AI models learn from profile, behavior, and context to rank complementary products or upgrades and push them via CRM, journeys, web/app personalization, and agent UIs as the next best cross‑sell/upsell step. Decisioning systems manage an offer catalog with eligibility, frequency caps, and arbitration so each person sees a single best offer at the right time … Read more
AI in SaaS predicts customer lifetime value by learning from transactions and behaviors to forecast future spend, churn risk, and order cadence, then activates those insights in campaigns, journeys, and offers to maximize profitable growth across the lifecycle. Leading platforms provide out‑of‑the‑box CLV models and building blocks like return probability, predicted orders, and AOV, with … Read more
Modern retention programs operationalize three loops: detect risk, act with targeted plays, and learn via controlled experiments. The stack combines a churn model (or health score) and journey orchestration that coordinates in‑app prompts, messages, and CSM tasks—then proves impact with holdouts and forecast‑vs‑actual tracking. What signals and features work Build an effective churn model Orchestrate … Read more