Introduction
With thousands of SKUs and millions of potential customers, ecommerce brands face a massive challenge: showing the right product to the right user at the right time. AI-powered personalization is solving this problem—and unlocking incremental GMV that traditional retargeting cannot reach.
Why Traditional Retargeting Falls Short
Retargeting usually shows users the exact product they already viewed. But this approach has limitations:
- It doesn’t explore alternative or complementary products
- It ignores category trends or best sellers
- It only works for audiences who browsed something
- It doesn’t uncover hidden purchase intent
Today’s ecommerce shoppers are unpredictable. They browse broadly, compare widely, and leave quickly. Traditional retargeting captures only a fraction of purchase opportunities.
How AI Personalization Improves Performance
1. Understanding User Intent Beyond Browsing
AI analyzes signals such as dwell time, page depth, scroll behavior, and category preferences—not just product views.
2. Predicting What Users Might Buy
Machine learning identifies products users never viewed but are highly likely to convert on.
3. Scaling Dynamic Creative Optimization (DCO)
AI automatically generates personalized ads with:
- Relevance-based product selection
- Best-selling or trending items
- Complementary / cross-sell recommendations
4. Real-Time Learning
The model updates itself continuously, improving prediction accuracy over time.
RtiBid’s AI Product Intelligence Model
RTIBid evaluates every product in a catalog across:
- Relevance
- Affinity
- Complementarity
- Category best-sellers
- Overall site performance
This leads to higher conversion probability and incremental sales.
Conclusion
AI-powered personalization is no longer optional. It is the foundation of scalable ecommerce advertising—and one of the most reliable ways to generate new GMV. RTIBid helps brands unlock hidden revenue opportunities that traditional retargeting leaves behind.
