Big data for real estate companies
Some of the world’s largest real estate companies are using Big Data to grow revenue and reduce costs. Names like Brookfield and Blackrock have doubled down on their data collection and invested heavily in recent years to use this data to help their team make better investment decisions.
While the big end of town has embraced this opportunity, we think the trend is set to filter down into mid-tier companies in the residential real estate space.
In this note, we discuss:
- Big Data — What does it really mean
- Residential opportunity
- Cost/benefit analysis
- How Wealthi partners with real estate companies to provide big data capabilities
So what is Big Data
It depends on who you ask. The way we think about Big Data is a collection of data, both internal and external, the requires a framework to source, manage and analyse. The framework is key. Big Data for Amazon or Costco is very different to Big Data for real estate companies. The concepts might be similar, but the structure and framework are completely different.
The key to Big Data is combining the three Vs — Volume, Velocity and Variety. That’s why it’s big. Because there’s a lot of it.
For commercial real estate, the applications are obvious. Large asset owners can collate data on asset sales, leasing transactions, their tenants, movement within their buildings, company trends etc. This is only useful when the data is warehoused, organised and then analysed to be useful for decision makers.
Residential opportunity
The most valuable real estate companies in the residential real estate space are already using Big Data. This is their secret sauce. It’s not the large home builders, brokerages or developers. It’s the online portals that collect, organise and sell data. Zillow and REA Group (owner of Realtor) are perfect examples.
They dominate almost every single online lead that turns into a real estate transaction within the US Market. Both Zillow and Realtor between them generate about 100 million users per month. They take that data and sell it to brokerages and agents. Commissions paid to agents are partially transferred to Zillow and Realtor in the form of advertising revenue. In reality, though, it’s just a Big Data play.
Zillow and Realtor have realised that the most valuable data they can collect and sell is around lead generation for brokerages and agents. It’s simple and it works. Zillow is valued at around US$10bn and REA Group at around US$13bn.
It’s hard to think of any successful real estate brokerage, estate developer or home building company that has the same value. But this presents an opportunity. The successful residential real estate companies of the future will be those who collect, organise, analyse and commercialise their data effectively.
Compass is a perfect example of a traditional brokerage, built around technology. It’s raised US$1.2bn from some of the world’s largest and most respected investors. They agree with its vision. Gary Keller, CEO of Keller Williams, agrees too. We were there when he gave this presentation in San Francisco last year.
Cost/benefit analysis
Like all things in business — anything worthwhile comes at a cost. We think the cost is an investment, as opposed to an expense. The return on this investment will only grow over the medium-long term. At Wealthi, we know that not all real estate companies can make the investment. Most brokerages and agents are just struggling to stay afloat.
We think the real estate market will fragment into two parts — the lowest cost supplier and the highest quality. This is what’s happened to the investment management space. You either trade with Robinhood or Goldman Sachs, an ETF or star fund manager, without much competitive advantage in the middle. Real estate will be the same — price vs. quality.
That is why we have focused on the mid-tier market, mainly real estate developers who have a large development pipeline and the capacity to invest in improving their investment returns.
Let’s use one source of Big Data — leads. Real estate developers generally pay around US$100–300 per online lead and about 3–5% commissions to sales agents for successful sales. On a US$500k apartment, that’s around US$15–20k in commissions and probably another US$5k in upfront marketing. See our previous analysis on the upfront investment cost in brand new real estate here.
A real estate developer with 100 apartments under construction will pay at least US$2–3m in commissions and marketing, which represents around 5% of their total realisable value or more importantly, around 25–30% of their total profit. Time is money in real estate development and the velocity of sales is key to realising capital and moving on to the next project opportunity.
How big is the real estate niche? We estimate around 1m brand new dwellings are completed and sold each year across the United States, Australia and the United Kingdom. The numbers are astronomically larger in Asia, but our focus is on these three key developed, English speaking markets for now.
Here’s how the 1m dwellings are broken up — USA 700k, Australia 125k and the United Kingdom at around 275k. We estimate the total value of brand new real estate sold each year across these markets is around US$340bn. Big Data used successfully to increase revenue and reduce costs makes huge sense. It scales extremely well because brand new development is a relatively systemised process and consistent between these three countries. The sales, marketing, construction and finance process is almost identical.
Does it make sense to invest in Big Data in a US$340bn annual market? We think so.
How Wealthi fits in
Our focus over the past six months has been to work with some of the largest real estate development companies across Asia. We’ve built our platform to help these companies collect, organise, segment and enrich their existing buyer databases. By doing this, we’ve managed to highlight missed sales opportunities and worked with internal sales teams to turn these opportunities into revenue.
Our clients have seen the opportunity in using their data (previously in excel spreadsheets, tucked away somewhere and forgotten) to build our new capabilities and rethink their business. In the next few months, we’ll start to document some of these case studies and post them on our Journal. If you would like to know more and see our platform in action, click here for a demo.
