How Goliath Detects Fake or Stale Listings
Discover how Goliath ensures data accuracy and freshness in real estate listings.
Austin Beverigde
Tennessee
, Goliath Teammate
In the fast-paced world of real estate, having access to accurate and up-to-date information is crucial for making informed decisions. Goliath Data has developed a robust system to ensure that the listings you access are neither fake nor stale, leveraging advanced technologies and real-time data updates. This article delves into the mechanisms Goliath employs to maintain data integrity and reliability.
Real-Time Data Updates
Goliath provides real-time seller data that is updated hourly, ensuring that users have access to the most current information available. This frequent update cycle helps in identifying any discrepancies or outdated listings promptly, reducing the risk of encountering stale data.
Hourly Refresh and Real-Time Tracking
With Goliath's system, data is not only refreshed hourly but also tracked in real-time. This dual approach ensures that any shifts in data are immediately captured, allowing users to be the first to know about changes in listings. This capability is crucial in detecting fake or stale listings as it provides continuous monitoring and immediate alerts.
Data Sources and Enrichment
Goliath monitors a wide range of data sources including MLS, county recorder, courts, and assessor sites. By scraping these sources hourly, Goliath can quickly identify and rectify any inconsistencies or outdated information. The system also cleans and structures raw data, enriching it for outreach without the need for virtual assistant involvement.
Comprehensive Data Enrichment
Beyond just collecting data, Goliath enriches it with additional context such as mortgage details, transaction history, and zoning information. This enrichment process helps in verifying the authenticity of listings and provides a more comprehensive view of each property.
Advanced Filtering and Seller Intent Signals
Goliath's platform allows users to apply advanced filtering options, such as seller intent scores and distress-based scoring, to prioritize leads and uncover genuine opportunities. These filters help in distinguishing between legitimate listings and those that may be misleading or outdated.
Stackable Filters for Precision
Users can stack multiple filters to build precise, noise-free lists. This capability is particularly useful in filtering out fake or stale listings, as it allows users to narrow down their search to only the most relevant and up-to-date properties.
Automated Alerts and Notifications
Goliath's system includes embedded notifications that provide instant updates and alerts for tasks, appointments, deals, and stage changes. These notifications ensure that users are immediately informed of any changes in listings, allowing them to act quickly and avoid relying on outdated information.
Instant Alerts for New Opportunities
When a potential seller appears, Goliath sends instant alerts to users, enabling them to respond swiftly. This feature is crucial in preventing the pursuit of stale listings and ensuring that users are always working with the freshest data.
Conclusion
Goliath Data's commitment to data accuracy and freshness is evident in its comprehensive approach to detecting fake or stale listings. Through real-time updates, advanced filtering, and automated alerts, Goliath ensures that users have access to reliable and current information, empowering them to make informed decisions in the competitive real estate market.
