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DATE

Friday, Aug. 21, 2026 at 8:00 a.m. ET

CALL PARTICIPANTS

• Co-founder, Chairman, and Chief Executive Officer - Stanley Peng
• Executive Director and Chief Financial Officer - Tao Xu
• Investor Relations Director - Siting Li

TAKEAWAYS

• GTV Growth -- 6.3% year over year, driven by a structural recovery in existing home transactions and improved coverage in higher-tier cities.
• Non-GAAP Net Income -- RMB 3.2 billion, representing a 74.9% year-over-year increase due to a healthier cost structure and higher operating efficiency.
• Gross Margin -- 28.6%, expanding 6.7 percentage points year over year reflecting improvements in contribution margins across all core business lines.
• Existing Home GTV -- RMB 629.9 billion, rising 8% year over year as transaction volumes in tier one cities outpaced other markets.
• New Home GTV -- RMB 258.4 billion, up 1.2% year over year despite broader market pressure, supported by collaboration on high-quality projects and higher customer conversion.
• Home Renovation Revenue -- RMB 3.2 billion, declining 30.1% year over year because of proactive exits from inefficient cities and lower new home deliveries.
• Home Rental Revenue -- RMB 4.8 billion, down 14.8% year over year reflecting a transition to a net-basis revenue recognition model for lighter-risk products.
• Managed Rental Units -- 790,000 units, growing 34% year over year with net-base products now comprising over 50% of the managed portfolio.
• GAAP Operating Expenses -- RMB 4.0 billion, falling 14.1% year over year as management optimized marketing spend and organizational efficiency.
• Broad Cash Balance -- RMB 67.3 billion, providing liquidity to support share repurchases and business development.
• Existing Home Contribution Margin -- 46.1%, improving 6.1 percentage points year over year through lower fixed labor costs and a shift toward platform service revenue.
• New Home AR Turnover -- 39 days, an improvement of 12 days year over year reflecting effective risk management and collections from developers.
• Rental Owner Renewal Rate -- 74%, up 4 percentage points year over year as the company focused on service quality and lease management.
• Leasing Agent Efficiency -- 5.6 transactions per agent, increasing from three transactions per agent between April and July following a reorganization of service areas into smaller blocks.
• Share Repurchases -- $250 million during the second quarter, bringing the total program expenditure since September 2022 to approximately $2.99 billion.

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RISKS

• Tao Xu warned that "overall demand remains pressured due to fewer new home deliveries, which directly weighs on the home renovation business," noting that the company has proactively exited inefficient cities as a result.
• Stanley Peng stated, "the market remains polarized," with housing demand concentrated in high-quality supply and core cities while prices across all tiers continue to adjust.

SUMMARY

KE Holdings Inc. (BEKE +4.47%) reported second-quarter results where profit growth outpaced revenue, driven by cost optimizations and a shift toward consumer-centric operational strategies. Management stated that the organization is moving from a single transaction commission model toward a modular ecosystem that utilizes AI to assist specialized roles. The company reported a significant expansion in non-GAAP net margins to a three-year high of 13% while maintaining a cash balance of RMB 67.3 billion. Capital allocation remained focused on shareholder returns through $250 million in share repurchases and the first buyback executed in the Hong Kong market.

• The company introduced an AI-assisted client manager role that handled over 50,000 leads with a 7.4% showing conversion rate, which outperformed the broader market average of 5%.
• Management shifted operational strategy from citywide metrics to district-specific analysis to tailor service solutions for high-end communities where clients view properties across geographic boundaries.
• The zero transaction ratio for leasing agents dropped from nearly 25% to under 10% after the company divided service areas into smaller blocks and rematched properties based on agent familiarity.
• Chairman Stanley Peng mandated presence for managers, requiring them to leave meeting rooms for the front line to directly assist with signing centers and stale listings.
• The Agent Cooperation Network is transitioning from a single listing workflow into a modular ecosystem covering marketing, renovation, and leasing services to enable professional service providers to independently monetize specialized skills.

INDUSTRY GLOSSARY

• GTV: Gross Transaction Value, representing the total value of all transactions processed through the company's platform.
• ACN: Agent Cooperation Network, the operating system that facilitates collaboration and commission sharing among real estate service providers.
• Lianjia: The proprietary real estate brokerage brand owned and operated by the company.
• Carefree Rent: A rental property management service that provides professional operations and standardized maintenance for property owners.
• Unit Economics: A financial model evaluating the profitability and costs associated with a single unit of business, such as an individual store or customer transaction.

Full Conference Call Transcript

Siting Li: 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 all 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 all 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.

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% year-over-year, a three-year high. Profit improvements were driven by a healthier cost structure, strict financial discipline, and a 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 a 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 base, accounted for a larger share.

This quarter, non-Lianjia platform service revenue increased to 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% 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% 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 a 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 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 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 sinecure-related 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-on-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, 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 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 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 priority or key metrics. Ultimately, we will balance business development with the 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.

Stanley Peng: 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 change 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 the district-specific and the project-specific strategies. Rather than tracking a single citywide metric, we analyze specific districts or projects to tailor solutions and what is the solution for each community. For example, in a high-end community where clients view property across districts, our legacy geographic bound model failed, and we regrouped operational units based on actual clients' viewing path, assigning project experts for professional presentations and clients' 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 allow us to replicate this model, and other cities have begun similar operations explorations. Second is shifting the metrics. Scale and markets share still matter. But now we focus more on consistent agent transactions, rising agent efficiency, and income healthy store profitability, and the stable service quality. Leasing illustrates this perfectly. In 2025, we have at most 700 agents for leasing at the peak. The average agent efficiency fell below two transactions. Instead of adding headcounts, we divided the city into smaller blocks, rematching properties, clients, and agents based on familiarity and the capabilities.

From April to July, average agent efficiency jumped from three to 5.6 transactions and a zero transaction ratio dropped from nearly 25% to under 10%. I think what matters is that the effective organization matters more than mere head count. 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 manager is two, presence. You cannot learn to swim without getting in the water. In short, operationalizing transformation means refined operations, shifted metrics, and mobilized the people. This stems from a single approach, solving real consumer and frontline problem first, then reorganizing our people, resources, and platform.

We are moving towards the changes and that they are 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 goods expanded from one, two, three. 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's capacity. Second, building expertise require mutually exclusive path. 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 the most valuable action has shifted from providing options to confidently eliminating them.

I think we are not only offering more choices to the consumers, instead, we needed 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 buyers 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 human assesses 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 have 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 definition, which is expanded. 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 give us more impetus. The question, as AI advances, will agents become obsolete? This assumes agents only sells 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 the platform and the service provider can make? What is depreciating? Static information, bedrooms, price, and year built, and also the layout of the house. I think this kind of information cannot support the decision-making, and it is very easy to get.

If we only transmit or we only 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 of selling, renovation potential, or local market assessment from seasoned managers, and how is the situation in the communities by the managers, and what is the closings and how is the deal most of the time. 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 any accountabilities. As the cost of counting mistake rises, consumer needed 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. The third thing is those who transform in the direction become more valuable, including platforms and their managers. We do not need information. We are players. We need professional who dare to make judgments and take responsibility. The previous question is about the industry and the service provider. If we look around, if we look inward, then with those comes to the question for how is AI applied in our business and with what results? Actually, the business in itself is a production function.

What is our input and what is output, and there is human capital and labor, capital and technology in a function. In today's AI, we should know the situation of AI in the industry. Is AI a sub-item or a direct variables? If it's a sub-item, it is an efficiency tool, or if it is a direct variable, it requires a totally right. We needed to change attitudes in the first. We now also open some of the foundational data, and we are lowering the threshold. We are worried about whether there will be disruption. We are thinking about how AI can be a new production factor rather than an opponent enables innovation.

I think the consumers finally pay the value. I think the consumers need a better experience, and we need to solve the problems of consumers. The second is it changes management. In the recent 200 years, we have improvement in the science and management, and we need quantifiable data in the management. I think we all benefit from this methodology in KE Holdings and also Lianjia. We need standard, and we also need tools for the improvement. However, for the unquantifiable, they cannot be measured. This is also a big problem.

But sometimes we may only focus on the numbers, and we find that sometimes we find that the numbers are too abstract, and the consumers now become the numbers and also become the number one in the standard. However, with the help of AI brings the unstructured data and I think the language and the numbers are totally different informations and signals. The granularity shifts from managing average to managing individual properties, clients, and agents. Previously, we manage the average, but now we have the computation powers and the knowledge, and we can have the tailored solution for each individuals. The third part is about AI changes subdivision of labor.

We talk about the segmentation of the task, or in the company by AI. Now, we have these scenarios, which includes financial, human resource products, technology, and also from the stage, backstage, and the computation power. But now we have AI breaking down the threshold, and all of them are in the computation power of AI. Previously, the old division vanish and the new ones emerge. In our changing new home business, we shifted the labor between humans and AI. AI helps agents compare proposals using a dynamic knowledge base, allowing agents to focus on understanding clients. The agents could fine-tune their understanding of the clients. This produces both close deals and also reusable organizational capabilities.

These only come from the front line. This disruption reshapes the organization. It concerns on four things. First is cost. AI lowers fixed costs and increases variable costs enabling rapid iteration. Whoever iterates fast, who creates more value. The next is the trial and error. In the past, it takes a lot of efforts. Right now, it takes a long path to evaluate, test, validate a proposal. The bigger the organization, the longer the chain is. Many people just hesitate. Right now, AI shifts innovation from heavy, slow investments into a high-frequency and low cost of probability gains.

This allows us to trial and test multiple models at the same time, and we have a higher probability of winning out the game. Next is the frontline and the middle office. The 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 is. Right now, I actually talked to a lot of managers. They don't feel like a lot of a sense of value. Right now, AI flattens the organization. It's changing the roles, handling the reporting. We're forcing managers to stop being megaphones and start creating real business value.

They're not just simply just presenting the numbers, they are actually creating real 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 a lot of the workflows. And those that with the human intervention becomes the bottleneck. There's this human and human interaction that AI cannot replace. Whether we can unite people together and provide them with the training, allow them to work efficiently with the AI. One is culture, the other is evolution. This is essentially a change we're talking about towards the whole industry.

Now back to the very first question, whether AI is 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? Now we must separate two things, where we need to 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 democratic side, deep data becomes scarce and the harder the decision-making becomes, and the deeper service becomes more valuable. As labor specializes, a platform is needed to orchestrate it. The one where we're still seeking answers, AI's final form and the ultimate structures of management and expertise remain uncertain. Directional matters require unwavering bets. How do we capture users' evolving needs? Management, of course, carries this value. So morphological matters require small investments, rapid testing, and cutting losses early. So why do we need to separate these things by certainty? Because again, we have already proven that directive matters requires unwavering bets, whereas the morphological matters requires more investment and rapid testing.

Looking back at the past two quarters, we have approved in some areas that keeping investment in areas with low marginal returns is meaningless. The purely skill-driven model is dead. So we should stop those meaningless investments. Moving forward, we must validate four things. First, professionals. Facing AI, whether they can use it directly or indirectly to create a value. Do they have a new definition for what is professionalism and whether they are committed to this concept? Second, for managers, whether they can return to the frontline and produce high-quality judgments to recreate this sense of value. The third is the processes and judgments. With the deeper services, can they earn the trust from their customers?

Whether they can earn a better recognition or trust. Number four, organizational capabilities. Can we turn a single success into a replicable capability? In such a discontinuous transformation, for many industries, they are pretty much faced with the same challenge. The way I see it, human conviction is the leading indicator. Numbers are the lagging indicator. Many of the management tend to hide their expertise within themselves. Without the open sharing, we cannot make that into replicable, successful model. Our core test is whether we can consistently execute consumer centricity and enable professionalisms to win. This must be embedded in our culture, in our workflows.

We will measure the success across four pillars: customer, service provider, operations, and replicability, all four must co-choose. If you look at these five things, we have to redefine our playbook. Consumers are facing harder decisions to make, that is driving deeper specialization. The AI is depreciating role info while elevating true expertise and reorganizational 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.

Siting Li: 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.

Timothy Zhao: 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?

Stanley Peng: Thank you, Timothy. In the first half, the existing home market showed a structural recovery in transactions with the 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 a 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 decline, 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 resuming. We will allocate resources based on market performance across cities, customer groups, and property tax, 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 translates 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.

Siting Li: Thank you. Our next question comes from John Lam from UBS. Please go ahead. Thank you, Mr. Tao, for your answering.

John Lam: 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 is any one-off factors? For those improvements, how sustainable are they in the long run?

Tao Xu: Thank you for your question. In Q2, the profit improvements were mainly driven by higher contribution margins across the core business and the lower operating expenses. For the core business contribution margins, they improved year-on-year and quarter-on-quarter, driving the group's gross margin up 6.7 percentage points year-on-year to 28.6%. At the same time, the GAAP operating expenses fell 14.1% year-on-year. There are three drivers. First, a lower cost and expenses baseline. Over the past years, we optimized Lianjia's store and agent structure by expanding management expense, consolidating resources, and reducing low productivity investment. This lowered the fixed labor cost and our break-even point. We also have a persistent baseline.

Second, improved operating efficiency in housing transaction in new homes, generally coverage of high-quality projects and improving customer conversion, enhanced transaction resilience. We also have stable monetization and better channel efficiency drove profit growth. For the existing homes, focusing on the priority listings and refined operational support for connected stores significantly boosted connected store revenue and profit contribution. Thirdly, improved the unit economics and the business mix in new business. We have centralized the procurement and refined cost management, lowered the 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 the generally 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 contribute to support profit. However, marketing channel incentives and certain frontline sales cost may fluctuate quarter-on-quarter due to revenue scale, mix, and also 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 resources allocation for current market. This is how we can cope with the 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.

Siting Li: Thank you, Mr. Tao. The next question comes from Xiaodan Zhang from CICC. Please go ahead.

Xiaodan Zhang: Good evening, Mr. Peng. Thank you for taking my question. Congratulations on your strong performance on Q2. The question is about existing homes in Q2. The existing home GTV increased 8% year-on-year, with contribution margin up 6.1 percentage point. How much of this stems from market recovery versus company operations? What metrics demonstrate this operating alpha? Thank you.

Stanley Peng: Thank you, Xiaodan. I am happy to hear your voice. 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 civilization providing some external support. We have that 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-on-year, and the transaction volume grew nearly 25% year-on-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-on-year. Network scale did not expand. The active stores and agents remained broadly stable year-on-year, but average transaction per active connected store rose 26%. This shows that our network is shifting from expansion to high quality operation. As earlier connected stores mature and the platform collaboration deepens, that network volume translates directly into higher per store output and high efficiency. The second alpha was improved conversion of platform service value into revenue.

Q2, non-Lianjia platform service revenue grew 27.8% year-on-year, outpacing non-Lianjia GTV. In a buyer's market, professional marketing, property presentation, and transaction facilitation create a clear value and are increasingly chosen by the homeowners. At the same time, the existing home contribution margin rose 6.1 percentage points year-on-year to 46.1%, confirming growth was not bought at the expense of profitability. Going ahead, we will monitor if connected store output and the platform service revenue conversion remain stable across different markets. Going forward, we will focus more on the output of the connected store and also whether the conversion remains stable across different markets to validate the sustainability of this alpha.

Siting Li: Thank you, Mr. Peng. Our next question comes from Alvin from CLSA. Please go ahead.

Alvin Huang: Thank you for taking my question. For the new home business, it is also amazing. What drove the Q2 new home alpha as 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?

Tao Xu: Thank you, Alvin. Good evening. In the first half of this year, the new home market remained under pressure. But in Q2, there was the improvement, with the year-on-year sales declining among top 100 developers narrowing to 9.3%. Demand and new supply increasingly concentrated in qualitative, high-quality projects and upgrade-oriented products. In this backdrop, our Q2 new home GTV grew by 1.2% year-on-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 have 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 choice and multiple choice, and they need more than just access to the project. I think they need to understand the project suitability, product value, and the comparisons with the nearby options and alternatives in terms of price, layout, and also the amenities and whether their needs can be met.

We are also evolving from the transaction channel to the customer-centric full-cycle project services. What we hope is that we want to be consumer-centric. We want to provide full-cycle services and integrating consumer insights into project research, repositioning, and sales, and also the decision-making to support the consumers. Consumer value drives this upgrade. Developer value follows from us serving consumers better. In this direction, we are also building three capacities. Firstly, we have earlier consumer insights and matching. We are using data from existing home transactions, searches, and viewings. We understand the demand to aid a project's positioning and marketing, reducing the mismatch between developer products and actual demands. Second, we translate product value into comparable decision metrics.

We turn complex factors like location, layout, and natural light, and amenities into intuitive content. We also have the explanation and also other services to help the decision-making. For example, at Guangzhou Star River make levels, we have 3D community presentations and a layout analysis, which help consumers intuitively understand the products, improving on-site conversion. Thirdly, we have end-to-end project operating capacities based on customer feedback. Now we link customer analysis, content, and channel sales for a project, and we also have the timely adjustment and resources allocation. For example, for a project in Shangrao, the developer helped to gain local market knowledge. We reanalyzed target consumers.

We adjusted the feedback from the market, and we adjusted the sales strategy and linked channel acquisition with on-site conversion, boosting the sales efficiency. But I think these capacities remain in early validation. We will tailor them per project, validating consumer value, operating results, and economics before scaling. In all of those projects, I think we need a sustainable validation, and we can have better replication as we expand our services and as our service scope deepens. We will manage payment terms and the developer credit risk even more prudently, avoiding the unreasonable risks just to expand the GTV.

In the long term, the growth will be built on deeper consumer understanding and accurate matching, ultimately translating into high-quality revenue, healthy profitability, and strong cash collection, and we can have high-quality growth. Thank you.

Siting Li: Thank you, Mr. Xu. The next question comes from Griffin from CITIC.

Speaker 7: 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, and how do we ensure the sustainability?

Tao Xu: 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 the competition. In such an environment, navigating the cycle depends on the 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 a healthier retained capacity and cost structure. Regarding revenue recovery, the contract value is a leading indicator. While reported revenue lags due to construction cycles, positively 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 profitably for scale. Long-term growth relies on delivery quality via frequent inspections.

It also enhanced the user experience, product competitiveness, which will be achieved through tailored renovation packages, as well as integrated showrooms at transaction centers. We are pursuing quality products and healthy profitability as three pillars, a growth strategy that will drive our deep growth in revenue and profit. On Carefree Rent, the units under management gradually grow steadily to less than 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 structure shift and general operating optimizations in labor, installation, and post-lease costs.

On top of this, whether we can sustain this profitability, I think that requires more than just acquiring more units. It requires managing an asset pool with a lower churn, fewer re-leases, and higher renewals. This way, the costs related to labor and channel will grow slower than actual revenue. Going forward, I think we will focus on three areas. First, stabilizing the units under management portfolio to reduce the re-leasing channel costs. As we see more units under management, more units are entering renewal or existing homes are going for re-leases. We are going to take a proactive lease management and deliver quality service. This will boost renewal and also boost retention.

In Q2, the owner renewal rate hit 74%, up 4 percentage points, and the 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. Going forward, 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-personnel efficiency. AI also can come into play. We can use AI planning to manage scale complexity by optimizing service areas, matching task scheduling, as well as many other refined operational measures. Third, improving incremental scale quality. We will increase asset light products to withstand rental fluctuation.

Additionally, tailored to different cities, we are going to adopt differentiated product solutions that will achieve healthier unit economics. Most importantly, service quality underpins all of these improvements. So whether tenants or owner decides to renew, hinges on the reputation we purchase and also the channel costs. We are going to pay special attention to reputation and lower channel costs. We believe profitability is only sustainable when service experience renewal and efficiency forms a positive cycle. We are solidifying this foundation to translate our scale growth directly into profit growth. Thank you.

Siting Li: 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.