Data Is The New Brick: Machine Learning In The Real Estate Industry

Amit Kumar Pandey

The Dubai market has always been relatively volatile, with textbook market cycles seemingly accelerated within a very short timeline. Such behavior can be expected in growing markets, with each significant price movement resulting in a slightly more measured response.

Supply-side issues appear to be inhibiting this early stage positivity, although some neighborhoods have been impacted more than others. Significant oversupply is expected to come by Expo 2020. This would drag down average property prices, whereas market sentiment in more upmarket areas is still positive with an abundance of amenities, high-quality properties, and good transport links continue to attract demand.

Data is the new brick for real estate

During the week of Gitex, I met some leading premium real estate developers in Dubai, who discussed how to use data they already have to achieve their objectives in the current challenging market environment. In this blog, I will share my views on the conversation about the use of machine learning in the real estate industry.

Machine learning is a growing field of artificial intelligence that uses algorithms that are capable of automatically learning from data, making predictions based on data and automating the task without being explicitly programmed to do so. In simple layman’s language, I would treat machine learning as a new wave of machine (computer) revolution. Earlier revolutions helped us to increase our mechanical power. But the new revolution through machine learning is helping us in increasing our cognitive/mental power.

With the rapid advances in modern technology visualization, artificial intelligence, machine learning, computer vision, deep learning, natural language processing (NLP), and natural language generation, all industries are impacted. Real estate is certainly not an exception to this rule. In fact, three fundamental pillars of the business are affected: customers, facility assets, and our employees, all resulting in informed decision-making.

1. Customer experience

  • Chatbot assistants
  • Maintenance ticket creation through image recognition
  • Property recommendations (broker vs. bot)

2. Facility maintenance

  • Linking energy efficiency with customer satisfaction
  • Predictive maintenance, fault detection, and diagnostics
  • Maintenance ticket categorization
  • Enhanced building automation

3. Automated tasks for higher productivity

  • Automated document scanning
  • Automated underwriting process
  • Invoice and payment reconciliation

By digitalizing these three areas of the real estate business, employees are empowered to make more precise decisions, such as:

  • Predict the market value of a property
  • Evaluate customer lifetime value
  • Plan for time to close
  • Forecast market bubbles
  • Investor analysis
  • Churn management for the property of one
  • Detection of spend anomalies

When you consider these opportunities, it becomes clear that data really is the new brick. The time has come to embrace data-generating processes instead of simply running processes that generate data.

Learn how SAP Leonardo Machine Learning brings digital intelligence to enterprise offerings and creates tremendous opportunities for customers to realize greater benefits through automated processes, targeted results-driven marketing, superior customer service, as well as increased agility and process efficiency.


Amit Kumar Pandey

About Amit Kumar Pandey

Amit Kumar Pandey is a Senior Business Architect at SAP Middle East, responsible for Digital Transformation across Real Estate and Construction Industry. He is a thought leader and evangelist responsible for developing digital transformation strategy and reimagining new business models by utilizing SAP technologies with customers and business partners.