Predictive Audiences with Taboola: The X-Ray Vision Finding the Hidden Buyers You’re Missing
- Patrick Coyle
- Aug 11
- 2 min read
Quick Summary
Predictive Audiences acts like an AI X-ray into who’s most likely to convert from your 1st-party data
AI-powered “detective” finds hidden, high-potential customers and scales performance up to 276%
Realize's solution outperforms lookalikes, works pre-and-post-cookie, and boosts conversion ROI
Beta testers saw: CVR +23%, CPA –13%, AND ROAS uplifts, e.g. The Motley Fool: +25% ROAS
This is the missing weapon in your e-commerce strategy — don’t sleep on it
1. What Is Predictive Audiences with Taboola?
Realize's new feature, Predictive Audiences, is a superhero-level targeting engine. It takes your first-party data—especially past converters—and uses Taboola’s advanced AI to predict who else is most likely to act. Think of it as having X-ray vision for e-commerce customers.
2. How Predictive Audiences Works
Smart detective-mode: Identify users with a high propensity to add to cart, sign up, or convert—without guesswork.
Scale beyond lookalikes: Traditional models match traits; Predictive Audiences matches behavior in real time.
Cookie-independent targeting: Powered by first-party signals for future-proof, privacy-conscious reach.
3. How to Activate Predictive Audiences in Realize
Using predictive audiences realize isn’t just about understanding the concept — here’s exactly how to set it up in your dashboard:
Go to “Audiences” in the Realize Dashboard
Here you’ll find all available audience types, including Predictive Audiences.
Create a New Predictive Audience
Define the foundation of your audience — for example, a purchase event.
Realize will then use this core audience to model and create your Predictive Audience.
Select Predictive Audiences in Your Campaigns
In the campaign setup, go to “My Audiences”.
Choose the Predictive Audience you created.
Adjust the “Similarity” Slider
Closer to the left = More similar to your base audience (safer start, higher quality, narrower reach).
Further right = Broader reach, but slightly less similar to your original high-converting group.
Test Multiple Segments
For scale testing, split campaigns with different similarity settings (e.g., 80%, 60%, 40%) and compare results.
💡 Pro Tip: Start with the slider closer to your actual buyers for early wins, then gradually expand to broader similarities to find the sweet spot between scale and efficiency.
4. Why Marketers Should Care About predictive audiences realize
Higher conversion rates: Beta clients saw up to 23% lift in CVR, and –13% CPA.
ROAS rockets upward:
The Motley Fool hit +25% ROAS compared to broad targeting.
QuinStreet reported +22% CTR and +31% CVR.
Massive scale potential: Some advertisers grew Q1 spend on Realize by 43% YoY, with conversion growth as high as 276% and virtually unchanged CPA.
5. Realize vs. Traditional Lookalike Models
Feature | Lookalike Models | Realize Predictive Audiences |
Data Basis | Demographics & attributes | Behavior + real-time context |
Cookie Dependency | High | Minimal (first-party focused) |
Scalability | Limited | High—powered by AI + network |
Performance Impact | Moderate | Up to +31% CVR, +25% ROAS |
6. Key Takeaways
predictive audiences realize acts like AI X-ray vision—find customers before they find you
Ideal for advertisers seeking efficient ROAS growth with minimal guesswork
Outperforms lookalikes, respects privacy, scales performance fast
Backed by impressive beta results and human-centered innovation
