Prepared remarks
Ladies and gentlemen, thank you for standing by for KE Holdings' second quarter 2026 earnings conference call. I am Siting Li, IR director of KE Holdings. Please note that today's call, including the management's prepared remarks and Q&A session, will be in Chinese. Simultaneous interpretation in English will be available on a separate line for the duration of the call. To access the call in Chinese, you will need to dial into the Chinese language line. At this time, all participants are in listen-only mode. Today's conference call is being recorded. The company's financial and operating results were published in the press release earlier today and are posted on the company's IR website. On today's call, we have Mr. Stanley Peng, our Co-founder, Chairman, and Chief Executive Officer, and Mr. Tao Xu, our Executive Director and CFO. Mr. Xu will provide an overview of our business update and financial performance. Mr. Peng will share more on the progress of our strategic transformation. Before we continue, I refer you to our safe harbor statement in our earnings press release, which applies to this call as we will make forward-looking statements. Please note that both the earnings press release and this conference call include discussions of unaudited GAAP financial information, as well as unaudited non-GAAP financial measures. Please refer to the company's press release, which contains a reconciliation of the unaudited non-GAAP measures to comparable GAAP measures. Lastly, unless otherwise stated, all figures mentioned during this call are in RMB. Certain statistical and other information relating to the industry in which the company is engaged to be mentioned in this call has been obtained from various publicly available official or unofficial sources. Neither the company nor any of its representatives has independently verified such data, which may involve a number of assumptions and limitations, and you are cautioned not to give undue weight to such information and estimates. For today's call, management will use Chinese as the main language. Please note that English translation is for convenience purposes only. In case of any discrepancy, management statements in their original language will prevail. Now, I will turn the call over to our CFO, Mr. Tao Xu.
Thank you, Siting. Hello, everyone. Welcome to our Q2 2026 earnings call. Let me begin with the key financial takeaways. Our total GTV returned to growth. Despite a modest year-over-year revenue decline, profits increased significantly, materially outperforming both GTV and revenue. In Q2, GTV increased 6.3% year-over-year, while revenue decreased 5.7% year-over-year. This revenue decline stemmed primarily from adjustments in our home renovation and furnishing business, and revenue recognition impacts from iterative product modeling in home renovation services. Non-GAAP net income grew 74.9% year-over-year to RMB 3.185 billion. Non-GAAP net margin reached 13%, up 6 percentage points year-over-year, a three-year high. Profit improvements were driven by a healthier cost structure, strict financial discipline, and higher operating efficiency. Contribution margins across all core business lines improved year-over-year and quarter-over-quarter, driving the group's gross margin up 6.7 percentage points year-over-year to 28.6%. Simultaneously, GAAP operating expenses fell 14.1% year-over-year. This combination of gross margin expansion and lower operating expenses fueled our profit growth. Next, I will review our segment financial performance. First, existing home transaction services. Q2 scale returned to growth and profitability improved significantly. GTV reached RMB 629.89 billion, up 8% year-over-year and 17.9% quarter-over-quarter. Revenue was RMB 7.02 billion, up 4.5% year-over-year and 14.5% quarter-over-quarter. GTV outpaced revenue growth year-over-year, primarily because non-Lianjia GTV, where platform service fees are recognized on a net basis, accounted for a larger share. This quarter, non-Lianjia platform service revenue increased 27.8% year-over-year and 29.8% quarter-over-quarter. With a stable network scale, we advanced and refined our operations to boost per store output, helping connected stores outperform the market in enhancing overall platform efficiency. Q2 contribution margin reached 46.1%, up 6.1 percentage points year-over-year, driven by lower fixed labor costs and a structural shift toward a higher-margin platform service revenue. It also rose 4.8 percentage points quarter-over-quarter, benefiting from operating leverage amid revenue recovery and further business mix improvements. Second, the new home business. Q2 scale remained stable year-over-year, while profitability continued to improve. GTV reached RMB 258.39 billion, up 1.2% year-over-year and 77.1% quarter-over-quarter. Revenue reached RMB 8.95 billion, up 3.8% year-over-year and 75.9% quarter-over-quarter. Despite a pressured market, we maintained a stable scale by collaborating on high-quality projects, improving customer conversion, and optimizing costs. Q2 contribution margin reached 28.8%, up 4.4 percentage points year-over-year, driven by cost structure optimization from refined operations. It also rose 3.1 percentage points quarter-over-quarter, benefiting from the same factors plus operating leverage from revenue growth. Third, home renovation and furnishing. Q2 revenue was RMB 3.19 billion, down 30.1% year-over-year, and up 36.4% quarter-over-quarter. The year-over-year decline reflects our proactive adjustments of inefficient customer acquisition channels and exits from cities with weak unit economics. New home market pressures also dampened renovation demand. The quarter-over-quarter revenue increase reflects a seasonal business recovery. Q2 contribution margin was 39.6%, up 7.5 percentage points year-over-year and 3.4 percentage points quarter-over-quarter, driven by lower material costs through centralized procurement and refined cost management. Fourth, home rental services. Q2 revenue was RMB 4.83 billion, down 14.8% year-over-year and 3.6% quarter-over-quarter. This stemmed from transitioning Carefree Rent to a lighter, lower-risk product model utilizing net-basis revenue recognition. While this reduces reported accounting revenue, managed rental units continued rapid growth. By the end of Q2, managed units exceeded 790,000, up approximately 34% year-over-year, with a net-base product comprising over 50%. Q2 contribution margin reached 15.3%, up 6.9 percentage points year-over-year. This reflects a favorable product mix shift and operating improvement from lower labor, installation, and post-lease costs. Quarter-over-quarter contribution margin rose 0.5 percentage points, driven by continued increase in net-based products. Fifth, emerging and other businesses. Q2 revenue reached RMB 550 million, up 26.4% year-over-year and 70% quarter-over-quarter. Next, turning to costs, expenses, and profits. Q2 store-related costs were RMB 560 million, down 25.9% year-over-year and broadly stable quarter-over-quarter. The year-over-year decline reflects Lianjia's rent cost optimization and network adjustments. Total Q2 GAAP operating expenses were RMB 3.989 billion, down 14.1% year-over-year, driven by improved organizational efficiency, optimized marketing spend, and continued financial discipline. Operating expenses rose 21.3% quarter-over-quarter due to higher selling expenses from the home renovation seasonal recovery and bad debt provisions in the new home business. Specifically, G&A expenses were RMB 2.04 billion, down 2.1% year-over-year. The 18.9% quarter-over-quarter increase resulted from a full bad debt provision of around RMB 280 million, following a prudent assessment of certain receivables and collateral value. Sales and marketing expenses were RMB 1.4 billion, down 26.1% year-over-year due to optimized sales personnel costs and refined marketing spend, but rose 29.6% quarter-over-quarter from seasonally higher home renovation selling expenses. R&D expenses were RMB 550 million, down 13.4% year-over-year due to lower labor and technical service costs, but up 11.4% quarter-over-quarter due to increased technical service fees. On the bottom line, Q2 GAAP operating profit reached RMB 3.026 billion, up 185.6% year-over-year. Non-GAAP operating profit was RMB 3.592 billion, up 123.6% year-over-year. GAAP operating profit rose 137.8% quarter-over-quarter with a 12.3% margin, up 8.3 percentage points year-over-year and 5.6 percentage points quarter-over-quarter. Non-GAAP operating profit grew 115.7% quarter-over-quarter with a 14.6% margin, up 8.5 percentage points year-over-year and 5.8 percentage points quarter-over-quarter. This year-on-year and quarter-over-quarter margin expansion was driven mainly by higher gross margins and lower operating expenses ratios. Q2 GAAP net income was RMB 2.624 billion, up 100.8% year-over-year and 109.1% quarter-over-quarter. Non-GAAP net income was RMB 3.185 billion, up 74.9% year-over-year and 97.6% quarter-over-quarter. Finally, turning to cash flow, balance sheet, and shareholder returns. Our Q2 net operating cash inflow was RMB 6.61 billion. Our new home accounts receivable turnover was around 39 days, down around 12 days year-over-year, reflecting effective risk management. Excluding customer deposits, our end of Q2 broad cash balance remained at around RMB 67.3 billion. This ample liquidity strengthened our risk resilience while supporting business development and shareholder returns. In Q2, we spent around $250 million on share repurchases, including our first buyback in the Hong Kong market. In the first half, we spent around $460 million on repurchases, up around 14% year-over-year, representing around 2.4% of our year-end 2025 outstanding shares. Since the launch of this share repurchase program in September 2022 through Q2 2026, we have repurchased around $2.99 billion in shares, representing around 14.8% of outstanding shares prior to the program start. In summary, Q2 profitability improvements reflect combined cost optimizations, operating enhancements, and a favorable business mix. Looking ahead, maintaining a solid balance sheet and ample liquidity will anchor our long-term growth. Across all core, new, and technical investments, we will enforce strict ROI discipline and take customer value, operating efficiency, and sustainable returns as our key metrics. Ultimately, we will balance business development with shareholder returns to consistently create long-term value. Next, I'll turn the call over to our Chairman and CEO, Mr. Stanley Peng. Please go ahead.
Thank you. Investors and analysts, good evening. Last quarter, we discussed our shift toward a consumer-centric transformation. This quarter, I will talk about how the changes translate into our operations. In Q2, I observed two trends. Our operation foundation stabilized, and our organization truly mobilized. This foundation enables the long-term change. I will address five key questions. The first one, what changes as transformation enters daily operations? Second, does being consumer-centric mean bypassing agents? Thirdly, as AI advances, will agents become obsolete? Fourthly, how is AI applied in our business, and what is the result? Fifthly, how will we know we are on the right track moving forward? For the first question, what changes as transformation enters daily operation? In this quarter, I spent a lot of time on the front line visiting stores, properties, construction sites, and discussing issues with clients, agents, and the store owners. The changes boil down to three areas. First, refined operation. We are shifting from the one-size-fits-all approach to district-specific and project-specific strategies. Rather than tracking a single citywide metric, we analyze specific districts or projects to tailor solutions for each community. For example, in a high-end community where clients view property across districts, our legacy geography-bound model failed, and we regrouped operational units based on actual clients' viewing paths, assigning project experts for professional presentations and client experts to address specific family needs. With 600 projects driving half the city's volume, standardizing these professional judgments into a clear division of labor allows us to replicate this model, and other cities have begun similar operations explorations. Second is shifting the metrics. Scale and market share still matter. But now we focus more on consistent agent transactions, rising agent efficiency, healthy store profitability, and stable service quality. Leasing illustrates this perfectly. In 2025, we had at most 700 agents for leasing at the peak. The average agent efficiency fell below two transactions. Instead of adding headcount, we divided the city into smaller blocks, rematching properties, clients, and agents based on familiarity and capabilities. From April to July, average agent efficiency jumped from three to 5.6 transactions and the zero-transaction ratio dropped from nearly 25% to under 10%. I think what matters is that effective organization matters more than mere headcount. Thirdly, mobilize the people. Managers have left meeting rooms for the front line. This quarter, managers personally sold stale listings, revisited dead leads, and accompanied agents to signing centers. My only requirement for managers is presence. You cannot learn to swim without getting in the water. In short, operationalizing transformation means refined operations, shifted metrics, and mobilized people. This stems from a single approach: solving real consumer and frontline problems first, then reorganizing our people, resources, and platform. We are moving towards change, and it is now being seen in operational units. The second question is, does being consumer-centric mean bypassing agents? This assumes that if the platform moves closer to the consumer, it must take from the agents. Historically, we only split a single transaction commission, which is a zero-sum game. This is what we did in the past. But to break this equation, we must create more high-value tasks, not just redivide the same money. Consumers are changing. 'Good' used to be a static property attribute. Today, I think good means a proper match. The variables determining 'good' expanded from one or two to include the property, the family situation, and also the service provider. The service provider is now a vital variable, not just a conduit. As decisions become harder, tasks must be segmented. There are three reasons. First, the required knowledge exceeds one's personal capacity. For example, we needed to know the property's client circumstances, mortgage, and the renovations and furnishing business. This exceeds one person's capacity. Second, building expertise requires mutually exclusive paths. You must either deeply root yourself in one project or follow a group of clients. You cannot do both simultaneously. That is the second reason. The third one is that the most valuable action has shifted from providing options to confidently eliminating them. We are not only offering more choices to consumers; instead, we need to help them to filter. However, filtering does not mean transaction. As long as income relies solely on closings, true professionalism won't develop. I think professionalism must be financially viable. Therefore, we are untethering a role's income from closed deals, aligning them entirely with the buyer or seller. This AI-assisted role is the client manager. Previously, platform insight stopped once a lead reached an agent. The client manager ensures continuity. AI organizes data, while humans assess the client stage and needs; the agent receives fully profiled clients, and because the client managers are not paid per transaction, they remain purely objective. As I mentioned, the managers are not paid per transaction. From May to July, this role handled over 50,000 leads, achieving a 7.4% lead-to-showing conversion rate, outperforming the broader market's 5%. The platform's mission is evolving from splitting commission to building a structure where every specialized skill is independently verified and compensated. ACN is shifting from a single listing workflow to a modular ecosystem, which includes consulting, showing, contracting, reporting, marketing materials, renovation, and leasing, and so on. Anyone creating incremental value is a service provider, and this is our expanded definition. The main goal is enabling professional service providers to win in the long term. Being consumer-centric means transforming the single agent into a group of independently valuable specialized roles. Now we have the help of AI, which gives us more impetus. The question: as AI advances, will agents become obsolete? This assumes agents only sell static information easily fetched by AI. However, technology reshuffles value. Some things depreciate while others become scarce. We should ask, what is depreciating and what is becoming more scarce? For the scarce part, what kind of progress can the platform and the service provider make? What is depreciating? Static information: bedrooms, price, year built, and layout. This kind of information cannot support decision-making and is very easy to get. If we only transmit or transport information, we may have no more opportunities going forward. What is scarce? Dynamic, deep, inspiring insights. They cannot be fabricated. For example, the reason for selling, renovation potential, local market assessment from seasoned managers, what is happening in the communities, and how deals typically close. This information lives in people's minds, and the industry lacks the pipeline to capture and reuse it. Fundamentally, AI does not bear the consequence of poor decisions. AI may not take accountability. As the cost of mistakes rises, consumers' need to reduce uncertainty grows. Therefore, three things will happen. Firstly, the industry becomes more valuable by mitigating uncertainty. Secondly, creating value is hard, requiring deep data and deeper surveys. Thirdly, those who transform in that direction become more valuable, including platforms and their managers. We do not need information; we need players. We need professionals who dare to make judgments and take responsibility. The previous question is about the industry and the service provider. If we look inward, how is AI applied in our business and with what results? Actually, the business itself is a production function. What are our inputs and outputs? There is human capital and labor, capital, and technology in the function. In today's AI environment, we should know AI's role in the industry. Is AI a sub-item or a direct variable? If it's a sub-item, it is an efficiency tool; if it is a direct variable, it requires a total rethink. We needed to change attitudes first. We now also open some of the foundational data, and we are lowering the threshold. We worry about disruption. We are thinking about how AI can be a new production factor rather than an opponent; it enables innovation. I think consumers finally pay for value. Consumers need a better experience, and we need to solve consumers' problems. Second, it changes management. Over the recent centuries, we have improved science and management, and we need quantifiable data in management. I think we all benefit from this methodology in KE Holdings and Lianjia. We need standards and tools for improvement. However, for the unquantifiable, they cannot be measured. This is also a big problem. Sometimes we may focus only on the numbers, and we find that the numbers are too abstract; consumers become numbers. With the help of AI bringing unstructured data, language and numbers are different types of information and signals. The granularity shifts from managing averages to managing individual properties, clients, and agents. Previously, we managed the average, but now we have the computation power and the knowledge, and we can have tailored solutions for each individual. The third part is AI changes the subdivision of labor. We talked about task segmentation in the company by AI. Now, we have scenarios including finance, human resources, products, and technology; from front stage to backstage, there is computation power. AI breaks down the threshold, and new divisions emerge. In our changing new home business, we shifted labor between humans and AI. AI helps agents compare proposals using a dynamic knowledge base, allowing agents to focus on understanding clients. Agents could fine-tune their understanding of clients. This produces both closed deals and reusable organizational capabilities. These only come from the front line. This disruption reshapes the organization and concerns four things. First is cost. AI lowers fixed costs and increases variable costs, enabling rapid iteration. Whoever iterates fast creates more value. Next is trial and error. In the past, it took a lot of effort to evaluate, test, and validate a proposal. The bigger the organization, the longer the chain. Many people hesitate. AI shifts innovation from heavy, slow investments into high-frequency, lower-cost probabilistic gains. This allows us to trial and test multiple models simultaneously, increasing the probability of winning. Next is the frontline and the middle office. Frontline workers armed with AI can rapidly build and test solutions; the mid-office can then scale with them. Last but not least, managers. In the past, the bigger the organization, the lower the efficiency. I talked to many managers. They didn't feel a strong sense of value. AI flattens the organization. It's changing roles and handling reporting. We're forcing managers to stop being megaphones and start creating real business value. They're not just presenting numbers; they are creating genuine value from the frontline because they're in the process of creating the value. Finally, the bottleneck shifts to humans. Look at KE. We have a long industrial process. AI can perfect many workflows. Those requiring human intervention become the bottleneck. There's human-to-human interaction that AI cannot replace. Whether we can unite people together and provide them with training to work efficiently with AI is key. One is culture, the other is evolution. This is essentially an industry-wide change. Now back to the earlier question: is AI a direct variable? Because it changes who we serve, our judgments, our process, and our organization. This is a direct variable. That means we're not simply installing AI into the company; we are regrowing the company with AI. Looking into the next phase, how will we know we're on the right track moving forward? We must separate where we place heavy bets from where we seek answers. I think there are three areas we're placing heavy bets: deep service, deep data, and a platform ecosystem. As information democratises, deep data becomes scarce and decisions become harder, making deeper service more valuable. As labor specializes, a platform is needed to orchestrate it. Areas where we're still seeking answers include AI's final form and the ultimate structures of management and expertise; these remain uncertain. Directional matters require unwavering bets. How do we capture users' evolving needs? Management carries this value. Morphological matters require small investments, rapid testing, and cutting losses early. Why separate these by certainty? Because directive matters require unwavering bets, whereas morphological matters require more experimentation. Looking back at the past two quarters, we have proved that keeping investment in areas with low marginal returns is meaningless. The purely skill-driven model is dead. So we should stop meaningless investments. Moving forward, we must validate four things. First, professionals: facing AI, can they use it directly or indirectly to create value? Do they have a new definition of professionalism and are they committed to it? Second, managers: can they return to the frontline and produce high-quality judgments to recreate a sense of value? Third, processes and judgments: with deeper services, can they earn customer trust? Fourth, organizational capabilities: can we turn a single success into a replicable capability? In such a discontinuous transformation, many industries face the same challenge. The way I see it, human conviction is the leading indicator; numbers are the lagging indicator. Many managers hide expertise within themselves. Without open sharing, we cannot make that into a replicable, successful model. Our core test is whether we can consistently execute consumer centricity and enable professionalism to win. This must be embedded in our culture and workflows. We will measure success across four pillars: customer, service provider, operations, and replicability; all four must cohere. If you look at these things, we have to redefine our playbook. Consumers face harder decisions, driving deeper specialization. AI depreciates role information while elevating true expertise and reorganizing internal work. Our direction is certain: deep service, deep data, and a platform ecosystem. Q2 is not the conclusion; it is just the beginning. Thank you. I will now turn the call to the analyst for Q&A.
Thank you, Stanley. As a reminder, we only accept questions on the Chinese language line. If you would like to ask a question, please press star one. If you would like to cancel your request, please press the pound key. For the benefit of all participants on today's call, please limit yourself to one question, and if you have additional questions, you can re-enter the queue. The first question comes from Timothy Zhao from Goldman Sachs. Please go ahead.
Questions and answers
Thank you, management, for taking my question. Congratulations on the strong Q2 results. My question is on the overall property market. It saw a diverging trend in volume and price in Q2, with some fluctuations in momentum in Q3. Given the uncertainty ahead, what controllable levers does the company have for Q3 and the full year?
Thank you, Timothy. In the first half, the existing home market showed a structural recovery in transactions with prices bottoming. In Q2, this recovery became more evident, though the pace varied across cities and price segments. By city, transaction volumes recovered faster in tier one cities, where the first half prices also showed greater sequential resilience. In Q2, year-over-year growth in registered existing home transactions in tier one cities outpaced other cities. According to Beike Research Institute, in the first half, tier one existing home prices rose cumulatively by 3.6% quarter-over-quarter, while national prices remained broadly stable year-over-year. Prices across all tiers have remained in an adjustment phase. For our platform, volume for lower-priced homes grew faster than mid- to high-priced homes. However, the transaction mix across unit sizes remained stable, indicating housing demand hasn't broadly downgraded to smaller homes. Instead, this reflects a downward shift in transaction price bands as prices adjusted. Meanwhile, higher-priced homes saw smaller year-over-year price declines, showing resilience in core upgrade-oriented and high-quality residences. In the new home market, overall Q2 volume remained under pressure, though projects in core cities with a strong product offering showed better support. Structurally, existing homes accounted for over 50% of the total national residential transaction area in the first half, becoming the market mainstay for housing demand. Overall, we see a structural transaction recovery while prices continue to bottom. Core cities and high-quality supply are more resilient, but the market remains polarized. With more property choices, customers are deciding cautiously, valuing professional judgment and transaction certainty. They need professional decision support, not just transaction matching or facilitation. This highlights our platform's accumulated service capability. Based on this, we will focus on three areas. First, capturing structural market opportunities to strengthen revenue resumption. We will allocate resources based on market performance across cities, customer groups, and product types, reinforcing coverage in higher tier cities. Meanwhile, centered around content-driven engagement, precise matching, and professional execution will help customers make better decisions and convert genuine demand into transactions. Second, we'll continue to reinforce financial discipline and flexible resource allocation. Our leaner cost structure improves our ability to hedge against or fend off market volatility. If pressure persists, we will dynamically allocate resources, prioritizing our core professional service provider network over short-term profits. Even if the market improves, we will not return to extensive expansion. New investments must pass stage-gated ROI and service validations before scaling, ensuring transactions translate efficiently into profits and cash flow. Third, we'll also prioritize cash flow and a solid balance sheet. We'll strictly manage receivables and collections, control risk exposure, and limit non-essential investments to preserve flexibility. Therefore, our second half operations will not rely on market events. On the revenue side, better decision support will help us win more customers. On the financial side, our healthier cost structure will protect cash flow and our core capabilities in weak markets, and release greater operating leverage while markets improve. Thank you.
Thank you. Our next question comes from John Lam from UBS. Please go ahead.
Thank you, Mr. Tao, for your answering. My question is that in Q2, the profit outpaced revenue growth significantly. Could the management break down the impact of business performance, operating efficiency, expense baselines, and if there are any one-off factors? For those improvements, how sustainable are they in the long run?
Thank you for your question. In Q2, the profit improvements were mainly driven by higher contribution margins across the core business and lower operating expenses. For the core business contribution margins, they improved year-over-year and quarter-over-quarter, driving the group's gross margin up 6.7 percentage points year-over-year to 28.6%. At the same time, GAAP operating expenses fell 14.1% year-over-year. There are three drivers. First, a lower cost and expense baseline. Over the past years, we optimized Lianjia's store and agent structure by expanding managerial efficiency, consolidating resources, and reducing low-productivity investment. This lowered fixed labor cost and our break-even point. We also have a persistent baseline. Second, improved operating efficiency in housing transactions and new homes: generally improving coverage of high-quality projects and customer conversion enhanced transaction resilience. Stable monetization and better channel efficiency drove profit growth. For existing homes, focusing on priority listings and refined operational support for connected stores significantly boosted connected store revenue and profit contribution. Third, improved unit economics and business mix in new businesses. We centralized procurement and refined cost management, lowering material cost ratios in home renovation. In rental services, the contribution margin improved due to a mix shift toward a net-basis revenue product, alongside operating improvements in labor, installation, and post-lease cost. Looking ahead to the next two quarters, under a neutral market assumption, the lower cost baseline will continue to support profit. However, marketing channel incentives and certain frontline sales costs may fluctuate quarter-over-quarter due to revenue scale, mix, and seasonality. We will not simply extrapolate a single quarter's profit, but focus on achieving balanced revenue and profit growth. If the market improves, incremental revenue will release stronger operating leverage from the lower baseline, creating greater profit upside. If pressure continues, our healthier cost structure reduces profit sensitivity to market volatility. Simply put, our current structure increases both upside potential and downside protection. In the long run, this optimization builds a healthier operating foundation. This is step one of our strategic transformation: optimizing resource allocation for the current market to cope with uncertainty. Step two is directing limited resources toward initiatives that create customer value rather than just cutting cost. Ultimately, through workflows, evaluation incentives, and platform tools, we will embed efficient resource allocation into our daily organizational capacities to support sustainable growth.
Thank you, Mr. Tao. The next question comes from Xiaodan Zhang from CICC. Please go ahead.
Good evening, Mr. Peng. Thank you for taking my question. Congratulations on your strong performance in Q2. The question is about existing homes in Q2. The existing home GTV increased 8% year-over-year, with contribution margin up 6.1 percentage points. How much of this stems from market recovery versus company operations? What metrics demonstrate this operating alpha? Thank you.
Thank you, Xiaodan. In short, while the market recovery provided a foundation for transaction volume, our existing home operating alpha did not come from expanding our network or rising prices. It came primarily from higher unit productivity within our stable network and a better conversion of platform service value into revenue. The simultaneous margin improvement confirms we did not sacrifice profitability for growth. Specifically, in Q2, the existing home transaction volume in our key cities recovered moderately, with sequential price stabilization providing some external support. However, the year-on-year average transaction price remained in adjustment, offering low price tailwind. In this backdrop, our Q2 existing home GTV grew 8% year-over-year, and the transaction volume grew nearly 25% year-over-year, significantly outperforming the market. The more direct alpha source was higher unit productivity in our connected store network. In Q2, the connected store transaction volume grew nearly 30% year-over-year. Network scale did not expand. The active stores and agents remained broadly stable year-over-year, but average transactions per active connected store rose 26%. This shows that our network is shifting from expansion to high-quality operation. As connected stores mature and platform collaboration deepens, that network volume translates directly into higher per-store output and higher efficiency. The second alpha was improved conversion of platform service value into revenue. In Q2, non-Lianjia platform service revenue grew 27.8% year-over-year, outpacing non-Lianjia GTV. In a buyer's market, professional marketing, property presentation, and transaction facilitation create clear value and are increasingly chosen by homeowners. At the same time, the existing home contribution margin rose 6.1 percentage points year-over-year to 46.1%, confirming growth was not bought at the expense of profitability. Going ahead, we will monitor if connected store output and platform service revenue conversion remain stable across different markets. We will focus more on connected store output and whether the conversion remains stable across different markets to validate the sustainability of this alpha.
Thank you, Mr. Peng. Our next question comes from Alvin from CLSA. Please go ahead.
Thank you for taking my question. For the new home business, it is also amazing. What drove the Q2 new home alpha: the operation upgrade from traditional channel collaboration to integrated marketing and the project service? What capabilities sustainably create value? Also in the process, how do you balance growth margins, contribution margin, collection cycles, and developers' credit risk?
Thank you, Alvin. Good evening. In the first half of this year, the new home market remained under pressure. But in Q2, there was improvement, with the year-over-year sales decline among top 100 developers narrowing to 9.3%. Demand and new supply increasingly concentrated in high-quality projects and upgrade-oriented products. In this backdrop, our Q2 new home GTV grew by 1.2% year-over-year, driven mainly by improved coverage of high-quality projects and higher conversion efficiency. Firstly, we identified and collaborated with high-quality and newly launched projects earlier, improving our coverage and performance in market-leading projects. Secondly, we refined needs identification and project matching. We effectively allocated resources to high-potential projects, boosting conversion rate. For the second half of this year, we assume the market will remain in adjustment, with cautious customers focusing on optimizing project mix and conversion to improve controllable operating efficiency. In the long run, our new home business aims to solve customer housing decisions, not just extend the service chain. So in a buyer's market, consumers face complex choices and need more than just access to projects. They need to understand project suitability, product value, and comparisons with nearby options in terms of price, layout, amenities, and whether their needs can be met. We are evolving from a transaction channel to customer-centric full-cycle project services. Consumer value drives this upgrade. Developer value follows from us serving consumers better. In this direction, we are building three capacities. Firstly, earlier consumer insights and matching: we use data from existing home transactions, searches, and viewings to understand demand and aid project positioning and marketing, reducing mismatch between developer products and actual demand. Second, we translate product value into comparable decision metrics, turning complex factors like location, layout, natural light, and amenities into intuitive content, with explanations and other services to help decision-making. For example, at Guangzhou Star River, 3D community presentations and layout analysis help consumers intuitively understand products, improving on-site conversion. Third, we have end-to-end project operating capacities based on customer feedback. We link customer analysis, content, and channel sales for a project, and we adjust timely based on market feedback. For example, for a project in Shangrao, we reanalyzed target consumers, adjusted sales strategy, and linked channel acquisition with on-site conversion, boosting sales efficiency. These capacities remain in early validation. We will tailor them per project, validating consumer value, operating results, and economics before scaling. We will manage payment terms and developer credit risk prudently, avoiding unreasonable risks just to expand GTV. In the long term, growth will be built on deeper consumer understanding and accurate matching, translating into high-quality revenue, healthy profitability, and strong cash collection, enabling high-quality growth. Thank you.
Thank you, Mr. Xu. The next question comes from Griffin from CITIC. Please go ahead.
My question is on home renovation and Carefree Rent. Our Q2 home renovation revenue declined faster year-over-year, but contribution margins improved significantly. What drove this decline? Are earlier adjustments largely complete? When will revenue recover? How do you balance scale, contribution margin, and delivery quality? Carefree Rent profitability or margin significantly improves; how do we ensure the sustainability?
Thank you, Griffin, for your question. The industry is undergoing a profound supply-demand restructuring as property adjustments feed into renovation. New home deliveries have dropped. Companies that previously focused on new homes are flooding into the existing home market, intensifying competition. In such an environment, navigating the cycle depends on operating quality, product competitiveness, and delivery quality, not just scale. The Q2 revenue decline stems from two factors. First, we proactively exited inefficient cities, stores, and acquisition channels over the past year. Second, overall demand remains pressured due to fewer new home deliveries, which directly weighs on the home renovation business. While competitors use price cuts and high channel incentives to fight for existing home customers, this proactive adjustment is now largely complete. We expect no further broad-based contractions this year. Despite pressured revenue, contribution margins improved significantly. Centralized procurement and supply chain optimization meaningfully lowered material costs. Service provider productivity per store also improved year-over-year, and store costs were optimized, indicating healthier retained capacity and cost structure. Regarding revenue recovery, contract value is a leading indicator. While reported revenue lags due to construction cycles, positive front-end metrics like July showroom visits improved quarter-over-quarter due to restored internal collaboration incentives, though it will take time to translate to revenue. Going forward, we will not trade profitability for scale. Long-term growth relies on delivery quality via frequent inspections and enhanced user experience and product competitiveness, achieved through tailored renovation packages and integrated showrooms at transaction centers. We are pursuing quality products and healthy profitability as three pillars to drive deep growth in revenue and profit. On Carefree Rent, managed units grew steadily to over 790,000, up 34% year-over-year. Revenue was around RMB 4.83 billion, with a 15.3% contribution margin, up 6.9 percentage points year-over-year. The year-over-year revenue decline reflects Carefree Rent's iteration toward a lighter net-based revenue product. Profitability improved due to the structural shift and operating optimizations in labor, installation, and post-lease costs. To sustain this profitability, we need more than acquiring more units: we must manage an asset pool with lower churn, fewer re-leases, and higher renewals so that costs related to labor and channels grow slower than revenue. Going forward, we will focus on three areas. First, stabilizing the managed units portfolio to reduce re-leasing channel costs. As more units enter renewal or re-leasing, we will take proactive lease management to boost renewal and retention. In Q2, owner renewal rate hit 74%, up 4 percentage points, and tenant renewal rate hit 56%, up 1 percentage point year-over-year. Second, improving efficiency to lower per-unit labor cost: Q2 managed units per asset manager rose 40% year-over-year to around 170. We will pilot separating transaction tasks, such as sourcing and leasing, from management tasks, such as renewal and post-lease, to boost specialization and per-person efficiency. AI can also help with planning, optimizing service areas, and matching task scheduling. Third, improving incremental scale quality: we will increase asset-light products to withstand rental fluctuations and adopt differentiated product solutions per city to achieve healthier unit economics. Most importantly, service quality underpins all improvements. Whether tenants or owners decide to renew hinges on reputation and channel costs. We will pay special attention to reputation and lowering channel costs. We believe profitability is sustainable when service experience, renewal, and efficiency form a positive cycle. We are solidifying this foundation to translate scale growth into profit growth. Thank you.
Thank you, Mr. Xu. That concludes our Q&A session. Thank you once again for joining us today. If you have further questions, please feel free to contact Beike's IR team through the contact information provided on our website. That concludes today's call, and we look forward to speaking with you next time. Thank you and goodbye.