KE Holdings Inc. (BEKE) Q2 2026 Earnings Call Transcript

Ladies and gentlemen, thank you for standing by for our K.E. Holdings second quarter 2026 earnings conference call. I am sitting the higher director of K.E. Holdings. Please note that today's call, including the management's prepared remarks and Q&A session, will all be in Chinese. Simultaneous interpretation 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. It is 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 Pong, our co-founder, chairman and chief executive officer, and Mr. Tao Shi, our executive director and CFO. Mr. Shi will provide an overview of our business update and financial performance. Then, Mr. Pong will share more on the progress of our strategic transformation. Before we continue, I refer you to our Safe Harbor Statement in our Earnings Price Release, which applies to this call as we will make forward-looking statements. Please note that Baker's Earnings Price 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 price 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 the 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. Well, now I'll turn the call over to our CFO, Mr. Tao Xiu. Thank you, Suding. Hello, everyone. Welcome to our Q2 2026 earnings call. Let me begin with the key financial takeaways. Our total GTV return to growth. Despite a modest year-over-year revenue decline, profits increased significantly, materially outperforming both GTV and revenue. In Q2, GTV increased to 6.3% a year, while revenue decreased to 5.7% a year a year. This revenue decline stemmed primarily from adjustments in our home renovation and furnishing business, and revenue recognition impacts from iterative product modeling in the home renovate services. Non-GAAP net income grew 74.9% a year a year to $3.185 billion. non-GAAP net margin reached a 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 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% a year-over-year. This combination of gross margin expansion and the lower operating expenses fueled our profit growth. Next, I'll review our segment financial performance. First, existing home transaction services. Q2 scale return to growth and profitability improved significantly. Currently, GTV reached $629.89 billion, up 8% year-over-year, and 17.9% quarter-over-quarter. Revenue was $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-based, account 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 a 46.1% up, 6.1 percentage points every year, driven by a lower fixed labor cost 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 $258.39 billion, up 1.2% year-over-year and 77.1% quarter-over-quarter. Revenue reached $8.95 billion, up 3.8% year-over-year and 75.9% quarter-over-quarter. Despite the pressure to market, we maintain the stable scale by collaborating on high-quality projects, improving customer conversion, and optimizing costs. Due to contribution margin reached 28.8% up, 4.4 percentage points a year per year, driven by cost structure optimization from refined operations. It also rose 3.1 percentage points a quarter per quarter, benefiting from the same factors plus operating leverage from revenue growth. Third, home renovation and furnishing. Q2 revenue was $3.19 billion, down 30.1% a year per year, and up 36.4% a quarter per quarter. However, 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 quote-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 quote-over-quarter driven by lower material cost through centralized procurement and refined cost management. Home rental services. Q2 revenue was $4.83 billion down 14.8 percent year-over-year and 3.6% quarter-over-quarter. This stemmed from transitioning carefree rent to a lighter, low-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% every 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 in operating improvements from lower labor, installation, and post-lease costs. Quote-over-quarter contribution margin rose 0.5 percentage points, driven by a continued increase in net-based products. With emerging in other businesses, Q2 revenue reached 550 million RMB up 26.4% a year-over-year and 70% quarter-over-quarter. Next, turning to costs, expenses, and a profit. Q2 store-related costs were 560 million RMB down 25.9% a year-over-year and broadly stable quarter-over-quarter. the year-over-year decline reflects a lien just rent cost optimization and network adjustment total q2 gap operating expenses were 3.99 billion rmb down 14.1 percent uvd driven by improved organizational efficiency optimized marketing spend and continued financial display operating expenses rose 21.3 percent in total of the quarter due to higher selling expenses from the home renovation seasonal recovery and the bed debt provisions in new home business. Specifically, G&A expenses were 2.04 billion, down 2.1% year-over-year. The 18.9% quarter-over-quarter increase resulted from a full bed debt provision of around $280 million following a prudent assessment of SYNEC-related receivables and collateral value. Sales and marketing expenses were 1.4 billion down 26.1 percent of year due to optimized sales personnel costs and refined marketing spend. But rose 29.6 percent of quarter over quarter from seasonal and higher home renovation selling expenses. R&D expenses were 550 million RMB down 13.4 percent a year-over-year due to lower labor and technical service costs, but up 11.4% quote-over-quarter due to increased technical service fees. On the bottom line, Q3 GAAP operating profit reached a 3.026 billion RMB up, 185.6 billion a year. Non-GAAP operating profit was 3.592 billion, up 123.6% a year. year. Gap 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-Gap operating profit grew 115.7% quarter-over-quarter with a 14.6% margin, up 8.5 percentage points of year-over-year and 5.8 percentage points quarter of a quarter. This year on year in quarter of a quarter margin expense was driven mainly by higher gross margins and lower operating expenses for issuers. Q2 GAAP net income was 2.624 billion, up 100.8 year of a year, and 109.1% of quarter of a quarter. A non-gap net income was 3.185 billion RMB up, 74.9% of year per year, 97.6% of quarter per quarter. Finally, turning to cash flow, balance sheet, and shareholder returns. Our Q2 net operating cash inflow was 6.61 billion RMB net. A new home account to receive a turnover was around 39 days down, around 12 days of year per year, reflecting effective risk management. Excluding customer deposits, our end of Q2 broad cash balance remained at around 67.3 billion RMB. This ample liquidity strengthened our risk of 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 spend around $460 million US dollars on repurchases, up around 14% of year-to-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 U.S. dollars in shares, representing around 14.8% of offsetting 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 Pong. Please go ahead.

Thank you, investors and analysts. Good evening. So last quarter, we discussed our shift toward 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. So 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 by passing agents? Thirdly, as AI advances, will agents become obsolete? Fourthly, how is AI applied in our business and what is it going out? Fifthly, how will we know we are on the right track moving forward? So for the first question, what's changed 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. So rather than checking a single city-wide 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 of legacy geographic bound and model field. And we regrouped operational units based on actual clients viewing path, assigning project experts for professional presentations and client experts to address specific family needs. So 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 become similar explorations. Second, shifted 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. So leasing illustrates this perfectly. In 2025, we have at most 700 agents for leasing at the peak. And the average agent efficiency fell below two transactions. Instead of adding head accounts, we divided the city into smaller blocks, rematching properties, clients, and agents based on familiarity and the capabilities. So from April to July, average agent efficiency jumped from 3 to 5.6 transactions, and a zero transaction ratio dropped from nearly 25% to under 10%. So I think what matters is that the effective organization matters more than mere headcount. Thirdly, mobilize the people. Managers have lasted meeting rooms for a different time. These quarter managers personally sold stale listings, revisited dead leads, and accompanied agents to signing centers. And my only requirement for a manager is to presence. You cannot learn to swim without getting in the water. So in short, operationalizing transformation means refined operations, shifted metrics, and mobilized the people. So this stems from a single approach, solving real consumer and frontline problem first, then reorganizing our people, resources, and a platform. So we are moving towards changes, and that they are now being seen in operational units. The second question is, does being consumer-centric mean bypassing agents? So this assumes that if the platform moves closer to the consumer, it must tick from the agent. Historically, we only split a single transaction commission, which is a zero sign game. So this is what we did in the past, but to break this equation, we must create more high value tasks, not just re-divided the same money. Consumers are changing. Good used to be a static property attribute today. I think good means a proper match. The variables determine goods expended from one to three. The property, the family's situation, and also the service provider. So the service provider is now a vital variable, not just a conduit. So as decisions become harder, tasks must be segmented. There are three reasons. First, the required knowledge exceeds one's personal capacity. For example, we need to know the properties, client circumstances, mortgage, and the renovations and a furnishing business, so this exceeds one's capacity. Second, building expertise requires mutually exclusive path. You must either deeply root yourself in one project or follow a group of clients, so you cannot do both simultaneously. So 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 and instead we needed to help them to filter however filtering does not mean transaction so as long as income relies solely on closings to professionalism won't develop I think professionalism must be financially viable so therefore Therefore, we are tethering our roles' income from closed deals, lining them entirely with the buyers or seller. This AI-assisted role is the client manager. So previously, platform insights stopped once a lead reached an agent. The client manager ensures continuity, AI organizes data, and while a human assesses the client stage and the needs. The agent receives fully profiled client because the client managers are not paid per transaction and that they remain purely objective. As I have mentioned, the managers are not paid per transaction. So from May to July, this role handled over 50,000 leads, achieving a 7.4% lead to showing conversion rate outperforming the broader market 5%, so the platform's mission is evolving from splitting commission to building a structure where every specialized skill is independently verified and compensated. ECM 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. So anyone creating incremental value is a service provider. And this is our definition, which is expanded. So the main goal is enabling professional service providers to win in the long So, being consumer-centric means transforming a single agent into a group of independently valuable specialized roles. And now we have the help of AI, which gives us more impetus. So the question, as AI advances, will agents become obsolete? So this assumes agents only sell static information easily, fetched by AI. However, technology reshuffles value. We are, some things depreciate while others become scarce. So we should ask, what is depreciating and what is becoming more scarce? So for the scarcest part, what kind of progress the platform and service provider can make? So what is depreciating? Static information, bedrooms, price, and year build, and also the layout of the house. So I think that this kind of information cannot support the decision making and it is very easy to get. So if we only transmit or we only transport the information, we may have no more opportunities going forward. So what is scarce, dynamic, deep, inspiring insights, and 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 closing, and how is the deal last time. And this information lives in people's minds, and the industry lacks the pipeline to capture and reuse it. And fundamentally, AI does not bear the consequence of poor decisions, and AI may not take any accountabilities. So as the cost of housing mistake rises, consumer needed to reduce uncertainty and growth. Therefore, three things will happen. Firstly, the industry becomes more valuable by mitigating uncertainty. Secondly, creating value is hard, requiring deep data and deep surveys. The third thing is those who transform in the direction become more valuable, including platforms and the managers. So we do not need information, we're players. We need professionals who dare to make judgment and take responsibility. So, the previous question is about the industry and the service provider, and if we look around and if we look inward, then it comes to the question for how is AI applied in our business and with what results. Actually, the business itself is a production function. What is our input and what is the output? and there is human, labor, and technology in the function. So in today's AI, we should know the situation of AI in the industry. So is AI a sub-item or a direct variable? So if it's the sub-item, it is an efficiency tool, or if it's a direct variable, it requires a total rewrite. so we needed to change attitudes in the first way now also open some of the foundational data and we are lowering the threshold so well we are worried about whether there will be disruption and we are thinking about how AI can be a new production structure rather than an opponent enables innovation. So 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. And I think we all benefit from this methodology. In KE Holdings and also Lientia, 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 sometimes we find that numbers are too abstract, and that consumers now become the numbers and also become the number one in the standard. However, with the help of AI, AI brings the unstructured data and writing the language and the numbers are totally different information and signals. And the granularity shifts from the managing average to managing individual properties, clients and agents. Previously, we managed the average, but now we have the computation powers and the knowledge. And we can have the tailored solution for each individual. And this third part is about AI changing subdivision of labor. We talk about the segmentation of the task in the company by AI. Now we have these scenarios which include financial, human resource products, technology, and also from the stage back stage and the computation power. But now we have AI breaking down the threshold, and all of them are in the computation power of AI. And previously, so the old division vanished and the new ones emerged.

So 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. so the agents could, you know, fine tune their understanding of the clients. So this produces both closed deals and also reusable organizational capabilities. So these only come from the front line. So this disruption reshapes the organization. So it concerns on four things. First is cost. You know, AI lowers fixed costs and increases variable costs. enabling rapid iteration. So whoever iterates fast, who creates more value? And the next is a trial and error. So in the past, it takes a lot of efforts. Right now, it takes a long path to evaluate, test, validate a proposal. So the bigger the organization, I mean, the longer the chain is, many people just hesitate. So right now AI shifts innovation from heavy slow investments into a high frequency and low cost of probability gains. So this allows us to trial and test the multiple models at the same time and we have a higher probability of winning out the game. Next is the frontline and to the admitted office. So the frontline workers armed with AI can rapidly build and test the solutions. The mid-office can then scale stuff. Plus, but not least, managers. So in the past, the bigger the organization, so 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 Flatten's the organization. They're exchanging the role, handling the reporting, forcing managers to stop being megathons and start creating real business value. So they're not just simply presenting the numbers, they are actually creating real genuine value from the front line. Because they're in the process of creating the value. Finally, the bottlenecks shift 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. So there's this human and human interaction that AI can have to replace, so whether we can unite people together and provide them with the training, allow them to work efficiently with AI. So one is culture, the other is evolution, so 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 so this is a direct variable that means we're not simply installing ai into the company we are re-growing the company with ai looking into the next phase how we will 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 where placing heavy bets deep service deep data and a platform ecosystem so as information democratic side deep data becomes the 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 so while we're seeking it so that 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 unweathering bets so how do we capture users evolving needs management of course carries its value more for a logical matters requires small investments rapid testing and cutting losses early why do we need to separate these things by uncertainty. Because again, we have already proven that directive matters requires unrivering bets, whereas the morphological matters requires more investment in rapid testing. So 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. We be sure to stop those meaningless investments. Most of all, 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're committed to this concept? And second, for managers, whether they can return to the front line and produce high quality judgment 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 broader recognition a better recognition or trust number four organizational capabilities can we turn a single success into a replicable capability so in such a discontinuous the transformation. So 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. So many of the management tend to hide their expertise within themselves. So without the the open sharing, we cannot make that into replicable, successful models. So our core test is whether we can consistently execute consumer centricity and enable professionalism to win. This must be embedded in our culture and our workflows. So we will measure these success across four pillars, customer, service provider, operations and replicability, all four must to co-choose. If you look at these five things, we have to redefine our playbook. Consumers are facing harder decisions to make, so that is driving deeper specialization. The AI is depreciating role and role while elevating true expertise in reorganization of internal work. Our direction is certain deep service, deep data, and a platform ecosystem. So Q2 is not the conclusion. It is just the beginning. Thank you. I'll now Turn the call to the analysts for a 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 Tim Fijal from Goldman Sachs. Please go ahead. 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 trollable levers does the company have for Q3 and the Foo Year? 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 tier, 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 to other cities. According to Baker 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 remain in an adjustment phase. For our platform, volume for lower-priced homes grow 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 of smaller year-over-year price declined, 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 strong product offerings 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 polarised. 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 capabilities. 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. We'll continue to reinforce financial displaying and flexible resource allocation. Our leaner cluster 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 validation before scaling, ensuring transactions translates efficiently into profit and cash flow. Third, we'll also prioritize cash flow and a solid balance sheet, we'll strictly manage receivables and collection control risk exposure and limit non-essential investments to preserve flexibility therefore our second-half operations will not rely on market bets 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 a core capability in weak markets and release greater operating leverage more market improve thank you thank you so

our next question comes from John Lang from UBS please go ahead thank you Mr. Tao for your answering so my question is that in queue to the profit outpaced revenue growth significantly. So, could the management break down the impact of business performance, operating efficiency, expense baselines, and if there is any one-off factors? And 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 the lower operating expenses. For the core business contribution margins, they incur year-on-year and quarter-on-quarter, driving the group's gross margin up 6.7 percentage points year-on-year to 28.6 percent. At the same time, the gap operating expenses fell 14.1 percent year-on-year. There are three drivers. First, a lower cost in the expenses baseline. Over the In the past years, we optimized lien-jastor and agent structure by expanding management expense, consolidating resources, and reducing low productivity investment. And this lowered the fixed labor cost and our break-even point, so we also have a persistent baseline. Second, improved operating efficiency in housing, transaction in new homes, generating coverage of high-quality projects and improving customer conversion, enhanced transaction resilience. We also have stable monetization and a better channel efficiency drove profit growth. And for the existing homes focusing on the priority listings and refund operational support for connected stores significantly boosted connected store revenue and a profit contribution. Thirdly, improved units, economics, and the business mix in new business. We have centralized procurement and refined cost management, lowered 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 a genuine operating improvement 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 profits. However, marketing channel incentives and a certain front line 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 the profit growth. So if the market improves, incremental revenue will release stronger operating leverage from the lower baseline, creating greater profit upside. If pressure continues over health, their concentration reduces profit sensitivity to market volatility. And simply put, our current structure increases both upside potential and the downside projection. In the long run, this optimization builds a healthy operating foundation. This is step one out of our strategic transformation, optimizing resources allocation for current markets. And this is how we can cope with the uncertainty. Step two is directing limited resources toward initiatives that create customer value rather than just a cutting cost. And ultimately, through workflow, evaluation incentives, and the platform tools, we will embed efficient resource allocation into our daily organizational capacities to support a sustainable growth. Thank you Mr. Tao. The next question comes from Xiaodan Zhang from CICC. Please go ahead. Good evening Mr. Tao. Thank you for taking my question. Congratulations on your strong performance on Q2. So the question is about existing homes. In Q2, the existing home GDP increased 8% year-on-year with contribution margin up 6.1 percentage point. So how much of these stems from market recovery versus company operations, and what metrics demonstrates this operating alpha. Thank you, Xiaotan. I am happy to hear your voice. In short, while the market recovery provided a foundation for transaction volume, our existing home operating alpha didn't come from expanding our network of rising prices. It came primarily from higher unit productivity within a stable network and a better conversion of platform service value into revenue. The simultaneous margin improvement confirms we didn't 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. And we have that as the external support. However, the year-on-year average transaction price remained in adjustment, offering no price till wind. In this backdrop, our Q2 existing home GDB grew 85% 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 didn't expand. The active source and agents remain 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, material and platform collaboration deepens, and that network value translates directly into higher per-store output and higher efficiency. The second alpha was improved conversion of platform service value into revenue due to non-Lien JAP platform service revenue grow 27.8% beyond the year, outpacing non-Lien JAP 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 grows 6.1 percentage points beyond the year to 46.1%, confirming growth wasn't bought at the expense or profitability. Going ahead we will monitor if connected store output and the platform service revenue conversion remain stable across different markets and 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. Thank you, Mr. Tao. Our next question comes from Alvin from CLSC. Please go ahead. So, thank you for taking my question. So, for the new home business, it is also amazing. So, what does the Q2 new home alpha as the operation upgrade from traditional channel collaboration to integrated marketing and the project service. So what capabilities sustainably create value? And also, in the process, how do you balance growth margins, contribution margin, collection cycles, and development's credit risk?

Thank you, Alvin. Good evening.

So in the first half of this year, the new home market remained under pressure. But in Q2, deal with the improvement with the year-on-year sales declining among top 100 developers narrowing to 9.3 percent. Demand and new supply increasingly concentrated in core cities, high-quality projects, and upgrade-oriented products. So in this backdrop, our Q2 new home GDV grew by 1.2 percent 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 a newly launched project earlier, improving our coverage and performance in market leading projects. And secondly, we have refined needs identification and project matching. We effectively allocated resources to high potential projects, boosting conversion rate. So 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 the buyer's market, consumers face complex choice and multiple choice, and they need more than just access to the project. So I think they need to understand the project's stability, 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. And we are also evolving from the transaction channel to the consumer-centric four-cycle project services. So what we hope is that we want to be consumer-centric. We want to provide four-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. So in this direction, we are also building three capacities. Firstly, we have earlier consumer insights and matching we using we using data from existing form transactions such as interviews we understand the demand on a demanded to aid a project positioning and a marketing reducing the mismatch between developer products and actual demands second we translate a product value into comparable decision metrics, which are 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 the layout analysis, which help consumers intuitively understand their products, improving onsite conversion. Thirdly, we have end-to-end project operating capacities based on customer feedback. Now we link customer analysis, content, and channel sales for our project, and we also have the timely adjustment and resources allocation. For example, for a project in Shanghai, the developer helped to gain a local market knowledge. We reanalyzed target consumers. We adjusted the feedback from the market and we adjusted the sales strategy and the link channel acquisition with all size conversion boosting the sales efficiency. But I think that 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. And I think we need a sustainable validation and we can have better replication as we expand 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. So 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.

Thank you. The next question comes from Griffin from CITIC. My question is on home renovation and carefree. So our future home renovation revenue decline is faster year to year, but contribution margins improved significantly? What drove this decline? And are earlier adjustments largely complete? When will revenue recover it? And how do you balance scale, contribution margins, and delivery quality? Carefree rent profitability or margin significantly improves? and how do we ensure the sustainability? Thank you, Corison, for your question. The industry is undergoing a profound supply-demand restructuring as property adjustments feed into renovation. New home deliveries have dropped. The 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. So the Q2 revenue decline stems from two factors. First, 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 waste on the home renovation business, while competitors use price cuts and high channel incentives to fight for existing home customers. So this proactive adjustment is now largely complete. We expect no further fraud-based contractions this year. Despite pressured revenue, contribution margins improved significantly. Centralized procurement and supply chain optimization meaningfully lowered the material costs. Service provider productivity per store also improved year-over-year. Also, store costs were optimized, indicating healthier retained capacity and cost structure. Regarding revenue recovery, the contract value is a leading indicator. While reported revenue lags due to construction cycles. Possibly front-end metrics like July showroom visits improved quarter-over-quarter due to restored internal cooperation 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 and also enhance the user experience product competitiveness which will be achieved through tailored renovation packages as well as an integrated showrooms at transaction centers. We are pursuing quality products and healthy probability as three pillars, a growth strategy that will drive our deep growth in revenue and profit. On carefree rent, so the units under management gradually grow steadily to less than 790,000, up 34% of your year. Revenue was around 4.83 billion RMB with a 15.3% contribution margin, up 6.9% percentage point every year. The year-over-year revenue decline reflects carefree strength iteration toward a lighter net-based revenue product. Profitability improved due to the structural shift and genuine 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. so this way the costs related to labor and channel you know will grow slower than actual revenue so going forward I think we'll focus on three areas first stabilizing the units under management portfolio to reduce the releasing channel costs as we see more units under management more units are entering renewal or existing homes are going for releases. We're 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 hits 74% up four percentage points and the tenant renewal rate hit 56% up one percentage point a year-over-year. Second, improving efficiency to a lower per unit labor cost. Due to managing units per asset manager rose 40% year-over-year to around 170. Going forward, we will pilot separating transition tasks such as sourcing and leaving from management tasks such as renewal and post lease to boost specialization and 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 will increase asset light products to withstand rental fluctuation. Additionally, tailored to different cities, we're going to adopt a differentiated product solution that will achieve healthier unit economics. Most importantly, service quality underpins all of these improvements. So whether tenants or owner decides to renew, I mean, hinges on the reputation, repurchase, and also the channel costs. So we're going to pay special attention to reputation and lower channel costs. So we believe profitability is only sustainable when service experience renewal and efficiency forms a positive cycle. So we're solidifying this foundation to translate our scale growth directly 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 Baker'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.