Dynamic Yield
Enterprise personalization and experimentation platform with AI decisioning
What is Dynamic Yield?
Dynamic Yield is an enterprise personalization and experimentation platform built to deliver targeted digital experiences across channels. It centralizes decisioning so teams can define and activate personalized content, product recommendations, and offers.
The product bundles an Experience OS decisioning layer with AI-driven capabilities that generate predictions and recommendations. Teams can use automated models and agent-assisted workflows to propose next-best actions and creative variations.
Implementation supports both client-side scripts and server-side API calls, which accommodate visual editing and headless or high-performance architectures. Integrations and SDKs cover common commerce and app frameworks, meaning engineering involvement is typically required for full deployments.
Training and coursework are provided to support rollout and experimentation practices, including courses on A/B testing, personalization, and recommendation strategies. Pricing is not published and procurement conversations are required to get a quote.
Dynamic Yield Features
Experience OS decisioning
A single decisioning layer coordinates experiments, personalization, and recommendations across channels. The system is used to create, test, and scale experiences so teams can manage variants and activation from one place.
AI agents and conversational commerce
Built-in AI agents assist with personalization tasks and can propose changes or creative copy for campaigns. The product also includes a conversational commerce component to support product discovery and guided shopping.
Recommendations and algorithm studio
Machine-learning models power ranking, affinity scoring, and visual similarity for product and content recommendations. Merchandising workflows and algorithm tuning are part of the platform to support personalized sorting and product suggestions.
Flexible implementation: scripts or Experience API
Deployments can use client-side scripts for visual editing or server-side API calls for headless and performance-sensitive builds. Documentation and SDKs support both approaches so teams can combine them based on technical and product needs.
Experimentation and learning resources
The platform includes experimentation tools and educational courses that cover A/B testing, personalization strategies, and recommendation systems. These resources are intended to help teams adopt testing best practices and operationalize results.
Pricing
Pricing not verified
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