Real Estate Analytics

Data-driven analytics solutions drive informed decision making through intelligent property insights for US markets.

Real Estate Analytics

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?

HitechDigital’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, HitechDigital 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.

Apply advanced analytics on property records and property listings from MLS platforms to predict a property’s current or future value.

  • Understand the property market in the present by assessing a fair transaction price for a deal today.
  • Intelligent predictions on future property value in a specific market by combining CRM and marketplace data with AI.
  • Analyze values of comparable properties, current asking prices, surveyor valuations, previous fluctuations and user inputs like bedroom count, property improvements, etc.
  • Research on traditional variables like market & property performance and year built.
  • Research on nontraditional variables like number of permits issued, change in number of shops within a specific radius or building energy consumption relative to nearby structures.
  • Use computer vision to estimate property value by analyzing photos. Generate heat map of the valuation across the neighborhood.
  • Leverage the data points to run regression models using ML algorithms, deep learning and neural networks.
  • Advance model performance analysis; ranking of AVM’s in each geography, price range and property type to provide the best combination to buyers.
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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.

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

Real Estate Analytics-  Automated property valuation methods

Property recommendations.

Use AI-driven capabilities factoring in similar homes on listing pages and data points like past user behavior, similar users, products, etc. for real-time personalized recommendations.

  • Leverage website data points to run regression models using ML 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 photos, like preferred floor types, 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 like nearby schools & hospitals to distinguish each property and enhance match rate.
  • Resolve issues about identifying houses on plots not yet built through zip code counting and histograms.
  • Use interaction history for relevant recommendations, weighted with time to calculate the discounted click frequency over time.
  • Algorithm testing by leveraging interleaving technique for 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.

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

Property recommendations

Proven track record.

95% recurring clients and partnerships with industry leaders reflect our commitment to customers – their growth, their satisfaction.

  • J P Morgan
  • Ernst & Young
  • LexisNexis
  • Schlumberger
  • DHL
  • IDB
  • Xerox
  • Aventis
  • Thomson Reuters
  • Dominos

3,100+

Satisfied Clients

50+

Countries Served

5,000+

Projects Completed

1,000+

Professionals

Service Leadership.

Bachal Bhambhani

Bachal Bhambhani

Sr. Vice President, Sales

Bachal represents HitechDigital in North America, and helps client and our production teams collaborate effectively on projects and partnership initiatives.

Bret Pranham

Brett Parnham

Vice President, Sales

Brett, Vice President for Europe, is based in London. He assists HitechDigital’s executive leadership team in reinforcing partnerships and in building long-term relationships with clients across the continent.

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