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How B2B Marketers Use AI-Powered Recommendation Engines for Upsells
Description
Episode 72 explores how B2B marketers leverage AI recommendation engines to drive upsells and cross-sells in enterprise accounts. Lucas and Luna break down the mechanics behind collaborative filtering and content-based filtering, using real examples from Amazon Web Services and Adobe. They discuss how to integrate these engines with CRM data, the importance of unstructured data like support tickets and meeting notes, and why a 'product affinity score' can double attach rates. The hosts also caution against common pitfalls like recommendation fatigue and model drift, and share a practical framework for measuring impact through incremental revenue and net retention rate. This episode is packed with actionable insights for marketers managing long sales cycles and complex account hierarchies.