In this quick tutorial, Pecan CEO Zohar Bronfman explains why filtering out irrelevant entities is a game-changer for your predictive models. Learn why including only relevant data points (like recently active customers) leads to more accurate predictions, faster processing, and better business outcomes.

This often-overlooked step can dramatically improve your model performance without requiring complex data science expertise. Whether you're predicting customer lifetime value or conversion likelihood, smart entity filtering ensures your models focus on what truly matters for your business goals.

New to predictive analytics? Pecan AI makes advanced machine learning accessible to business users without requiring data science expertise. Learn more at https://www.pecan.ai