How Goliath Uses Behavioral Data to Score Leads
Unlock the power of AI-driven insights to transform your real estate pipeline.
Austin Beverigde
Tennessee
, Goliath Teammate
Introduction to Goliath's Lead Scoring
In the fast-paced world of real estate, understanding seller intent and motivation is crucial for success. Goliath provides real estate operators with the tools they need to prospect, nurture, and close deals efficiently, leveraging AI and seller intent signals. This article explores how Goliath uses behavioral data to enhance lead scoring, ensuring that users can focus their efforts on the most promising opportunities.
Real-Time Data and Seller Intent Signals
Goliath's platform is built on the foundation of real-time data, with seller information updated hourly. This ensures that users have access to the freshest insights, enabling them to be the first to know about shifts in the market. By tracking life events and behavioral indicators, such as moves and job changes, Goliath infers seller motivation, providing a comprehensive view of potential leads.
Behavioral and Financial Signals
Goliath enriches its lead scoring system with both behavioral and financial signals. Behavioral signals include life events that may indicate a seller's readiness to move, while financial signals provide context on potential distress indicators. This dual approach ensures a nuanced understanding of each lead's situation, allowing users to prioritize their outreach efforts effectively.
Advanced Filtering and Custom Lists
One of Goliath's standout features is its advanced filtering capabilities. Users can filter leads based on a variety of criteria, including:
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 and estimated equity percentage.
Market Status: Filter by MLS status, such as not listed properties.
Interest Rate: Filter by current or estimated interest rate.
Motivation: Filter by seller motivation and Seller Intent Score.
These filters can be stacked to create precise, noise-free lists that match specific criteria, ensuring that users can focus on the most relevant leads.
Seller Intent Score and Distress-Based Scoring
The Seller Intent Score is a key component of Goliath's lead scoring system. It supports thresholding, allowing users to filter leads with a score above a certain level, such as 60+. This score is enhanced by distress-based scoring, which includes distress signals and other motivation inputs to provide a comprehensive view of a lead's potential.
Automated Outreach and Nurturing
Once leads are identified and scored, Goliath offers tools for automated outreach and nurturing. Users can engage in personalized multichannel outreach, including calls, texts, and emails, at scale. Automated follow-ups and drip actions keep prospects moving through the pipeline, while smart call lists and instant summaries accelerate actions.
Smart Call Lists and Scheduling
Goliath's platform generates smart call lists and provides instant summaries to help users take action quickly. Built-in reminders and appointment management features ensure that no opportunity slips through the cracks, keeping the sales process on track.
Closing Deals with Efficiency
Goliath's platform includes a deal dashboard that provides a single live view of every deal, notes, next steps, and instant updates. Automated contract creation and tracking shorten the time-to-close, while smart reminders help keep deals on track. Digital agreements support remote e-signing, and document tracking provides visibility on what's signed and pending.
Conclusion
Goliath's use of behavioral data to score leads is a game-changer for real estate operators. By leveraging real-time data, advanced filtering, and automated outreach, Goliath empowers users to focus on the most promising opportunities, turning conversations into contracts. With Goliath, real estate professionals can build smarter pipelines and close deals faster, all while reducing the time spent on manual research and prospecting.
