Predictive Data Analytics: How REALTORS® Identify Sellers Before They List

Most REALTORS® are still chasing listings after sellers raise their hand.

Top producers do something different.

In Predictive Data Analytics, you’ll learn how consumer behavior, data aggregation, and real-world triggers can identify homeowners who are most likely to sell—before they list their property publicly.

This session breaks down a complex topic into simple, actionable strategies REALTORS® can apply immediately to increase listing opportunities and improve quality of life.

What You’ll Learn

• What predictive data analytics actually is (without tech jargon)
• How online behavior signals when someone is thinking about selling
• The most powerful seller “triggers” that predict future listings
• How absentee owners, landlords, and vacant properties fit into predictive models
• Why handwritten notes and direct outreach still outperform automation
• How REALTORS® use predictive data to prioritize sellers instead of guessing
• How this system consistently leads to more listing-side transactions

Why This Matters

Predictive data is already used by the world’s largest companies—Amazon, Apple, Zillow, and major insurers.
This class shows how REALTORS® can apply the same thinking ethically and practically at the local level.

You’ll walk away understanding how to:

• Spend less time prospecting the wrong people
• Focus on sellers with higher probability of listing
• Shift from buyer-heavy production to listing-driven income
• Build repeatable systems that scale over time

Who Should Attend

• REALTORS® who want more listings
• Agents tired of cold prospecting with low conversion
• REALTORS® interested in systems, leverage, and smarter marketing
• Professionals who want data-supported decision making—not guesswork