Safely Personalize Every Experience to Increase Engagement & ROI

Traditional audience creation: Users in blue and orange are categorized into different “audience” targets based on how they look, with the assumption that they will behave similarly.

Yobi’s innovative approach: Our AI/ML models identify how these audiences behave and create new dimensions, clustering them into new distinct audiences based on the most predictive 200+ signals derived from our knowledge graph.

What is an Embedding?

Embeddings (vectorized data) are the cornerstone of modern AI, allowing AI to process vast amounts of data quickly & efficiently, capturing non-linear relationships in data, and drawing correlations that might not be apparent to humans.

By converting consumer behavior datasets into Embeddings, AI can keep relationships and correlations between consumer behavior intact, providing AI with the signals necessary for modeling without exposing it to raw consumer data. This is ideal for AI/ML Teams, who have been restricted from using raw consumer data up until this point.

What are Embedding use cases within AI/ML

1. Instant Personalization – provide a starting point for recommender systems (overcoming the cold start problem), by enriching your users’ profiles
2. Improve Ad Conversions – create more granular audience segments by understanding your users’ behavior, to deliver the right message, through the right channel, at the right time
3. Anticipate Churn – reactivate churned customers, and identify which segments share similar characteristics, by enhancing their user profiles
4. Prevent Fraud – identify which users might be more susceptible to fraud, and what normal behavior looks like, by creating a richer customer profile
5. Optimize Pricing & Demand Forecasting – leverage consumer behavioral signals from outside your ecosystem to provide insights on price sensitivity, competitive intelligence, and market trends