Technology and residential property: shaping the future

Break the habit

29 May 2018

Technology is not only a tool but offers a means of innovating and better understanding your customers’ needs. Saurabh Saxena gives his view of the technologies shaping the future of residential property

Consumer behaviour constantly evolves. Two decades ago it was not common to own a computer, and print, radio, TV and other conventional advertising channels were the most powerful means to reach consumers. When Google was launched in 1998, most people were still trying to understand what the internet really was.

It is hard to change people’s habits, and even harder to sell them a vision that sounds unrealistic. In the 1990s, today’s reality of widespread internet and information consumption through a smartphone might have sounded as though it came from a sci-fi movie.

In 2000, property website Rightmove fought hard to change the advertising mindset of the property sector, which depended on newspaper classifieds to sell homes. Today, Rightmove has more than a million listings, 130m visits a month, and is worth more than £4bn.

Figure 1 shows how UK real-estate consumers have adapted their use of technology over the past 20 years. The next natural step is expected to be completely digital platforms that bring together all the interactions and transactions between user groups.

There are similar stories in other sectors – for example, Amazon and eBay in retail, and and TripAdvisor in travel. Each of these giant corporations began small by aligning themselves to changing consumer behaviours and educating the market as to their benefits.

The message from entrepreneurs, historians and philosophers is clear: change is inevitable, the ones who lead or adopt change will share the gains, and the rest will run the risk of becoming obsolete. This has nothing to do with technology; it is more of a fight within people to discard their old habits and acquire new ones.

Evolution of digitisation in UK real estate.

Figure 1: Evolution of digitalisation in UK real estate. Source: Houzen

Insight paper

I have worked in more than 20 industry sectors across three continents and have advised Fortune 200 and private equity professionals on how corporations should realign their business models to changing consumer demographics and consumption patterns.

When I moved into real estate, I noticed that many professionals feared adopting this new phenomenon called property technology, or 'proptech', and even those who showed willingness didn’t know how to change.

In 2017, we interviewed 30 professionals and thought leaders across different sectors and continents to learn from their success and failures, and define a clear path for technology adoption in real estate. These experts are building businesses using technologies as varied as artificial intelligence, deep learning, blockchain, the Internet of Things, machine learning and computer vision. The interviewees included the likes of Tyler Winklevoss of Facebook and Bitcoin, and senior professionals from KPMG, Centrica, the Shell Foundation, Urban Land Institute and Ethereum, an open-source platform to write and distribute a decentralised currency.

We asked interviewees to give their recommendations for implementing technology in real-estate professions. The top 10 are:

  1. using big data and machine learning to predict which neighbourhoods will be hot and upcoming;
  2. using machine learning and artificial intelligence-powered apps that show tenants the optimal places to live;
  3. digitalising and securing land registry data using blockchain;
  4. supporting architectural design with artificial intelligence and machine learning;
  5. using blockchain and virtual reality to remove the agent from the lettings value chain through smart contracts and virtual viewings;
  6. creating a digital identity for all actors in the lettings value chain, for instance landlord–property–tenant, seller–buyer and so on;
  7. using interconnected smart devices and sensors to monitor and cut energy waste and minimise residents’ utility bills;
  8. using real-time property valuations derived from pictures and videos through computer vision and deep learning;
  9. using intelligent property management informed by machine learning and artificial intelligence; and
  10. enabling asset optimisation for portfolio managers through machine learning.

RICS published these findings in an insight paper, The technological revolution and the future of residential property, and hosted a launch event for members working in investment, surveying, valuation and property management. Most were excited and optimistic, while a few were initially hesitant and challenged the new ideas. This is natural, as most of us find it difficult to change old habits and adopt new ways of working. We recommended that change and improvement happen in incremental steps that follow the core principles outlined below.

Old and new: how the market rewards innovation and customer-first models

Figure 2: Old and new: how the market rewards innovation and customer-first models. Source: Houzen

Putting the customer first

To start thinking about an evolving business model, real-estate professionals should first focus on their end customer. Real estate has traditionally been an asset management sector, and little attention has been given to identifying and managing the end customers themselves.

During debates at prominent commercial and residential real-estate corporations, executive managers repeatedly say that they know their customer well. However, the end customers seem to differ in opinion when they show a strong preference for innovative business models rather than the traditional ones, for example for WeWork rather than Regus. Figure 2 compares the way the market has rewarded traditional and new business models – valuations are always a good proxy for consumer advocacy.

Many investors have been intrigued by the substantial difference in valuation between Regus and WeWork, even though they provide similar services. The latter’s growth has put the former under pressure from its shareholders as it has been consistently losing share in both mature and growth markets.

Most senior executives in the traditional shared-working sector will suggest that there is absolutely no difference between the Regus and WeWork business models. They are partly correct, but there remains a difference in the way that their customers consume products and services, and how much they value fulfilling experiences. WeWork’s value is that it seamlessly connects its tenants with one another through an internal online network and makes a conscious effort to delight customers every time they’re contacted.

WeWork service

A friend of mine recently began working at WeWork in Moorgate, London. She was greeted by one of its community managers who showed her around and introduced her to the organisation’s excellent internal social network, which can be used to connect with other start-ups and small companies for anything her company needs.

For example, if she needed a designer, she could post a notice on the internal network and get quotes from WeWorkers in the same or different London offices. If she wanted to open a New York office and needed some legal advice, she could post the task on the New York network and be assured of a specific response. The value of WeWork’s innovative approach is in unifying the crowd of small and ambitious companies. My friend loved the power of the exclusive network, and was also pleased by the gift of a Buddha for her desk, and now actively supports the WeWork mission in her social conversations.

The common thread in the growth and valuation of the successful new business models – Uber, Airbnb, WeWork, Apple and so on – is strong advocacy and brand loyalty from customers. Entrepreneurs at each of these companies spend years learning about their customers’ habits and needs, then provide the experience they want through carefully designed product features and services. Brian Chesky, the founder of Airbnb, famously went on a world tour and lived with hosts and guests, studying their habits and trying to understand what fulfilling experiences mean to them.

Glossary of deep technology

  • Proptech: this refers to all aspects of technology and how it affects the built environment. This may include software, hardware, materials or manufacturing. It is an all-encompassing term, but is often used to refer specifically to the small start-ups using technology to address market problems.
  • Blockchain: a distributed database that maintains a continuously growing list of records – blocks – that are secured from tampering and revision. Each block contains a timestamp and a link to a previous block.
  • Artificial intelligence (AI): a general term that refers to hardware or software that exhibits behaviour that appears intelligent. The phrase was coined by Professor John McCarthy in 1956, who called it 'the science and engineering of making intelligent machines, especially intelligent computer programs'.
  • Intelligence augmentation (IA): this aspires to give humans the tools and information that they need to eliminate mundane tasks so they can focus on their core and experiential activities, thereby amplifying users’ productivity, creativity and gratification.
  • Machine learning (ML): the subfield of computer science that, according to Arthur Samuel’s remark in 1959, gives 'computers the ability to learn without being explicitly programmed'.
  • Deep learning (DL): an approach to AI that aims to solve practical problems by mimicking our own decision-making processes. AI, ML and DL are highly interlinked.
  • Big data analytics: big data refers to data sets so large or complex that traditional processing applications are inadequate. Research and advisory company Gartner says big data is 'high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making, and process automation'.
  • Computer vision: the British Machine Vision Association says that, while 'humans use their eyes and their brains to see and visually sense the world around them … computer vision is the science that aims to give a similar, if not better, capability to a machine or computer'.
  • The Internet of Things: this is broadly defined by business publisher Forbes as 'a giant network of connected ‘things’ (which also includes people). The relationship will be between people–people, people–things, and things–things'. It allows for virtually endless opportunities and connections.

Power of scale

Exceptional service is typically provided by people with a strong customer orientation and a mission to improve the status quo. Once someone is able to impress their customers, the next and more difficult step is to scale that experience up to reach every touchpoint. Doing so successfully would likely convert the customer into a loyal advocate for a brand.

This process can now be powered by a strong infrastructure supported by technology and data, so that customers can start interacting with the product or service in real time and with each other. These interactions start producing invaluable insight on consumer consumption patterns, which can steer product improvement; hence, more interactions mean a better product offering if leveraged properly.

The Uber napkin.

Figure 3: The Uber napkin. Source: David Sacks

Financially, there are even greater benefits to a business as the cost of scaling the customer experience keeps reducing with increased consumer density. The famous Uber napkin (see Figure 3) was drawn by internet entrepreneur and Uber investor David Sacks to demonstrate the positive impact of supply and demand density. Houzen sketched out its own version (see Figure 4), which demonstrates how supply and demand aggregation, and hence bigger portfolios, benefit the residential real-estate market in general.

The Houzen napkin.

Figure 4: The Houzen napkin. Source: Houzen

So put your customers first and understand what it is in particular that they value in your services and products. Don’t assume anything; listen more than talk. World-class products and services can only be created once you know your end customer inside out.

Saurabh Saxena is the Founder of online letting agent Houzen

Further information