This white paper from Braze AI Decisioning Studio explains how reinforcement learning and “bandit” algorithms enable true 1:1 personalization in marketing. It describes multi-armed and contextual bandits, showing how AI agents test, learn, and optimize engagement strategies in real time. Braze’s “community of bandits” architecture—combining elastic nets, decision trees, and meta-bandits—learns efficiently to predict the best message, channel, and timing for each customer. A case study of a major bank illustrates a 92% conversion lift and $16M annualized value, proving AI decisioning’s power to transform lifecycle marketing.

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