply embedded across all industries, all aspects of business operations. So with those 2 drivers, we see in the next 3-year period, highly definitive trend of demand for AI. And with all of this rapid growth in demand, we also need to be thinking about the supply side. I'm sure that you, as analysts have also been looking at the supply side. Starting from the second half of this year, I think we've seen worldwide. If you look at fabs, if you look at DRAM vendors, storage companies, CPU manufacturers across all of those different links in the value chain that go to making AI servers, there is a situation of undersupply. Supply is unable to keep up with demand for all of these components globally. And I think that you can expect that to continue throughout this scaling up an investment cycle, driven by real demand for AI, we know that the supply side is going to be a relatively large bottleneck. So I think that it could be at least a period of 2 or 3 years for those different suppliers, those different venues to be able to ramp up their production capacity. So in this period of 2 to 3 years, we can expect to continue to see a rapid increase in demand and that to be driving the supply side. So I think in the next 3 years to come, AI resources will continue to be undersupplied with demand outstripping supply. And what we can see internally in the industry, and if we look at the hyperscalers in the U.S., all of the latest GPUs that are running are running at full capacity and not just them, the last generation GPUs, even GPUs from 3 to 5 years ago, so also several generations back, those GPUs are to this day still running at full capacity. So looking ahead to the next, say, 3 years, we don't really see much of an issue in terms of a so-called AI bubble.
Unknown Executive: Well, let's take the last question, please, operator.
Operator: Your last question comes from Jialong Shi from Nomura.
Jialong Shi: [Interpreted] So in the last earnings call, management shared that Alibaba intends to grow its market share in the consumption market, in China. And we've seen that over the past few months, your investments in quick commerce have indeed resulted in an increase in market share. So I'd like to know apart from quick commerce, apart from Instant Commerce, what are the other subsectors in the consumption market that you see as good opportunities for investment where you will consider scaling up your investments?
Fan Jiang: [Interpreted] Thank you. This is Jiang Fan. Let me take this question. Alibaba has been investing strategically in consumption market over many years, and we've entered a huge number of different categories and sub verticals. So apart from quick commerce, which we've been investing in heavily, we've talked a lot about it. We also, of course, have Freshippo, we have offline, the offline O2O model as well as Fliggy as well as Amap and of course, local services. So that's our landscape or matrix of businesses that we've been investing in. And I think what we need to be doing now really is working to integrate, connect those businesses and to drive more synergies across those existing businesses. And in that way, we can achieve a further increase in our market share in that larger consumption market.
Lydia Lu: Thank you. Thank you, everyone, for joining us today. We look forward to speaking with you again on our December quarter earnings call.