How ATTOM is Powering Real Estate Innovation
A deep look into how real estate companies are utilizing ATTOM to revolutionize the housing market.
Table of Contents
Introduction
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This real estate portal is a top disruptor in the housing industry, known as an iBuyer and purchasing homes directly from homeowners. 5
This company was formed when hedge-fund thinking collided with the often- inefficient single family real estate market in the wake of the Great Recession. 9
A look into how property data is powering one of the longest real estate portals in the country. 12
Discover a company utilizing ATTOM’s AVM to fuel its AI-driven engine, matching buyers with Realtors.
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This real estate portal is leveraging market trend data to gain a competitive edge in the buy and rent marketplace. 16
Insight into how this company addressed the systemic lead conversion problem in the real estate industry by “deciding with data”.
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This real estate disrupter is disrupting future housing inventory by predicting transactions before they happen. 22
This real estate data platform partnered with ATTOM to power their real estate data AI technology. 25
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INTRODUCTION
Real estate professionals, from real estate agents to the owners of transactional marketplaces, now use ATTOM to make high-impact decisions and gain the advantage against their biggest competitors. In recent years, many industries within the real estate sector have accelerated growth by partnering with ATTOM for property data and analytics. The need for real time, accurate data on the property market was especially strong following the COVID-19 outbreak, as the industry tried to make sense of abrupt changes to trends within the industry and continue to scale and grow their revenue amongst several new challenges - from COVID-specific housing policies to the impact of mandatory lockdowns on in-person meetings and property viewings. The ever-growing need for greater transparency in real estate has only been intensified in the past year and many real estate companies have relied on ATTOM to build resiliency and strengthen their business amongst the fall-out from COVID-19 and the shake-up within the real estate industry.
ATTOM Data Solutions has become fundamental to the decision- making processes and business strategies of many real estate companies across the U.S. Allowing them to capitalize on new markets, grow profits, maintain a competitive advantage, and revolutionize home selling, insuring, buying, and investing. In the past, real estate professionals, looking to harness the power of property data and analytics, were presented with overwhelming, ever-evolving data sets from a vast range of disconnected sources. Near impossible to draw insights that they could easily and quickly put into action, much of the invaluable data on the market remained untappable. As an early disruptor, ATTOM was one of the firsts to provide a crucial deep dive into the property market. Blending comprehensive property tax, deed, mortgage, foreclosure, environmental risk, natural hazard, and neighborhood data for over 155 million U.S. residential and commercial properties, real estate companies from across the industry were quick to catch on to the disruptive power of the real- time insights ATTOM provided.
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Real Estate platforms have used our extensive market trend data, providing transparent insights into foreclosure activity, historical home appreciation, and more, to strategically assess the best markets to launch in. In one use case, ATTOM was leveraged to challenge the traditional buy-or-rent paradigm in three Midwestern markets, strategically chosen due to their stability. In comparison, real estate brokers are continually up against new competition, as an industry known for its low barriers to entry and the rising influx of new talent each year. With ATTOM’S Building Permit Data, brokers are now gaining key insights into property developments in their target markets; accelerating business growth with highly accurate property evaluations and the capability to effectively target lucrative prospective home sellers in their lead- generation endavors. In another use case, ATTOM’s property and neighborhood data was used to offer consumers self-service access to information on properties and neighborhoods that would have at one time only been accessible by real estate agents. In this white paper, we dive into ATTOM’s impact on the real estate industry in more detail. Throughout the following pages, we provide an in-depth look at practical applications of ATTOM’s custom data solutions within different segments of the real estate industry - exploring its transformative impact.
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REAL ESTATE PORTAL
Top Real Estate Disrupters: Offerpad Disrupting the Disrupter
Zillow bought its first home in May.
The online real estate giant’s plain-vanilla purchase of a four-bedroom, three-bathroom home in Chandler, Arizona, for $410,000 is bursting with symbolism for the one-time real estate disrupter, itself now reacting to a new wave of disruption in the real estate industry.
The rapid ascent of so-called iBuyers over the past five years has forced Zillow to pivot from a core value its CEO proudly adhered to as recently as three years go.
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“We sell ads, not houses,” said CEO Spencer Rascoff in the company’s Q1 2015 earnings call. But in his prepared statement for the company’s Q1 2018 earnings call, Rascoff spends seven paragraphs on how the company plans to start buying and selling houses with its version of the iBuyer business model, dubbed Instant Offers. “We purchase the home, do all the work a seller would do, and put it back on the market in short order, in partnership with agents and brokers,” he says of the Instant Offers initiative. Rascoff also provides an example of how the company could conceivably generate $1 billion in profit from Instant Offers. “Given the enormity of the U.S. residential real estate market, the potential total addressable market for providing homesellers with a service such as this is significant. There are 5.5 million annual home sales at $1.8 trillion in annual sale volume,” reads the Rascoff statement. “It’s too early to estimate how many sellers might choose to sell in this way or what our typical net profit per transaction might be, but as an example, if 5 percent of sellers select this method, that is 275,000 transactions. For illustrative purposes at scale, using $250,000 as the typical home value, a $3,500 net profit per transaction would result in a nearly $1 billion profit opportunity annually.” That $3,500 net profit may be a bit ambitious based on Zillow’s first home purchase, which is now listed for sale with an asking price of $425,000 — just $15,000 above the purchase price. A listing commission of just 3.5 percent would alone wipe out any profits, not to mention any needed renovation costs and carrying costs such as property taxes. But it’s the bigger picture represented by the $1.8 trillion in annual home transaction volume attracting disruptive business models to real estate along with the capital funding those real estate disrupters. Total funding to real estate tech startups in 2017 was $12.6 billion in 347 deals — up 200 percent from $4.2 billion in 2016, according to RE:Tech, real estate tech research marketing agency.
estate industry: iBuyers, discount brokerages, predictive listing models, and off-MLS marketplaces. Although each real estate disrupter is targeting a different niche of the marketplace, the common theme among all four companies is the heavy use of data and technology to fuel the disruption.
Real Estate Disrupters: Defining a New Industry
While the iBuyer model may be new for Zillow this year, it’s a disruptive business model that has already proven to have some staying power thanks to pioneers like Offerpad, which started purchasing homes directly from homeowners in the Phoenix area as early as June 2015, according to Cortney Read, director of communications and outreach for the company.
“As we are defining a new industry, there are a lot of competitors coming in,” she said, noting that each of the companies under the iBuyer umbrella are offering a different flavor of products and services to the real estate marketplace. “It really only validates that consumers want this.” The success of Offerpad has attracted venture capital, with a total of $410 million raised so far, according to Crunchbase. Its biggest round of funding was a $230 million deal in 2017, landing Offerpad as No. 3 among notable funding deals ranked by RE:Tech for the year. While Zillow has purchased one home so far, Offerpad and fellow iBuyer pioneer Opendoor — which launched in 2013 — have purchased nearly 10,000 homes combined over the past five years, according to an ATTOM Data Solutions analysis of public record data.
This is the first in a series of articles highlighting four real estate disrupters that each represent four distinct business models threatening to bring about massive change to the traditional real
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The number of purchases by these two pioneering real estate disrupters has grown exponentially each year, up 112 percent in 2016 and up 133 percent in 2017, and is on pace to nearly triple in 2018, according to the ATTOM analysis. The average purchase price for homes acquired by Opendoor and Offerpad over the past five years was $230,307, a significantly lower price point than the charter Zillow home purchase, and translating into roughly $2.3 billion in transaction volume. It’s important to note that the $2.3 billion represents less than one- half of the transaction dollar volume that the two companies are participating in given that the iBuyer model involves reselling homes purchased within a relatively short period of time — and at a higher price point. Offerpad’s Read estimated that her company alone is involved in $130 million in real estate transactions per month, a run rate of more than $1.5 billion for the year.
uses data to fuel its business model,” he said. “If an organization is only in one market, they only have one market to consider when making decisions. We’re currently in eight markets — eight markets that each have their own trends. The market trends can be identified with the help of data and it’s how we stay ahead of market.”
In addition to informing market trends, data also helps inform decisions Offerpad makes at the property level, according to Mayes.
“Offerpad receives data from many sources, and most importantly knows how to use when buying and selling homes,” he said. “From deep neighborhood data that helps set a benchmark for offers, to providing property characteristics to better help us determine the needs of our buyers.”
“We are doing it at a large scale,” Read said, noting that after launching in Phoenix the company has expanded to eight markets.
ATTOM analyzed homes resold by Offerpad within 12 months of the original purchase date in Phoenix in 2017 and found the median price of those sales was $26,400 above the median price at purchase. That price differential was significantly higher than the potential $15,000 expected with the Zillow resale and leaves more room for a net profit, but Read said that price differential is not the company’s primary source of revenue. “The way that we make money is that we have a fee … that varies on the home (depending on) how soon they are looking to move out of the home,” she said. “We manage all the renovations. We have our team that does that and they are very efficient to get it done and get it buyer-ready to put it back on the market.”
Data-Fueled Real Estate Disrupters The large scale Offerpad has achieved in just a few years has been fueled largely by data, according to Chief Real Estate Technology Officer Dan Mayes.
Read said Offerpad’s business model is disrupting the marketplace by giving control back to sellers.
“While real estate is at the core of our history and brand, Offerpad
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“The number one thing is you’re putting the control back in the seller’s hand,” she said. “Before Offerpad there wasn’t much control they had or certainty over the process.
“A lot of people have actually lost out on their dream house … because they had a contingency of their house selling. There is not really peace of mind until the deal closes and the funds are transferred to their account,” Read explained. “With Offerpad you come to us, give us your property address, upload some pictures and within 24 hours we’ll provide you an offer. … We actually have customers that sell to us and buy Offerpad homes and they are able to do those transactions within a month.”
Mayes said the same data and analytics the company has developed to fuel its business model and customer-facing applications is also helping to fuel investment in the company.
“In addition to using data to provide a tremendous home buying and selling experience, we invest continuously in developing our proprietary technology and enhancing the millions of real estate and economic data points we collect,” he said. “These investments in data and technology help us identify potential market expansion while providing our investors and partners with the insight and the confidence to continue fuel our operations.”
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INSTITUTIONAL INVESTOR
Top Real Estate Disrupters: Roofstock Disrupting Single Family Rentals
Top real estate disrupter Roofstock was formed when hedge-fund thinking collided with the often-inefficient single family real estate market in the wake of the Great Recession.
In 2009 firms like Blackstone, Starwood Capital Group, Colony Financial and American Homes for Rent each began purchasing tens of thousands of single family homes to hold as rentals — lured by discounted foreclosure properties and plummeting homeownership rates that foreshadowed a strong rental market in the years ahead.
Inefficiencies in the real estate marketplace grated against the data-driven culture of many involved in this massive shift in residential real estate ownership, including Roofstock’s Beasley,
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who at the time was CEO of Starwood Waypoint Residential Trust, a firm that at one point managed more than 15,000 U.S. single-family rental properties.
“(Roofstock) was really born out of frustration of trying to sell homes we had a Waypoint,” said Beasley, who co-founded the company along with Gregor Watson in mid-2015. “We found it was very difficult to sell homes with tenants in them because the traditional MLS was really set up to sell vacant homes … It seemed kind of crazy that you had to wait for the tenants to move out … it was costing 10 to 12 percent on average to sell these homes.” Rapid adoption of the Roofstock platform over the past two years is proof that real estate disrupters were needed in the single-family rental (SFR) marketplace, according to Beasley, who said the platform went from $40 million in transactions in 2016 to nearly $1 billion 2017 — a 25-x increase. Roofstock charges sellers 2.5 percent and buyers pay 50 basis points on transactions to use the platforms big-data analytic tools.
Rental Genome Project a Real Estate Disrupter
“One of our projects last year was to complete a property database of all the SFR owners in the country,” Beasley said, noting that the company can now display all 16 million SFR homes in the country on an interactive map that can be used for internal purposes but also productized for clients to “use that data to make ourselves relevant to our clients … we can get inventory that way and sell it for them in a pretty elegant way.” Roofstock’s SFR database — which they have dubbed the “Rental Genome Project” — includes the ownership entity of each property along with ways to contact those owners, a marketing goldmine for the company. “We can use for multiple purposes. … Once you know a little bit about someone, you can target them on Facebook for example,” Beasley said. “It has borne fruit. We have gotten a lot of retail inventory with these targeted Facebook ads.”
Roofstock raised $35 million in Series C funding in 2017, according to an RE:Tech report, which listed that as one of the top 20 notable real estate startup fundraising deals for the year.
“It has been an attractive time to raise money in real estate and fintech,” said Gary Beasley, CEO and co-founder of the online marketplace for buying and selling single-family rental investment property outside of the Multiple Listing Service (MLS). “Lots of capital chasing a relatively few companies.”
Individual property-level data is auto-populated at key points in the Roofstock workflow to help further reduce friction in the process of selling a single family rental, according to Beasley.
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“We have a process where sellers can onboard their properties in a self-service way. … we can use data and AI and machine learning to make people answer as few questions as possible,” he said, adding that the company serves up automated property valuations to help seller decision-making. “We have our own valuation that can predict probability of sale at certain price points.”
Beasley said a data-driven culture at Roofstock has also helped the company attract funding.
“Having a head of data science and a data science strategy is the price of entry for any startup in the valley,” he said. “The fact that we had a strategy that involved data and really understanding our future customer base was very attractive from a business model perspective. “The one thing real estate has going for it is the market size is quite large. That is appealing for investors who see a lot of companies,” he continued. “It is really the last major sector to not be discovered … and I think there are a lot of pockets of opportunity in real estate.”
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REAL ESTATE PORTAL
HomeFinder Launches Off Market Property Search Powered by ATTOM Sometimes less is more. While many home buying real estate portals have become somewhat cluttered, HomeFinder.com has been focused on giving consumers a user-friendly experience to help make their home buying process as pain-free and efficient as possible. ATTOM Data Solutions is helping with that effort. The iconic website, HomeFinder.com has been in the game since 1997 when it was originally called Homescape.com, giving HomeFinder the designation of being the longest surviving real estate portal in the country. The company was purchased by newspaper conglomerate, Classified Ventures, 10 years ago, who used the site to power all their newspapers’ real estate websites.
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In 2017, entrepreneur, Mike Sawtell, purchased HomeFinder from Placester, a real estate marketing company. Over the last 3 years, he and his team have been busy transitioning the popular 20-year-old legacy website to a modern, cloud-hosted, mobile first, web portal featuring extremely fast loading pages. “Our company has been focused on making sure HomeFinder continues to be very relevant as a search portal for all consumers looking for their next home. The latest version of HomeFinder 2.0, which has been rebuilt from the ground up, focuses on ease of use while providing timely, relevant property data that will empower consumers to make sound buying decisions,” said Mike Sawtell, CEO of HomeFinder. In partnering with ATTOM, the CEO said HomeFinder is utilizing additional quality data to give even more information to consumers about a particular neighborhood and home they’re considering. In January of 2020, the company just completed adding 100 million off- market properties to their searchability. HomeFinder has built all new pages for the 100M off-market properties; where most of the data comes directly from ATTOM. The company is also using ATTOM’s automated valuation model (AVM) and a vast set of ATTOM’s property data and local information. Sawtell added that the site offers a simple, modern user interface, a new page layout while being hosted in the cloud. With Progressive Web App (PWA) front end technologies, consumers will enjoy a site that loads very quickly. But most importantly, the CEO takes pride in the fact that the consumer-focused portal is easy to use. “We accentuated the simplicity of use instead of making it complicated,” said Sawtell, HomeFinder has always had the reputation of being a consumer- friendly real estate portal, we still have many more features to add in 2020, but we will always emphasize ease of use and honor the legacy of the HomeFinder brand.”
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ONLINE TRANSASCTIONAL MARKETPLACE
AVM-Driven Property Stories Ending in a Perfect Match for Realtors What is your elevator pitch for SetSchedule? SetSchedule is the technology innovator revolutionizing real estate business development by filling Realtors’ calendars with a targeted stream of real, interested local buyers and sellers, not a list of leads. The multi-patented matching engine leverages AI-powered predictive data, insider market insights and automated marketing software tools to deliver the right opportunities, appointments and valuable insights to close the deal. We turn the pay-per-impression model on its head, into pay-per-action. At the end of the day, we use an AI environment to increase the odds that a real estate agent will close the deal. There is a gap in the lead generation industry on mentorship and training, so we also married those elements into the app.
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How is SetSchedule utilizing real estate data from ATTOM Data Solutions? SetSchedule utilizes ATTOM’s AVM (Automated Valuation Model) as part of our SetValue network for homeowners. This gives homeowners the opportunity to see what their house is estimated to be sold for if they were interested in selling their property. Utilizing ATTOM data allows homeowners to have a better understanding of what their house is worth without having to look at comparable houses, since the system factors that in.
What has been your experience with the property data delivery? Our experience with data delivery has been extremely helpful. By connecting other databases, we are able to provide an aerial viewpoint; that streamlines the search and retrial process. What has been your experience with the property data quality? Our experience with data quality has been really positive because of our versatility. By regularly adjusting our information contribution, our provisional data, and industry tools to meet the need of our clients, we ensure data delivery is up-to-date, simple, efficient, and easy to follow.
We have a team with rich machine learning experience that is able to take the data from ATTOM and create a data-based story around a specific property that we can provide to both buyers and Realtors, while also leveraging that data-based story to properly match and connect buyers and Realtors. How is the real estate marketplace responding to SetSchedule products/ services? The marketplace loves it! They use it as part of their home-shopping search. It makes their experience a more pleasant one in which they can just type in their address and get an estimate on what their house is worth along with additional information on the house. Why did SetSchedule decide to use ATTOM Data Solutions? We wanted to have a comprehensive data company that has a holistic approach to the retail data as well as the professional data. ATTOM data has this approach and offers well-rounded data that marries the retail and professional data in an insightful way. Along with the bulk property data, we can utilize ATTOM-powered RealtyTrac.com to feed potential consumer leads into the app. We hope our RealtyTrac account rep Mitch can retire on our account!
In terms of the AVM provided to us by ATTOM, I think that is the most consistent one we’ve seen in across the industry.
What has been your experience with customer service? Customer engagement at this phase has been minimal, but this aspect is extremely important, as we are constantly finding new avenues to help customers address and prevent concerns.
In terms of the customer service we receive from ATTOM, all I can say is that you guys are rock stars!
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REAL ESTATE PORTAL
Market Trend Data Helps Divvy Challenge the Buy-or-Rent Paradigm
Divvy Homes is challenging the traditional buy-or-rent paradigm in three Midwestern markets with the help of market trend reports from ATTOM Data Solutions.
“Divvy is a fractional homeownership company,” said Adena Hefets, co-founder of the San Francisco-based real estate tech startup that is focused on three markets east of the Mississippi: Memphis, Atlanta and Cleveland.
Neither renting nor owning is the future of the housing market, but “some combination of both,” according to Hefets. “In most single-family rental businesses the landlord is seen as an adversary. We want to be seen as a partner with the renter.” The Divvy Homes model involves buying homes for prospective homeowners who can’t afford or qualify to buy. The company then rents the property back to that prospective homeowner for three years, during which time the renter builds up equity credits that can be used toward buying the home from Divvy at a pre-set price.
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Rooted in a Personal Story Hefets experienced the wealth-building effect of homeownership from an early age. “For me it’s a personal story. My parents were immigrants and came here without any money … The only way we made any money was we invested in rental properties. There is this amazing risk-adjusted return you can get with owning a home … and start to build wealth over time,” she said, adding that many missed out on that wealth- building opportunity in the wake of the Great Recession. “The wealthy saw tremendous wealth gain over the last decade, and the middle class did not. … they were left out of this giant period of economic prosperity for the U.S.”
a couple of markets is really important. … Our goal is not to extend out to a ton of markets right away (but) extend out once you have that playbook.” Fed Up With Status Quo Divvy has purchased more than 100 homes since launching in October 2017, according to Hefets. “That feels really good given how operationally complex this is,” she said. “We’ve had nothing but increasing demand over time. … We’re now gaining enough traction where there’s less of convincing that we’re a real company.” The average purchase price for homes purchased by Divvy Homes over the past year was $131,000, according to an ATTOM Data Solutions analysis of public record data. Homes at that price point continue to be in high demand, Hefets noted. “We buy $100,000 homes in Cleveland, so we’re not really seeing a slowdown,” she said, adding that the company has noticed a bit of a drop-off in cash offers from investors. “A little bit of a slowdown in investing activity. We used to bid against multiple cash offers.”
Although Divvy’s business model may appear markedly different than a traditional SFR operation, Hefets said that the company makes money the same way — at least for now.
“We make money like any other rental platform; we make it off rent yields … we are very selective about the markets we move into to make sure they have enough rent yield,” she said, noting that the company has future plans for additional revenue streams. “If Divvy helps you buy your home, don’t you think Divvy will be a trusted partner for other things? There is a lot of ways to monetize the largest asset for most people. We don’t think the relationship will end when they become a homeowner.” Built on Market Trend Data Divvy carefully chose the markets to launch in based on extensive market trend data from ATTOM, including historical home price appreciation, gross rental yields, property values and equity, foreclosure activity, property characteristics such as year built and neighborhood characteristics such as school quality and crime rates. “We tend to be in more stable markets where it’s easier to predict appreciation,” said Hefets, noting that it was important for the company to launch in a few markets ideal for the company’s business model and build off the success in those markets. “Staying deep within
Divvy’s offering has been highly appealing to consumers, both renters and homeowners, according to Hefets.
“Whether you’re a renter or a homeowner we’re seeing them getting fed up with the status quo,” she said. “People are experiencing a beautiful product that feels different — ‘Wow, there’s actually real companies that are addressing this with technology.’”
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REAL ESTATE DATA PLATFORM
Opcity “Decides with Data” to Solve Lead Conversion Problem In this Q&A, Opcity CEO Ben Rubenstein shares insights into the company’s rocket ride from idea to $210 million exit in less than three years, relying on data-driven leads from ATTOM Data Solutions and adhering to the core value “Decide with Data.”
1. What is the story of how Opcity got started?
I learned a lot from my first startup Yodle. We focused on helping over 55,000 small businesses market online and generate leads to build their companies. We grew Yodle to over 1,500 employees and after our successful exit to Web.com for $342 million, I was ready to tackle many of the same problems we saw in the real estate space.
Real estate didn’t have a lead generation problem. As an industry, we are generating over 100 million online leads a year to only sell 5.5 million homes. What we looked to address is a lead
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2. How is Opcity disrupting the real estate market?
conversion problem. Over 90 percent of all home buyers start their journey online, and the industry simply wasn’t equipped to respond to consumers in a way that helped them move from online to offline. We also saw that many consumers weren’t a good fit for agents that received the leads.
There were so many systemic issues in real estate that had to be addressed simultaneously for our model to work.
1. Opcity turned online leads from loss leader to profit center for thousands of brokerages. Most firms lose money on their online leads, and your average agent sees a -32 percent ROI on online ad spend. We took the risk of investing in buying leads with our own money so we could prove that our lead conversion model worked. We also put our money where our mouth is by having a referral model so brokers and agents only pay for our services on close. That took a lot of faith in our generation-to- close conversion model. 2. Opcity had to do the hardest part of Uber and Match.com at the same time! With the advent of technology, today’s consumer expects a response and results virtually instantly. That’s why we respond to new consumer inquiries in our system on average within 4 seconds. We also connect real, motivated consumers with an agent in real time while on the same phone call. When you call an Uber, you just want to get from point A to point B. In a real estate transaction, the level of money and complexity means you have to have a good relationship with your agent. We had to connect the consumer with an agent instantly, but it had to be the right one, so our team built our agent matching algorithm. This allows us to look at millions of pieces of data about the consumer and the agent to ensure that real-time connection results in a good fit that will lead to a close. This all happens in the span of one phone call. In fact, our agent matching algorithm continues to improve and has increased our own close rate 172 percent in the last 12 months alone. 3. Opcity provides real transparency and accountability for online leads to agents, brokers and the industry by staying focused on the consumer. Consumers want the help of an agent. They need to be responded to on their timeline and placed with an agent that is a good fit for them. Agents no longer want leads, they want real, motivated buyers and sellers. Brokers want more visibility into delivering value to their agents and consumers
Most agents didn’t get into real estate because they are experts at online lead conversion. So we had huge problems to address. Too many leads were being generated for agents who have so many other responsibilities that it’s nearly impossible to effectively work online leads without support. Ultimately the consumer, agent and broker were all suffering as a result. We partnered with a brokerage firm in Austin that had made online lead generation and conversion a core strategy and, leveraging 16 years of data, we applied the most successful conversion strategies to the entire national real estate market. In order to do that we raised a $27M series A, one of the largest in central Texas history, to build the team to take this model to the point we are today with over 400 employees in our Austin-based office. Now we serve 50,000 agents, over 5,000 brokerage firms, process hundreds of thousands of leads every month and will help close 20,000 homes in 2018 after less than three years in business. The team at Move, Inc and Realtor.com saw what we were doing, the significant value we brought to the industry and finalized the acquisition of Opcity in October of 2018.
It’s been a rocket ride, and I am proud of our team for joining me on this mission and accomplishing so much in such a short time.
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with the right support to hold every aspect of the system accountable to the right actions. We are able to meet every one of these expectations and deliver on it daily. By providing the industry a 24/7, 365-day-a-year lead conversion engine we solved a pain point all parties were feeling. The consumer has new expectations in our on-demand, digital world. Brokers and agents have an expectation that their lead generation and technology partners actually prove an ROI. We are excited to meet those expectations and we have proven that we consistently can.
We have an incredibly robust data science and analytics team driven by my Co-Founder, CFO and Head of Analytics, Michael Lam. Our data science and analytics team is nearly as large as our engineering team. Our research team is results oriented and has a bias towards high-iteration testing. We maintain a handful of conversion-focused machine learning models that inform our technology and multiple parts of our process. Across our various models, we utilize techniques such as random forest, Bayesian models, and neural networks. We have the best data sets in the industry and are growing and enhancing those everyday. Through competition between our models we are always driving continuous improvements in performance. That is how we are always getting better at delivering a great consumer experience, making the best matches between consumers and agents, and supporting our agents and brokers through the entire transaction.
5. How is Opcity using leads/services/data from ATTOM to fuel its platform?
3. What data is Opcity leveraging to help fuel its platform?
ATTOM has built a powerful lead generation platform in its consumer- facing property RealtyTrac. RealtyTrac has highly actionable information that homebuyers and investors rely on to make informed decisions about opportunities in the markets they want to purchase in. ATTOM did the incredibly difficult work of combing and normalizing a massively fractured data landscape in the real estate industry. When you have millions of agents, millions of home sales and 40,000 zip codes in the US, it is a nearly herculean task to deliver all of that information in a consumer-friendly and accurate way. ATTOM has data as a core part of its DNA, just like Opcity. ATTOM’s data fuels RealtyTrac and in turn, the leads generated there fuel our business. It’s been a great partnership and we continue to look for ways to leverage more of ATTOM’s robust data sets and analysis.
Opcity leverages massive amounts of data to fuel our business. In fact, one of our core values is that we “Decide with Data”. With our model, we are a partner with our brokers, not a vendor. We win when our brokers and agents win by making money together. That creates a lot of risk for our business, and we mitigate that risk by having an incredible data science and analytics team. Every aspect of our business — lead buying, how our call center operates, our agent matching algorithm, even what we serve in our twice daily employee meals — leverages data. For us, data is not about how much we have, but how actionable it is. Every single improvement in our business is a result of applying data to our practices. In fact, we have been able to make our callers nearly 300 percent more productive in the last year alone through data. Every small improvement we make is driven by data that adds up to big results for our consumers, brokers and agents. 4. How is Opcity using applied analytics and machine learning and any other disruptive technology you want to mention?
6.Why did Opcity choose ATTOM as a vendor/partner?
We put RealtyTrac and ATTOM through a really rigorous lead testing process, as we do for all lead partners. The leads we invest in have to convert into real closings and though we started small, we now capture every possible lead we can from RealtyTrac because the leads
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
work within our ecosystem and result in closings. Ultimately, our vendors are held to an incredibly high standard and ATTOM proved that it can deliver.
7. How is the marketplace responding to Opcity’s offering?
In less than three years, we went from an idea to a $210 million exit. We now have over 5,000 brokerages, 50,000 agents and will do 20,000+ closings this year. We are currently seeing a 3- to 5-x close rate from online leads compared to the industry average. We have also expanded into mortgage and title with thousands of loan officers and title representatives receiving value from those products. We actively pull in leads from hundreds of different funnels and that proves our model can support nearly any quality lead in the marketplace. One of the things we are most proud of is our recent survey of our broker customers who rated us a +20 on our net promoter score (NPS). While a little below Starbucks and Amazon, we ranked higher than Netflix and Modelo Beer. It’s tough to beat beer and movies, and while we are proud, we still have work to do. Most importantly we are consistently rated one of the top large companies to work for in Austin, and were just named a 2018 Top Workplace by the Austin American Statesman. We ask a lot from our team, and they see what we are doing and choose to invest in that success every day. Everyone from the consumer, agent, broker and our team is proving that our idea translated into real results for the industry. I am proud to be a part of that.
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
REAL ESTATE DATA PLATFORM
Top Real Estate Disrupters: Offrs.com Disrupting Future Housing Inventory
This is the third in a four-part series of articles chronicling notable real estate disrupters fueled by property and neighborhood data from ATTOM Data Solutions.
A completely self-funded startup, Offrs.com has not needed to raise capital thanks in large part to the success of its predictive analytic-driven products for real estate agents and others in the industry, according to co-founder Rich Swier.
“It’s been very rapid growth for us over the last few years,” he said noting that since the company launched in 2013 its customer base has grown to more than 10,000 agents accessing its predictive analytics and marketing platform, designed to help those agents identify inventory of homes for sale before those homes are listed or the homeowner even knows they are going to list.
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
“Most of the market today is looking at a transaction-based model,” Swier noted. “In order to predict that transaction you have to have predictive analytics. In order to get to that transaction before others do, you have to have predictive analytics.”
Many real estate agents still fear that discount brokerage models such as Purplebricks and iBuyer models such as Offerpad will eventually push them out of the real estate transaction, according to Swier of Offrs.com
“We have a unique combination of machine learning methods, and we base it on geography,” said Swier, who has a degree in mathematics and built out the technology driving the company’s predictive modeling. “That’s what makes us really special. We score parts of Florida completely different than we do in New York.”
“There’s a natural disruption that’s happening on many levels,” he said. “If real estate agents embrace the data we provide, they can solidify their place in the real estate transaction.”
Democratizing Big Data in the Real Estate Space
Swier claimed that Offrs.com is disruptive not only because of the accuracy of its inventory-predicting model — he said the model accurately predicts 70 percent of all U.S. property listings in advance — but also because the model is made available to the masses of real estate agents at an affordable price point. “We democratize big data,” he said. “Our customers might buy a very small zip code and it might be very affordable to access this valuable data and analytics. … Before it would be very time consuming and costly for them.”
In the simplest terms, Offrs.com predicts future real estate transactions so that agents and others in the industry can identify these transactions further upstream, before they flow into the discount brokerage and iBuyer business models. “It really depends on who comes to the table first,” Swier said, citing a statistic that 70 percent of soon-to-be sellers choose the first real estate agent they meet. “Predictive analytics is the name of the game. If you predict future listings, you’re going to be first in the door. That’s one of the reasons we sell our data exclusively because it’s so powerful that whoever has that data is going to be in a great position.”
Swier also noted that Offrs.com provides marketing assistance for agents to help them put big data into action.
Offrs.com pulls data from more than 25 data providers, including consumer, demographic, financial, and behavioral social media data — all appended to property data.
“We provide templates and campaign systems for them to use,” he said. “You could effectively create a digital postcard on Facebook to the homeowners who score high on our algorithm for very little money.”
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
Although Offrs.com is primarily applying its predictive analytics to disrupt access to future housing inventory on a transaction-by- transaction basis, the model could eventually disrupt real estate housing inventory on a macro basis, according to Swier. “We are predicting the single transaction, and by predicting the single transaction we are also predicting the broader market,” he said. “This will be a living a breathing machine … and that will impact the way people will look at the market.
“The long tail of predictive analytics is this is really going to drive the entire industry,” Swier continued, noting that while predictive analytics is newer to real estate, it’s long been used in other industries. “The entirety of how these hedge funds drive everything based on quants … it’s computers doing the trading … and this is going to spill over into the real estate market.”
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
REAL ESTATE DATA PLATFORM
Predicting Intent in Real Estate with Data-Powered AI
Q&A with Likely.AI CEO and co-founder Brad McDaniel
What is your elevator pitch/30-second sound bite for Likely.AI?
We are an artificial intelligence platform that is specifically designed for the real estate industry.
We’ve built this platform by aggregating data, including public record data from ATTOM on 155 million properties nationwide. We also incorporate a 225-million-record demographic dataset that provides information on buying trends and behavioral trends. We also have accumulated a macro market and micro market data set that is proprietary, made up of both local and national influence signals.
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
We use all this to create different lead-generating products for the real estate industry, the first one being who has the desire to sell. We’ve gotten down to where we’re highly accurate.
When we went out and created our team we really wanted someone with that AI and machine learning expertise … that next level of guy. We got very lucky in finding somebody we had a relationship with and thus being able to go to market very quickly. How is the marketplace responding to Likely.AI products/services, specifically those integrating ATTOM data? We started conceptualizing these types of products as early as 2007, before the now-ubiquitous data science nomenclature even existed. We sat on it until technology and the industry caught up — when industries were willing to incorporate data into their growth strategy. Until that happened, the industry was talking about data like high schoolers talk about sex. Everybody was talking about it but nobody was really doing it. Once we believed market forces had caught up to our vision, we did a soft launch in Q4 2017, providing 10 leads a week per zip code for our beta customers. We got great feedback from this launch. One customer in South Carolina knocked on 10 doors and talked to two people — both wanted to list. A Realtor in Contra Costa County, California got four really solid follow-up leads and one called back with three properties to list from one hour of cold call prospecting.
In essence we score every U.S. property based on the likelihood of a sale in the near future, and once a property reaches a certain confidence threshold in our deep learning models, we say that is a valuable lead for real estate professionals.
How is Likely.AI Data utilizing ATTOM real estate data?
Other companies — list optimizers — look backwards to predict and it’s not a very viable model. It’s something we were doing back in 2007. These list optimizers, some of whom have rebranded as AI companies, use shallow neural networks with limited layers of neurons. Now we use deep learning. Deep learning has very deep neural, long neural networks. All these layers of neurons allow you to make non-linear non-sequential connections between layers. Because of all the different property data that ATTOM Data Solutions has, we started looking at other models we could train and what industries would care about those models — predicting the appearance of a notice of default, or predicting the appearance of a trustee sale. If we can predict that a month or two in advance it is highly valuable for real estate investors. There are a lot models we can create utilizing different pieces of ATTOM data. The challenge is to identify which of these models service the most industries and which industries are willing to pay the most for the models. We want to be that fourth-generation marketing platform. First generation was direct marketing followed by online leads and then list optimizers who narrowed down a list of 100,000 homes to 20,000 homes that were higher-quality leads based on basic property and ownership characteristics. Our fourth-generation platform, driven by artificial intelligence and machine learning, will narrow down that same list of 100,000 homes to just 1,000 homes that we can predict with a high degree of certainty will represent revenue-generating opportunities for our clients.
The key piece of what we do is to identify the people who haven’t done anything about transacting on their home but they are thinking about it — that’s what we’ve found we’re able to predict well.
I knew the predictive modeling was working when my name was highly ranked in the last run for Travis County, Texas, even though my wife and I don’t have any of the regular indicators in terms of years owned, size of home, age of children, etc. But the model was correct in that we are seriously considering a move!
Why did Likely.AI decide to use ATTOM Data Solutions?
We were evaluating ATTOM against another company, and really what it came down to for us was model accuracy and price. At a
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How ATTOM is Powering Real Estate Innovation – www.attomdata.com/contact-us/
What has been your experience with the data delivery?
baseline, we wanted to make sure that our models would function as well or better with ATTOM data and that ATTOM data coverage was comparable or better than the other source. ATTOM passed this initial check with flying colors.
The data delivery was actually a pretty smooth process; there weren’t a lot of errors, which is a testament to the robust data management process that ATTOM employs — merging all the various sources together to create one superset of property data.
What has been your experience with the data quality?
Each property in the ATTOM Data Warehouse is assigned a unique ID that persists across all records associated with that property, and that ensures that the data quality and quantity is consistent across all areas. ATTOM has also been willing to listen to — and work on implementing — our recommendations to improve the data for our specific use case. That type of responsiveness is far above and beyond what we have experienced with others in the industry.
During the evaluation process we also discovered some additional datasets ATTOM offered outside of the standard public record property datasets that would be very beneficial to our models. That was of course icing on the cake. On the pricing front, our rep John — whom I’ve known for many years and is a great industry resource — worked with us closely to fairly and flexibly price the data licensing agreement so that we were getting the data and terms that fit the specific objectives of Likely.AI. Lastly it became apparent during the evaluation process that the level of customer service we would be getting from ATTOM far exceeded what we were getting from the other company. When dealing with that other company, we had to wait months for something to get done. We had to sit on our hands for months. That high level of customer service continued after we signed on as an ATTOM client. As with any data provider, there are always challenges that arise, but ATTOM has been quick to respond to and address those challenges. As long as I have the support of my data provider to solve a problem, that’s what I need. As long as it’s getting resolved in a timely manner. That was something that was a deciding factor for us.
What has been your experience with customer service?
Our rep John carries around two cell phones, and he gave me both cell phone numbers and told me to call him any time. There was nothing that ever fell through the cracks. And that was very important to me being in a detailed-oriented space. Having someone at the customer support level being able to understand and being able to get us in touch with the right people very quickly is key to our success, and ATTOM has excelled in providing that high level of customer support.
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