---
title: "BEKE (Trans): Neutral on 2026 property mkt; pivoting from scale to efficiency"
type: "Topics"
locale: "en"
url: "https://longbridge.com/en/topics/39290961.md"
description: "Below is Dolphin Research's Trans of $KE(BEKE.US) FY2025 earnings call.For our earnings analysis, see 'BEKE: Selloff Looks Bottomless — Can Policy Backstop It?'.1) Key takeaways recap — Shareholder returns: FY2025 buybacks of approx. $921 mn (+29% YoY).Final cash dividend of approx. $300 mn; total shareholder returns of approx. $1.22 bn (+9% YoY), about 170% of Non-GAAP net profit.Since the repurchase program began in Sept 2022, cumulative buybacks have reached approx. $2.5 bn..."
datetime: "2026-03-16T16:06:45.000Z"
locales:
  - [en](https://longbridge.com/en/topics/39290961.md)
  - [zh-CN](https://longbridge.com/zh-CN/topics/39290961.md)
  - [zh-HK](https://longbridge.com/zh-HK/topics/39290961.md)
author: "[Dolphin Research](https://longbridge.com/en/news/dolphin.md)"
---

> Supported Languages: [简体中文](https://longbridge.com/zh-CN/topics/39290961.md) | [繁體中文](https://longbridge.com/zh-HK/topics/39290961.md)


# BEKE (Trans): Neutral on 2026 property mkt; pivoting from scale to efficiency

**Below is Dolphin Research's**$KE(BEKE.US) **FY2025 earnings call Trans. For our results take, see '**[**BEKE: Selloff 'bottomless' — can policy backstop it?**](https://longbridge.com/zh-CN/topics/39290421)**'**

**I. Key takeaways from the results**

1\. **Shareholder returns**: FY2025 buybacks of about $921 mn (+29% YoY) and a final cash dividend of approx. $300 mn. Total shareholder return was about $1.22 bn (+9% YoY), or ~170% of non-GAAP net income. Since the Sep 2022 program launch, cumulative buybacks reached about $2.5 bn, roughly 12.6% of shares outstanding.

2\. **Q4 results**: GTV of RMB 724.1 bn (-36.7% YoY), revenue of RMB 22.2 bn (-28.7% YoY), and GPM of 21.4% (-1.6 pp YoY). GAAP NP was RMB 823 mn (-85.7% YoY) and non-GAAP NP was RMB 570 mn (-61.5% YoY), impacted by one-off cost optimization charges.

3\. **Cost structure optimization**: Store labor costs in existing-home brokerage fell QoQ for four straight quarters. New-home variable cost ratio and fixed personnel expenses declined YoY, lifting FY contribution margin by 0.2 pp YoY. Home renovation losses narrowed materially, and the rental biz. achieved operating profitability for the year. FY operating expense ratio fell 1.4 pp YoY.

4\. **Liquidity**: Total cash liquidity (incl. customer deposits) was about RMB 68.7 bn; Q4 operating cash inflow was RMB 1.9 bn. New-home AR days were 44 in Q4, improving by about 10 days QoQ.

**5\. 2026 outlook: Neutral on the market; will balance efficiency and growth while continuing to improve revenue quality and capital efficiency.**

**II. Earnings call details**

**2.1 Management highlights**

1\. **Strategic shift: from scale-led to efficiency-led**

a. In 2025, pivoting from sales-driven to efficiency-driven growth, optimizing business model, tech enablement, and cost structure. b. Growth will rely less on store and agent count and more on efficiency and value creation.

c. Four priorities: upgrade transaction services into full-funnel decision support; use AI to optimize resource allocation; embed AI into service workflows; and build diversified housing-service capabilities.

2\. **More diversified revenue mix**

a. Non-transaction revenue reached a record 41% of total. b. Lianjia GTV was 67.6% of total GTV, with focus on markets with stronger structural upside.

c. Platform-connected brands contributed ~63% of existing-home GTV, increasing the share of asset-light models. d. Platform service revenue was broadly stable, underscoring model resilience.

3\. **Existing-home brokerage**

a. FY GTV was RMB 2.15 tn; existing-home transaction volume rose over 10% YoY to a record high. b. Transactions via platform-connected stores increased 15% YoY.

c. Year-end platform exceeded 58k connected stores and 445k+ agents, with stable scale. d. Per-agent existing-home transactions for franchisees rose 6% YoY, up from below 2 deals in 2022 to above 3.

e. Lianjia prioritized network and agent mix optimization and deepened core cities, lifting per-capita productivity in core cities. f. Q4 contribution margin was 40.4%, flat YoY and +1.5 pp QoQ.

4\. **New-home business**

a. FY GTV was RMB 890.8 bn, outperforming the market amid volatility. b. Evolving from traditional channel distribution to a capabilities platform: offering online decision support to buyers and early-stage positioning insights plus integrated marketing to developers.

c. Q4 contribution margin was 28.3%, +2.6 pp YoY and +4.2 pp QoQ.

5\. **Home renovation**

a. FY revenue was RMB 15.4 bn (+4.4% YoY); contribution margin 31.4% (+0.7 pp YoY); operating losses narrowed significantly. b. Advancing product standardization and digital design (bundled/modular products plus AI/BIM design flows).

c. About 80% of main materials and 6% of auxiliary materials have completed centralized procurement bidding. d. In 2025, will deliberately moderate expansion, prioritizing repair and validation of the underlying business model.

6\. **Rental (home leasing)**

a. Year-end managed units exceeded 700k, +62% YoY. b. Achieved full-year operating profitability, with contribution margin of 8.6% (+3.6 pp YoY).

c. 'Worry-free rent' iterated toward lighter, lower-risk products, with net revenue recognition accounting for over 30%. d. Property managers' avg. monthly unit acquisition rose 7% YoY; units managed per capita rose 42% YoY.

e. AI is being embedded into signing, pricing, lease management, and operating strategy.

7\. **AI strategy**

a. AI will not replace agents but will reshape division of labor: standardized tasks become highly automated, while complex decisions and trust remain human-led. b. AI is used in auto-generation of marketing assets, simulation training, rental pricing recommendations, and tenant matching.

c. AI will become a co-pilot across the service life cycle, covering need identification, precise matching, pricing, decision support, and process automation.

**2.2 Q&A**

**Q: How are store/agent operating efficiencies trending? If the market recovers this year, can you capture share, and how will you execute the efficiency-led strategy?**

A: **Upgrading from scale-led to efficiency-led is a natural evolution for a platform business.** The core is to upgrade value creation — by delivering more value to customers, we raise community service penetration, resource conversion, and unit output. This is not about cutting capacity or shrinking the business. What truly sets industry capacity is not more agents or stores but higher-quality, more reliable decision support, including better matching, sharper marketing, and comprehensive purchase planning.

We are reallocating from nominal capacity to effective capacity, concentrating organizational resources on solving real customer problems. **In 2025, first, in self-operated businesses we will concentrate resources on high-performing stores and agents to boost efficiency.** We will further flatten management so top operators stay closer to the front line to create value, while institutionalizing best-in-class service capabilities into the platform and division of labor, rather than leaving them with individuals.

Second, **on the platform, we will keep expanding connected stores and agents but with greater emphasis on quality and efficiency.** By end-2025, active connected stores and agents are targeted to grow 21% and 7% YoY, respectively, while optimizing network mix to identify and amplify high-rated stores and agents. In Q4, per-agent productivity improved QoQ; existing-home lead conversion in Beijing and Shanghai rose about 8% QoQ; and per-capita commission income increased 2% QoQ, supported by more platform capabilities including AI tools.

Third, **data and AI are the key drivers,** as we redesign resource allocation, division of labor, and buy-side/sell-side workflows. In many areas, this is a systemic redesign of how the platform operates.

**Q: With new-home developers facing sell-through pressure, lower profitability, and higher SOE concentration, how will your marketing model innovation change developer relationships and sustain performance?**

A: We start from structural industry shifts. **Digital penetration in new homes remains low. Historically, our model followed traditional channel sales — allocating resources around commissions and traffic, using large channel traffic to help core projects sell-through,** which worked in upcycles but is constrained now, serving only specific projects and buyer cohorts and creating limited value for developers, especially buyers.

We think the new-home market is entering a new phase. For buyers, the core is not more information but greater decision certainty. For developers, the core is not just clearing inventory via channels but achieving more predictable sales within a constrained budget.

Thus we are **upgrading from a channel role to a comprehensive capabilities platform. First, strengthen online decision support for new-home transactions,** using stronger data and product capabilities to solve the hardest decision pain points for customers.

**Second, use data and AI to optimize traffic allocation and improve structural matching between projects and potential buyers,** broadening buyer reach, widening the top of the funnel, and ultimately lifting conversion.

**Third, treat developers as long-term clients rather than channel partners only,** providing integrated solutions across product positioning, customer acquisition management, and sales pacing to enhance project efficiency.

Our aim is to evolve new homes from distribution to an efficiency platform between developers and buyers. As capabilities scale, services and revenue streams will diversify, making the model more resilient. We believe this evolution is critical to sustaining long-term competitiveness in new homes.

**Q: What are AI's potential impacts on real estate, and how is BEKE applying AI across businesses? What progress has been made?**

A: The question is not whether AI replaces agents but how it reshapes division of labor, value creation, and organizational design. Housing transactions are not short-cycle standard consumption but long-cycle, multi-step, highly complex decisions — search, decisioning, closing, move-in, operations, and improving the living experience.

AI can markedly raise efficiency or automate many steps, such as information gathering, need matching, process reminders, document generation, preliminary risk checks, and workflow coordination. These are standardized, repeatable, rules-based tasks where AI drives substantial productivity gains.

In rentals, AI is already involved in unit acquisition decisions, rent pricing suggestions, and tenant matching. By analyzing historical transactions, local supply-demand, and unit attributes, it helps operators decide whether to take units, recommends rent ranges, improves leasing efficiency, and strengthens risk detection. This lets systems handle standardized tasks so professionals focus on complex decisions and client service.

Some steps will not be replaced and will matter more with AI. These include probing whether stated needs reflect underlying needs, making dynamic pricing judgments, coordinating buyers, sellers, lenders, title/closing steps, and performance risk, stabilizing expectations and emotions near close, and ultimately bearing responsibility. These rely on judgment, coordination, trust, and accountability — where humans add the most value.

**AI will bifurcate workflows: one side highly automated with rapid efficiency gains, the other centered on expert judgment, accountability, and high-value service.** Traditional information intermediation will matter less, while transaction responsibility and housing-service infrastructure will matter more.

For BEKE, the opportunity grows. We aim not just for AI-driven efficiency but to upgrade into integrated housing-service infrastructure — making matching, processes, and collaboration far more efficient, while making transaction responsibility, performance assurance, and service delivery more reliable.

Consumer needs are hard to fully express, while supply is highly non-standard. Because needs are fuzzy and supply is non-standard, the industry inherently needs humans to interpret, match, coordinate, and ultimately take responsibility. As AI lifts the efficiency baseline, stronger service providers generate outsized marginal value — AI amplifies, not diminishes, top performers, making capability uplift the key growth lever.

**Industry evolution will be driven by four forces: technology (efficiency and capability expansion), professional expertise (judgment and service in complex scenarios), customer trust (enabling closings and long-term relationships), and culture/values (integrating the first three into a scalable, evolving system).** What matters is not merely having AI, but integrating AI, professionals, trust, and culture into a continuously evolving model.

**Q: How do you view content creators and KOLs using new media to drive housing transactions?**

A: When a phenomenon keeps attracting customers, it reflects a real need. Rather than judge good or bad, the better questions are what need it addresses, which customers it resonates with, in which scenarios, and which needs were underserved before.

This reflects a broader shift. **Real estate used to be house-centric, with decisions anchored on the property as the scarce resource.** Now the industry is shifting to people-centric. Each purchase decision reflects real-life considerations — family structure, budget, lifestyle, schooling, commute, risk tolerance, and relocation plans. Buying, renting, or upgrading appears property-driven but often is about how people choose to organize their lives.

From this lens, housing transactions have always been complex decisions, though the industry long treated them as a light-weight matching exercise. As needs become more complex and personalized, decisions are reverting to their essence, requiring understanding, explanation, judgment, and trade-offs.

The rise of content creators and KOLs is not just a channel story. They offer different value — focusing less on the property alone and more on the people behind the decision. Through viewpoints and interpretation, they help customers understand the market, compare options, and reflect on needs, reducing decision costs and anxiety.

For BEKE, this is both a reminder and an opportunity. It reminds us not to position ourselves merely as an information-matching platform but to be truly customer-centric, understanding the people behind each transaction. The opportunity is to combine content, professional service, execution, and trust to build deeper, more durable advantages. KOLs can provide perspective and influence, but in complex transactions, execution, risk management, and delivery ultimately rest on a professional service system.

**Q: Home renovation shows slower revenue growth in 2025 but better margins. How are centralized procurement and standardized delivery progressing, and when is the profitability inflection?**

A: The slower 2025 revenue growth **is a deliberate choice to temper expansion.** Renovation is delivery-intensive; if unit economics are unstable, scaling adds risk. Liquidity issues at some peers in 2025 further validated this pain point. Thus last year we prioritized repairing and validating the underlying business mix.

Results show improving contribution margin and sharply narrower losses, indicating healthier project-level unit economics. At about RMB 15 bn of revenue today, we **break unit economics into three levers: product mix optimization, explicit cost control (materials, labor, delivery efficiency), and implicit cost reduction (rework, after-sales, and reputation loss).**

**In 2025 we focus on explicit costs.** For centralized procurement, about 80% of main materials and 6% of auxiliary materials have completed national or regional tenders, strengthening bargaining power and product quality stability and reducing price volatility risk. We are also improving work-order dispatch, digital design and modular tools, and access/ratings standards to build a high-quality delivery talent pool, materially lifting PM and designer productivity.

On implicit costs, via escrow, performance commitments, and standardized clash detection at the design phase, we reduce rework and delivery variance at the source, improving project-level earnings stability. **Looking to 2026, as unit economics improve and delivery capabilities solidify, we will expand the top of the funnel with discipline.**

The key is not simply more traffic but higher conversion: first, keep refining product portfolios to match customer segments. Second, replicate high-conversion showrooms centered on signing hubs, integrating existing-home transactions with renovation product experiences to create higher-certainty decisions. Third, roll out community-focused operations to more cities, leveraging broker–renovation collaboration in specific areas to raise overall conversion.

As delivery standardization advances and implicit costs fall, rising satisfaction and word-of-mouth will create a positive loop, laying a firmer base for future scale. It will take time to fully show in the P&L. Over the next 2–3 years, we plan to connect design, construction, and operations data via BIM and a modular component library, building productization and gradually shifting renovation from project-based to scalable, industrialized capacity.

**Q: The rental biz. grew fast over the past two years with impressive profitability gains, but reported revenue dipped QoQ due to accounting changes. From a long-term UE standpoint, how do you view the path and headroom?**

A: Two clarifications: scale trajectory and profit structure. **The short-term revenue decline mainly reflects accounting changes as the 'worry-free rent' product moved from gross to net revenue recognition,** under which we recognize only service fees, better reflecting our role as an asset-management service provider. This coincides with a lighter operating model and much lower risk exposure, with no negative impact on cash flow or per-unit profitability.

On fundamentals, **the core operating KPI — managed units — kept expanding strongly.** Managed units exceeded 700k at end-2025, +62% YoY, reflecting stronger product competitiveness and released demand, not accounting noise.

On profit structure, we focus on per-unit improvements. The rental business turned profitable for the full year in 2025, reversing prior operating losses. The improvement is not purely scale-driven.

**Structural profit drivers ahead include: first, labor productivity gains,** especially for property managers, with monthly unit acquisition +7% YoY and units managed per capita +42% YoY in 2025. **Second, lower CAC on better channel efficiency and higher conversion,** plus higher renewal rates from better post-lease service and satisfaction, which reduces new-customer acquisition needs. **Third, product mix upgrades, with a higher share of asset-light management products meaningfully lowering risk-related costs,** and making the model far less sensitive to rent-price volatility.

Overall, this is a business with sustained rapid scale growth, steady per-unit margin gains, and declining operating risk. Long-term UE improvement will be led by product mix upgrades (stability and risk resilience), labor productivity, channel efficiency and lower CAC, and continued scale benefits. Financially, we are shaping rentals into a segment with sustained scale expansion, improving earnings quality, and increasingly stable cash flows.

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