Real Estate Analytics

Real Estate Analytics

Leverage advanced analytics to generate intelligent insights into property markets

Hitech Hitech

Service Overview.

You might have invested significantly in aggregating millions of records of property listings, transactions and other data from across sources. But are you able to harness this power to generate precise pricing estimates or data-driven property recommendations? How effectively can you factor in multiple traditional and nontraditional variables to provide accurate property intelligence?

Hitech’s real estate data analytics solutions offer granular and actionable insights into property market performance, bridging the gap between data availability and data utilization. Our automated valuation models embed into your website to give users fairly precise and instant property value estimates. Accurate property intelligence related to submarket performance, recommendations on best buys etc. is delivered through visually interactive customizable dashboards and alerts.

Our custom property analytics workflow has 100+ data analysts working in sync on sequential and parallel activities ranging from data aggregation and standardization to market predictions and price intelligence. Using a blend of machine learning algorithms, deep learning and neural networks, we clean and standardize massive amounts of raw transactional data to prepare it for further analytical drills. Integrating this data with a host of traditional and nontraditional attributes such as locality, property specifications, historical trends etc., and applying advanced analytics helps generate accurate and intelligent property insights.

For over two decades, Hitech has successfully provided analytical insights and predictive intelligence for more than 155 million U.S. properties across 3,000 counties.

Get timely, reliable and intelligent real estate market insights.

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Automated property Valuation Models.

Use advanced analytics on property records and property listings from platforms like Zillow for a given property to predict a property’s current or future value.

  • Automated valuation models to understand the property market in the present by assessing a fair transaction price for a deal today.
  • Better predict future value of a home in a specific market by combining CRM and marketplace data with AI.
  • Analyze values of comparable properties, current asking prices, previous surveyor valuations, historical house price movements and user inputs like number of bedrooms, property improvements, etc.
  • Research on traditional variables such as market performance, property performance and year built.
  • Research on nontraditional variables such as number of permits issued, change in number of shops within a specific radius or building energy consumption relative to other structures in the same zip code.
  • Use computer vision to estimate property value by analyzing photos.
  • Leverage the data points to run regression models using ML algorithms, deep learning and neural networks.
  • Heat map of the valuation across the neighborhood.
  • Advance model performance analysis; Ranking of AVM’s in each geography, price range and property type which can be used by customers to provide the best combination of AVMs to buyers.
  • Intelligent forecast values for upcoming 36 months.
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Truly impressed with the property valuation solution you guys gave us. Its added tremendous value to our site and our user engagement has really increased. Quote

– Founder, Chief Executive Officer, Real Estate Listing Site, The Netherlands

Real Estate Analytics-  Automated property valuation methods

Property recommendations.

Set of AI-driven capabilities factoring in similar Homes on listing pages and data points such as past user behavior, similar users, similar products, and more, for real-time personalized recommendations.

  • Leverage website data points to run regression models using machine learning algorithms, deep learning and neural networks.
  • Data extraction – quantitative information (price, bedroom count, etc.) and categorical information (property type, etc.) from the property listings to build recommendations on similar homes, personalized search rankings etc.
  • Identify user’s preferences and extract relevant information from the user’s photos, such as the preferred type of floors, color palettes, and construction materials.
  • Improve data quality by leveraging advanced cleansing tools for an updated view of the properties.
  • Add additional levels of data e.g., schools, religious type to highlight and distinguish each property, enhancing the match rate, confidence level.
  • Resolving issues about identifying houses on plots not yet built through zip code counting and histograms.
  • Use interaction history for a user for more relevant recommendations, weighted with time to calculate the discounted click frequency over time.
  • Algorithm testing by leveraging interleaving technique (as a substitute to the classic A/B testing model) that provides statistically significant results on comparative model performance.
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I must say, your smart tools worked perfectly at providing personalized property recommendations to visitors on our site. Quote

– VP of Operations, Customer Services, Property Portal, California

Property recommendations

Satisfied Customers.

80% recurring clients and partnerships with industry leaders reflect our commitment to customers – their growth, their satisfaction.

3,100+ Satisfied Clients
50+ Countries Served
5,000+ Projects Completed
1,000+ Professionals

Service Leadership.

Bachal Bhambhani
Bachal Bhambhani
Bachal represents Hitech in North America, and helps client and home teams collaborate effectively on projects and partnership initiatives.
Brett Pranham
Brett Parnham
Brett, Vice President for Europe, is based in London. He assists Hitech’s executive leadership team in reinforcing partnerships and in building long-term relationships with clients across the continent.

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