Monetate

Monetate is an enterprise experience optimization platform for personalization, product discovery, recommendations, and experimentation across websites, mobile experiences, email, apps, and other customer touchpoints. Its current platform centers on the Symphony personalization suite, Maestro experimentation suite, and MONET AI intelligence layer.

1. Personalization and discovery: Symphony uses customer behavior, contextual signals, audience data, and product catalogs to deliver individualized content and product recommendations. It also includes Product Finder, Dynamic Bundles, Social Proof, audience and journey analytics, targeting, and merchandising controls such as SKU-level filtering, boosting, and burying.
2. Experimentation: Maestro supports standard A/B/n and multivariate tests, Dynamic Testing, targeted experimentation, and feature experimentation with feature flags and gradual rollouts. Standard tests retain fixed traffic allocation for controlled learning, while Dynamic Testing automatically reallocates traffic toward variants performing better against the selected goal metric.
3. MONET AI: MONET powers both customer-facing guidance and behind-the-scenes optimization. It supports self-learning recommendations and automated personalization, while its adaptive and agentic capabilities can refine personalization and testing decisions in real time. Automated Personalization goes beyond choosing a universal winner by using machine learning to select the most appropriate experience for individual customers.
4. Platform and commercial considerations: Monetate acquired Simon AI in July 2026, connecting its onsite personalization and experimentation capabilities with an AI-first composable CDP and broader omnichannel customer intelligence. For organizations requiring experimentation in authenticated, regulated, or performance-sensitive environments, Forte extends Maestro with network-layer testing. Monetate does not publish standard package prices and instead provides customized quotes.

Monetate is most relevant to enterprise digital, ecommerce, product, and experimentation teams that want personalization, product discovery, and controlled testing to share the same decisioning and optimization layer rather than operating as separate point solutions.