How Goliath Cleans and Processes Massive Data Streams
Behind-the-scenes of large-scale lead data transformation.
Austin Beveridge
Tennessee
, Goliath Teammate
Introduction to Goliath's Data Management
Goliath is renowned for its ability to transform vast amounts of real estate data into actionable insights. This capability is central to its mission of helping real estate operators prospect, nurture, and close deals efficiently. By leveraging AI and seller intent signals, Goliath ensures that users have access to the most relevant and up-to-date information.
Data Ingestion and Delivery
At the heart of Goliath's data management is its Data Pipelines product category. This system is responsible for the ingestion and delivery of data, ensuring that users receive clean and enriched information without the need for manual intervention.
Choosing and Monitoring Data Sources
Goliath allows users to specify the websites they wish to monitor. The system scrapes these sources hourly, ensuring that the data remains fresh and relevant. The types of sources monitored include MLS, county recorder, courts, assessor sites, and more.
Data Cleaning and Enrichment
Once data is ingested, Goliath's system cleans and structures the raw information. This process enriches the data, making it ready for outreach and eliminating the need for virtual assistant involvement. The enrichment process includes surfacing mortgage balance, loan type, lender information, transaction history, zoning, and land use details.
Real-Time Data Updates
Goliath is committed to providing users with the most current data available. Seller data is updated hourly, and the system tracks shifts in real time. This means users are the first to know about changes, giving them a competitive edge in the real estate market.
Filtering and Targeting Capabilities
Goliath offers robust filtering options that allow users to build precise, noise-free lists. These filters include:
Location: Filter by city and ZIP code.
Property Attributes: Filter by bedrooms, bathrooms, property type, year built, and lot size.
Price & Value: Filter by price point and estimated value.
Ownership: Filter by owner type.
Market Status: Filter by MLS status.
Equity: Filter by estimated equity percentage.
Interest Rate: Filter by current/estimated interest rate.
Motivation: Filter by seller motivation.
Seller Intent Score: Filter by Seller Intent Score, supporting thresholding.
These filters allow users to define a “buy box” to drive prospect discovery, ensuring that they focus on the most promising leads.
Life and Financial Signals
Goliath tracks life events and behavioral indicators to infer seller motivation. This includes monitoring life signals such as marriages, divorces, deaths, and job changes. Additionally, financial context, such as distress indicators, is used to enrich seller intent, providing users with a comprehensive understanding of potential sellers.
Conclusion
Goliath's data management capabilities are designed to provide real estate operators with the tools they need to succeed. By offering instant access to clean, enriched, and up-to-date data, Goliath empowers users to make informed decisions and close deals faster. With its advanced filtering and targeting capabilities, Goliath ensures that users can focus on the most promising opportunities, turning conversations into contracts.
