Anton Babkov, Chief Executive of Rex Software, discusses his findings from Inman San Francisco, 2015.Brad Inman is the US authority on everything real estate tech and it really showed during his keynote. His big picture opening was that technology represents the biggest threat and at the same time, the biggest opportunity, in the history of our industry. In the last quarter of 2014, venture capitalists in the US poured more than $300 million dollars into startups in the real estate space. Some of these companies are building tools to help agents transact better and attract more clients. Others like Opendoor are taking direct aim at agents themselves. Whether the industry likes it or not, every real estate agent is now effectively in the tech business.Inman argued that the industry shouldn’t be overreacting to innovation and should instead “think first about innovating themselves”. To achieve maximum success over the next five years agents will need to learn to effectively leverage all the new tools and capabilities being delivered to the industry. This doesn’t mean throwing the baby out with the bathwater and starting again - what agents need to think about is how they can retool their existing infrastructure to innovate.The keynote outlined a number of trends that will drive industry change in the coming years:
Lessons from Hybrid agencies
Tech-powered ‘hybrid’ agencies are becoming increasingly prevalent in the U.S. market. The approaches these businesses are taking offer some interesting lessons for the industry:
- Heavy emphasis on technology: hybrids have invested heavily into in-house platforms and external technology to allow them to automate their businesses and provide a richer customer experience. Tech used varied widely, though here are a few key examples:
- Redfin has developed a whole of business platform to automate process, track and constantly improve their client satisfaction. Efficiencies gained by streamlining processes allow Redfin to charge half the commission of its competitors. Their growth in the US has been dramatic.
- Compass – a new entrant – uses public smartphone apps and their website to give consumers a better experience searching for properties and discovering new places to live. Compass is positioning itself as a premium service, and appears to charge rates in line with the broader market in the U.S.
- Opendoor has been described as a ‘big data house flipper’. The startup uses proprietary technology to determine the market price of a property with pinpoint accuracy. This gives them the ability to turn around sales for homeowners in as little as 3 days. Opendoor charges a substantial premium to standard market commissions for their quick turnaround service.
- Agents are at the centre (generally): The majority of startups place a strong emphasis on the continued critical role of agents. Redfin relies on its agents to deliver outstanding customer service. Compass hires agents that have expert knowledge about their local areas. Buying and selling property is a complex, emotional and infrequent transaction that requires a human expert that can support and advise their clients through the selling process.
- Affiliated revenue sources: A more full service and revenue from secondary sources are major parts of the hybrid value proposition. The sale and purchase of a property usually involves a number of large exchanges of value: finance, insurance, utilities connections, etc.Because tech powered agencies track everything about their clients, those clients are able to benefit by receiving a more convenient and comprehensive service during the transaction (often at discounted rates). Agents also benefit from referral fees paid by banks, insurers and utilities companies.
- Corporatisation / Specialisation: Hybrids use specialisation to deliver the real estate service more efficiently. Specialist teams inside the business carry out functions like marketing, technology, customer support, property inspections and after sales service. Specialisation agents focus on their core role: listing properties, managing client relationships and negotiating great outcomes for clients. In fact, hybrids appear to have a lot more in common with ‘teams’ or ‘effective business units’ than they do with traditional agency models.
- Customer experience focus: Whatever their value proposition, the customer stands at the centre. Hybrids are focused on delivering a seamless service - building trust and lasting value for clients throughout a transaction and long after it completes. This fanatical focus on the customer is intended to create long-term loyalty, a great market reputation and the foundation for a strong business powered through referrals by extremely happy clients.
For those that are interested, Inman recently published a report on hybrid agencies. Only subscribers have access, though subscription is well worth it.
Data gathering, ownership and privacy
CRM tools, government data initiatives and the rise of new tech are creating an increasingly complex set of electronic data sources with rich information about properties, customers and real estate transactions. Some key examples of data being gathered and stored by agencies include:
- Core transactional and pricing data from rental and selling activity
- Contact information and demographic data gathered from clients, open for inspections, contact lists, etc.
- Details about contacts’ engagement with properties and other content via marketing channels like portals, agency websites and mass email marketing
- Customer testimonials and reviews managed by the agency and on external sites like yelp.com
External data sources:
- Government sources of demographic data about property ownership and suburb characteristics
- Agent profiles on real estate portals like realestate.com.au
- Financial / credit file data
- Government data about property values, mortgages activity and titles
- Data about social status, activity and linkages on social networks
Over the next few years, more progressive agencies will focus aggressively on gathering and combining their internal data sources to create a tapestry of information about clients and properties.As government and tech providers increasingly open up new data sources for industry access, two potential benefits can foreseeably arise for forward-thinking agents:
- Richer customer / transaction profiles: Agents can build solutions linking their own with internal data sources to allow them to paint a clearer picture of consumers and transactional activity.
- Seamless tech powered sale and purchase process: More open data sources could also be used to ‘stitch together’ the sales process. Customers can benefit from complete visibility and automation during the transaction process via smartphone apps and rich vendor portals.
Agents will need to work to encourage the tech companies working in the industry, as well as government, to make this a reality. In Australia, initiatives like e-conveyancing are starting to open the doors to this type of innovation. Still, much more work needs to be done by government and industry tech players like portals and CRM companies to set data sources free.With all this potential insight, it’s important to remember that greater use of and access to data raises some complex issues. Who owns the data? The customer? The agent? The agency? Portal companies? And how can consumer privacy be protected while allowing the industry to get the best out of the data it generates? It will be important to tread carefully to secure the most value for the industry and consumers in the long term.
Artificial intelligence / machine learning and your data
In its simplest form, artificial intelligence uses complex data sets in combination with an algorithm to build models predicting the likelihood of a given outcome given a specific set of facts. For the real estate industry, predictive models could be built up based on existing data and used to predict consumer behavior. Examples could include:
- Finding out exactly when sellers are ready to list or buyers are ready to buy: already, companies like Core Logic are combining transaction and social data to create ‘propensity models’ allowing you to work with more qualified and highly targeted prospects. With increasingly complex data being exposed, these models will become more and more accurate.
- Discovering the properties / locations buyers are actually looking for: the industry will increasingly use more semantic information about buyers and sellers to target their activity and create outstanding customer experiences. This could include:
- Demographic data like family status (kids at primary age may need to move for schools, kids graduating and moving away to work may mean a downsize)
- Work location (how long is the average commute for a buyer from a given property?)
- Suburb demographics (are purchasers with similar demographics buying in a particular area?).
- Social data (Where do a buyer’s closest social connections live? Do they want to live nearby?)
AI and machine learning are not new. Tech companies are already using data with complex algorithms to some very interesting ends:
- Facebook friends and your credit score: In 2012, Facebook filed a patent that would allow lenders to determine whether a person is worthy of getting a loan based on their circle of friends on the social network.
- E-harmony’s algorithm playing cupid: Before it launched, E-harmony used the result of a 500 question survey delivered to 3,000 couples to create an algorithm that could predict how compatible a potential couple would be based on their person characteristics.
For more information on AI and machine learning, check this out.That’s it for the keynote - more to come soon.