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要做房产交易的Uber,Opendoor再获3.25亿美元融资

在线房屋买卖平台Opendoor获新一轮3.25亿美元融资,投后估值达到20亿美元。此轮融资由General Atlantic、Access Technology Ventures和Lennar Corporation共同领投,现有投资者Norwest Venture Partners、Lakestar、GGV Capital,NEA和Khosla Ventures跟投。

此轮融资主要用于其业务扩张、团队建设以及“Trade Up”换购业务的推行。迄今为止,Opendoor已经完成了6.45亿美元的股权融资和15亿美元的债权融资。

Opendoor于2014年创立于旧金山,创始人Eric Wu为美籍华人,曾创立公寓搜索网站Rent Advisor和房屋数据分析网站Movity.com,先后分别被Apartment List和Trulia.com收购。2014年和出身PayPal的Keith Rabois共同创立了Opendoor。

Opendoor可以简化房屋交易中繁琐的步骤和流程。现在房屋出售者只需要在Opendoor上提交地址,平台会通过定价模型和算法技术,在几分钟内生成报价。如果卖方接受报价,Opendoor会直接买下房屋并进行一定的修整,以提高售价。不过目前仍依赖质检员上门检查房屋受损是否虚报,来确认最终报价。

平台会向卖家收取占出售价格7%-8%的佣金,比传统的房地中介高大约2%。但因为卖家可以快速脱手房产,降低持有的风险和成本,许多卖家还是可以接受这个佣金比例。

另外,Opendoor通过使用智能密码锁和监控设备,让买家在任何时间都可以自己独立看房,省去了联系经纪人约定时间的中间环节,大大节省了买家的时间成本。下一步Opendoor想要为客户提供“Trade Up”换购服务,即用现有住所换一个新住所。

Opendoor的理论是,希望通过将时间和能源成本降为零,有效地建立一个技术驱动的业务模式,就像Uber和Airbnb一样,通过移动设备就能实现即时交易。

Eric Wu表示:“购买或出售房屋是消费者可能是消费者一生中最大的单笔交易之一,尤其是在市区,房屋价格可达到100万美元以上,所以对消费者来说,通过按几个按钮就能完成数十万美元的交易仍然是一个难以跨越的障碍。想要说服客户,必须与他们建立足够的信任,让他们意识到整个过程都是透明化的,是数据驱动的。

目前Opendoor平台拥有超过5万个可售房屋,服务客户超2万个,服务范围覆盖全美10个城市,并计划在2020年底扩大到50个城市。团队目前共650人,预计到明年底增加一倍以上。

高额的购房成本是Opendoor目前面临的问题之一,公司每年以超过25亿美元的价格购买房产,导致公司始终处于负债状态。

Opendoor不是“购买后再出售”这个模式下的唯一玩家。今年四月,在线房地产数据库上市公司Zillow宣布正式进军买卖房产交易市场,首先在凤凰城和拉斯维加斯进行试点。同Opendoor的商业模式类似,当地的房产卖家可以使用Zillow的平台来比较潜在买家和Zillow的出价。当Zillow购买了一处房产后,对其进行翻修,然后快速转手。这一消息最初导致Zillow的股票大跌,股民担忧其购买房屋造成的巨大成本,以及它可能使该公司与其平台上的房地产经纪人发生直接冲突。

除了Zillow外,初创公司OfferPad和Knock等也是Opendoor的竞争对手。Offerpad迄今为止完成了总额4.1亿美金的融资,Knock也在去年1月完成了3200万美元的A轮融资。在如此重资产的业务模式下,好像又是一场烧钱大战。未来谁能缩减成本提升盈利能力,以及不断优化算法和定价模型,实现交易流程完全自动化将是这场大战中的关键。

Investors are placing another huge bet on a startup looking to reinvent a decades-old process into something that’s near instant, this time pouring $325 million into Opendoor — a company that wants to bring the complex operation of buying or selling a home down to something similarly as simple as hailing a Lyft.

The idea of Opendoor  is one not so dissimilar from a consumer theory that’s blossomed into companies worth tens of billions of dollars — consumers hate complex processes and are willing to hand off those processes to technology companies if they can make it even a little simpler. Home-buying and selling can be one of the more intense ones, requiring a lot of moving pieces and coordinating multiple time tables and schedules. Opendoor’s theory is that it can create a sizable business by dropping that time and energy cost to zero and effectively create a new technology-powered business model in the process, just like Uber or Airbnb.

Opendoor says it hopes to expand to 50 markets by the end of 2020 with this additional financing. It is in 10 markets right now, and also says it now purchases more than $2.5 billion in homes on an annual run rate. The company says it has raised a $325 million financing round co-led by General Atlantic, Access Technology Ventures and Lennar Corporation. Andreessen Horowitz, Coatue Management, 10100 Fund and Invitation Homes also participated, as well as existing investors Norwest Venture Partners, Lakestar, GGV Capital, NEA and Khosla Ventures. Opendoor has in total raised $645 million in equity and $1.5 billion in debt.

“What I realized was that there’s a lot of tailwinds with people wanting to transact with their mobile device,” CEO Eric Wu said. “We see this with Uber and Lyft and Amazon. I believe the future of real estate will be on demand and that’s the centerpiece of Opendoor’s thesis, making the transaction real time and instant. I realized there were going to be tailwinds, and that real estate was in need of being transformed.”

Opendoor has also sought to expand its efforts to make viewing those homes just as seamless. The company enables potential customers to check out a home by opening it with the app seven days a week. Wu said that most potential buyers go to the house each of the seven days up to the transaction, and then seven days after the transaction happens. Given that it’s such a significant step for any home owner, it makes sense that a lot of planning and consideration would go into the process. The next step is to create a sort of trade-up system, where Opendoor works to create a streamlined way to turn around an existing home for a new home.

Still, buying (or selling) a home is one of the single-largest transactions a consumer can do — especially if they are in a major metropolitan area where houses can quickly hit the $1 million-plus range. So it’s still a hurdle to convince consumers that they should press a few buttons to make a transaction in the hundreds of thousands of dollars. Wu said that the challenge there was to build enough trust with customers that they realize the process should be as seamless and powered by transparent data.

“It’s something we faced early on when we launched the service,” Wu said. “We were asking sellers to sell their home online to a tech company. A lot of the things we’ve done — such as lowering the fees and being transparent about pricing — which helped us build trust. Since it’s one of the largest financial transactions anyone makes, we had to build a world-class pricing model, be transparent about how we got to the quote, make it a low-fee service, and provide a certainty around the process.”

To try to do all this, Opendoor says it’s built a robust data set that will help best model potential prices for homes and be more transparent about that information. Wu said Opendoor currently employs around 650 people and hopes to double that by the end of next year, and the company is investing a significant amount of capital in growing out its data science team. The challenge is to understand the dynamics of the housing market — and any potential chaos — in order to best assess how to buy and sell those homes. Opendoor acquires some risk by purchasing some homes and holding them for a period of time, so ensuring that the company knows how the market performs will be one of its biggest challenges.

Opendoor is certainly not the only player in this area, as some competitors like Knock and OfferPad are starting to raise additional capital. Knock picked up $32 million in January last year with a similar bet: simplify the home-buying process and handle all of the details behind the scenes. If anything, it’s shown that there’s an appetite among the venture community (especially one where the numbers just keep getting bigger) for models that look to tap the same consumer demand of simplifying overly complex processes to just a few inputs on a smart app powered by data science.


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