Core Insights - The core viewpoint of the article emphasizes the shift in real estate marketing from traditional traffic-driven methods to AI-driven decision-making, where users actively seek information through AI rather than passively receiving it [2][3] - The introduction of the GEO (Generative Engine Optimization) platform by Deep Intelligence aims to enhance the understanding and recommendation of real estate information by AI, thereby influencing user purchasing decisions [2][3] Group 1: GEO Concept and Misconceptions - The current understanding of GEO is often limited to being a mere "AI version of SEO," with many teams attempting to increase visibility through keyword stuffing and high-frequency postings, which can lead to misinformation and a lack of trust [3][4] - True GEO should focus on "cognitive co-construction" rather than treating it as a traffic game, as AI is not a simple keyword matcher but a sophisticated system that requires authoritative and well-structured content [3][4] Group 2: Six Dimensions of Cognitive Optimization - The essence of GEO in real estate marketing is to build the recognition of new housing projects, ensuring that AI can not only see but also understand and endorse these projects [4][5] - The six core dimensions for establishing project recognition include: - Visibility: Ensuring projects can be retrieved by AI during user inquiries [5] - Authority Penetration: Citing evaluations from third-party professional institutions to enhance credibility [6] - Information Correction: Correcting outdated or erroneous information that AI might reference [7] - Expression Richness: Providing multi-dimensional and detailed descriptions of projects [8] - Positive Conversion: Highlighting strengths while downplaying weaknesses to foster a positive perception [9] - Ranking Elevation: Prioritizing projects that better meet user needs in recommendations [10] Group 3: Core Competencies and Results - The competitive edge of the "Geek Inquiry" platform stems from three synergistic dimensions: large-scale user intent simulation, authoritative source construction, and AI semantic structured output [12][13] - A case study showed that after five days of optimization, a project in Chengdu saw a 400% increase in recommendation frequency, with authoritative source citation rates rising from 14.7% to 52.9%, and improved user confidence in purchasing decisions [12][14] Group 4: Dual-Driven Model - The successful implementation of GEO relies on a dual-driven model combining "Good House Review Network" and "Geek Inquiry," which provides a professional content foundation and a systematic cognitive optimization path [14][15] - The platform utilizes a comprehensive database and professional research system to deliver structured, verifiable real estate information that can be directly referenced by AI [14][15] Group 5: Long-term Strategy and Future Outlook - GEO optimization is viewed as a long-term project rather than a one-time marketing effort, requiring continuous iteration to build a sustainable competitive advantage [19][20] - As AI technology evolves, early adopters of GEO will accumulate data advantages and optimization experiences, creating barriers that are difficult for competitors to overcome [19][20] - The article concludes that the future of real estate marketing will be defined by cognitive competition, with GEO technology enabling precise targeting of high-value customer segments [20]

1月30日，在"智联地产·深度实战"房地产AI应用工作坊暨新春体验日上，深度智联首次集中展示了其 GEO泛地产认知优化在 13个首批试点楼盘 中的实战成效，并获得一线房企操盘手与营销负责人的 一致认可。 截至目前， "极客问道"已在上海、北京、广州、成都等全国9个核心城市实现落地；预计春节前将扩 展至22个城市，预计为上千个楼盘提供认知优化服务 ，展现出强劲的市场渗透力与行业接受度。 此 举标志着深度智联泛地产行业GEO认知优化解决方案，正式从试点验证迈向全国规模化落地。 从"流量游戏"到"认知共建"： 重新定义泛地产GEO 在传统营销思维中，不少 GEO实践仍停留在"可见性"层面——通过高频发稿、堆砌关键词、制造提 及量等方式，试图让项目名称出现在AI的回答中。这类做法虽短期见效，却极易导致信息失真、价 值模糊、转化断层，本质上仍是将GEO视为一场"流量游戏"。 ■ "AI不是搜索引擎，大模型正在变得越来越聪明。"深度智联GEO泛地产认知优化主理人方欢指出， 冲量刷榜式的操作很快会被AI识别并纠偏。真正的GEO，必须从"内容供给"转向"认知共建"。 "极客问道"不试图操控AI，而是成为AI愿意引用的权威事实 ...

乐居财经 当AI成为购房入口，GEO正在改写营销逻辑 原创 阅读全文 分享一篇文章。 ...

2026年第4周 Weekly 2026年1月26日-2026年2月1日（第4周），土地供应规模延续低位，成交量环比大幅上涨，溢价率也迎来回升。本周重点城市监测范围内，土地供应建筑 面积258万平方米，环比下降19%；成交建筑面积394万平方米，环比增长106%。重点城市平均溢价率3.2%，环比增加2.5个百分点，主因杭州、湖州等地 部分优质宅地高溢价成交，拉高了平均溢价率。 供应：本周土地供应建筑面积258万平方米，环比下降19%。 一线城市没有新增供应宅地，本周重点城市供应宅地平均容积率仅为1.8，无锡、西安、天津平 均容积率均在1.7以下。 本周挂牌宅地中，出让底价最高的地块来自宁波鄞州，江东板块宅地出让底价29.16亿元，容积率2.75，综合起拍楼板价约9700元/平方米。共分为4宗子地 块，其中3号、4号地块为商品住宅用地，可售商品住宅体量约10万平方米，1号、4号为回迁房用地，计容建面近20万平方米。地块计划建设安置房共2272 套，回购价格均为15400元/平方米，配套建设非人防车位1667个，回购价格为5万元/个。作为浙江省首批未来社区试点创建项目，白鹤未来社区旨在成为"全 国都市宜居社区典范 ...

2026年第4周（1.26-2.1），本周房地产领域中央层面的动向有两方面值得重点关注： 一是监管端出现边际调整， 部分出险房企不再被监管部门要求每 月上报"三条红线"指标； 二是发展产业联动房地产去库存， 本周出台的支持养老产业发展的相关措施、培育服务消费新增长点的工作方案，均提及通过 发展相关产业助力房地产行业去库存。 地方层面， 优化公积金成为本周地方发力重点， 共有8地出台了相关稳市场政策，典型如天津将公积金贷款额度上限从120万元提升至144万元，多孩家 庭首套房可获得最高贷款额度。 多地积极落实中央下调商业用房首付的政策， 将商业用房购房贷款最低首付款比例下调至30%，吉林、山东、甘肃、西 藏等省份均明确发文落实这一新规。 | 日期 | 部委/省市 | 主要内容 | | --- | --- | --- | | １月 28 日 | 监管部门 | 多家房企:目前已不被监管部门要求每月上报"三条红线"指标 | | １月 28 日 | 三部委 | 深化自然资源要素保障支持养老服务改革发展 | | 1月29日 | 国务院 | 鼓励地方结合消化存量房地产,支持旅居项目用地和服务设施建设 | | 1月26日 | ...

Core Viewpoint - The central government continues to strengthen financial support for the real estate sector and accelerates urban renewal efforts [2][3] Policy Environment - In January 2026, multiple central departments collaborated to clarify the development framework, with over 40 provinces and cities implementing detailed measures, creating a "central decision, local precise policy" linkage [3] - The policy focuses on four main areas: urban renewal, housing security, "good housing" construction, and financing optimization [3] - The Ministry of Natural Resources and the Ministry of Housing and Urban-Rural Development jointly issued documents to support urban renewal, encouraging the use of existing land and property resources [3] - The People's Bank of China implemented a moderately loose monetary policy, reducing the re-lending rate by 0.25 percentage points to 1.25% and lowering the minimum down payment ratio for commercial properties to 30% [3] - Tax incentives for residents purchasing new homes have been extended until the end of 2027, covering various tax types [3] New Home Transactions - In January 2026, the transaction area of new residential properties in 50 key cities nationwide was approximately 8.1 million square meters, a month-on-month decrease of 32% and a year-on-year decrease of 20% [8][9] - Among first-tier cities, the transaction area was about 1.32 million square meters, with month-on-month and year-on-year declines of 36% and 28%, respectively [9][11] Second-Hand Housing Transactions - In January 2026, the transaction area of second-hand houses in 13 key cities was approximately 8.1 million square meters, with a month-on-month increase of 16% and a year-on-year increase of 33% [14][17] - Chengdu led with a transaction area of 2.18 million square meters, showing a month-on-month growth of 18% and a year-on-year surge of 63% [17][18] Land Transactions - In January 2026, land transaction areas and amounts both fell by 90% month-on-month, with year-on-year declines of 48% and 59%, respectively [21] - The supply of land was 33.6 million square meters, an 8% year-on-year decrease [21] - The market heat remained low, with many land parcels sold at base prices, indicating a lack of competitive bidding [24][25]

深度智联"地产AI先锋"招募计划由此应运而生，与传统招聘的"人员扩充"逻辑有着本质区别，这是一场立足AI时代新型业务场景的生态协作邀约。 "你不 是客户，而是共建者；你不是使用者，而是共创者"！深度智联致力于在行业中寻找志同道合的伙伴，构建由正式员工、渠道伙伴、生态伙伴组成的精英 组织体系。入选者将直接参与深度智联核心产品迭代和市场拓展，并获得依托平台的强大支撑和专业背书，在真实业务实战中反哺AI模型优化，形成"用 即共创、推即共建、赢即共赢"的生态闭环，助力每一位行业精英在AI时代找到价值跃升的清晰路径，实现个人与行业的同频进化。 深度智联"地产AI先锋"招募计划诚意寻找 GEO泛地产认知优化师、数字员工推荐官、OPC人机协同研究员三类地产行业"新 物种"，为不同类型的行业 人才提供适配的发展路径。 GEO泛地产认知优化师 ： AI时代认知架构者 随着AI成为房产消费决策的核心信息入口，"被AI信任并正确推荐"已成为地产营销竞争的新战场，传统SEO模式已难以适配新时代需求。当前GEO备受 关注，但对应楼盘项目的复杂性、用户购房咨询行为的多维逻辑尚未给出令人满意的解决方案。 2026年1月30日， 深度智联正 ...

2026年1月30日，深度智联成功举办 " 智联地产・深度实战"房地产AI应用工作坊暨新春体验日 。近百位来 自全国的房企操盘手、投拓专家、渠道负责人及内容创作者齐聚一堂，通过产品体验、分组实战、成果展 示等多元形式，沉浸式体验AI在营销获客、投资决策、认知优化、组织提效等全业务链条的落地价值，共 同验证深度智联AI产品从技术发布迈向上岗实战的关键一步。 这不是一场概念演示，而是深度智联在去年年底全系列产品上线后，在真实业务场景下的工作能力验 收。后续，度智联还将把此类生成式AI实战型工作坊向全国推广，让更多地产专业人士结合一线需 求开展实操演练和效果检验。 本次活动平行组织四大主题AI生成式工作坊，邀请行业同仁亲身参与实战，共同检验GEO认知优化 成果，切实印证"金牌案场"、"决策专家"、"私域主编"三大数字员工战队，在楼盘案场运营、投研决 策支撑、内容创作传播等工作场景中的增效价值。同时，深度智联将系统收集参与者的体验反馈与问 题建议，以支持产品完善及后续迭代，为行业提供更贴合业务实际、更具落地性的AI应用解决方 案。 工作坊实战 1 GEO认知优化——构建AI可信知识图谱，让好房子被看见 工作坊实战 3 ...

导 读 1、土地成交规模处于季节性低位 2、百强门槛均较同期下滑 3、投资TOP100拿地金额同比降幅近五成 4、供地"窗口期"开启后土拍热度有望回升 | | 金地集团 | | | --- | --- | --- | | 12 | 保利发展 | 22.7 | | 14 | 龙湖集团 | 20. 4 | | 15 | 青铁置业 | 20. 3 20 | | 16 | 和润达开发建设 | 18.9 | | 17 | 四川城更 | 18.5 | | 18 22 11 | 浙江博策 | 17.520 | | 19 | 如东新天顺 | 16.9 | | 19 | 扬州城建 | 16.9 | | 219 | 滨海城更 | 16 3 | | 22 | 汇龙地产 | 15.4 | | 23 | 宜兴经开投资 | 15.3 | | -74 | 湖南大雷投资 | 15 7 | | 25 | 阜宁城建 | 14.7 | | 26 | 元垄地产 | 14.6 | | -27 | 锦诚汇龙房地产 | 14.1 | | 28 | 金洲房地产 | 13.2 | | 29 | 如东荣能实业 | 12.8 | | CF30 | 信阳国信发展 ...

Core Viewpoint - The second-hand housing market in core cities has shown signs of recovery, with the top 100 real estate companies achieving a sales turnover of 165.45 billion yuan in January 2026, indicating a positive trend in the market [1][16][17]. Group 1: Sales Performance - The top 100 real estate companies achieved a sales turnover of 165.45 billion yuan in January 2026, which is a significant performance indicator for the industry [16][17]. - Among the top 100 companies, 32 reported year-on-year growth in sales, with 10 companies experiencing growth rates exceeding 100% [26][27]. - Notably, companies like Junyi Holdings and Bontai Group saw substantial increases in sales, attributed to strategic investments made since 2021 [28][29]. Group 2: Market Trends - The new housing market is experiencing a slowdown, while the second-hand housing market is showing signs of recovery, with a 16% month-on-month increase in transaction volume for second-hand homes in key cities [31][32]. - The central government has introduced various supportive policies aimed at revitalizing the real estate market, including financial support measures and tax incentives, which are expected to stimulate demand, particularly in the second-hand housing sector [33]. Group 3: Company Rankings - In January 2026, the top companies by sales included Poly Development (15.6 billion yuan), China Overseas Property (14.48 billion yuan), and China Resources Land (11.65 billion yuan) [8]. - Seven new companies entered the top 100 list, with CITIC City Development making a notable entry into the top 30 [23][24]. Group 4: Policy Impact - The government has focused on urban renewal and financing optimization, which are expected to enhance the market's stability and encourage investment in real estate [33]. - The central bank's monetary policy adjustments, including a reduction in the re-lending rate and changes to down payment requirements for commercial properties, are designed to alleviate financial pressures on real estate companies [33].