About Dynamic Yield
Dynamic Yield by Mastercard is an enterprise personalization and experimentation platform. Acquired by Mastercard in 2022, it is now delivered as the "Experience OS" — one system that algorithmically matches content, products and offers to each individual customer across web, mobile app, email and in-store touchpoints. It is an 8-time consecutive Leader in the Gartner Magic Quadrant for Personalization Engines (through 2026), a Forrester Wave Leader for Experience Optimization Solutions, and serves 400+ global brands across retail, grocery, QSR, travel and financial services.
Pricing
Check the official site for current plans and pricing.
Key features
- A/B & multivariate testing (client + server-side):: Bayesian and multi-armed bandit statistical engines, Dynamic Traffic Allocation and Affinity Allocation to route traffic to winning variations autom
- Product recommendations:: journey-aware recommendation engine with collaborative filtering, user-affinity, geo-based predictive spend and deep-learning (AdaptML) models; visible uplift — e.g. 88% ARPU
- Experience Search:: next-generation AI search with semantic understanding and visual AI that captures real user intent, reduces maintenance and boosts long-tail product visibility.
- Shopping Muse:: generative-AI shopping assistant that turns conversational prompts like "outfits for a summer wedding" into curated product guidance.
- AdaptML:: decisioning core using recurrent neural networks (RNN) and NLP that retrains continuously from live sessions instead of rigid if-then rules.
Pros & cons
Pros
- A/B & multivariate testing (client + server-side):: Bayesian and multi-armed bandit statistical engines, Dynamic Traffic
- : journey-aware recommendation engine with collaborative filtering, user-affinity, geo-based predictive spend and deep-l
- : next-generation AI search with semantic understanding and visual AI that captures real user intent, reduces maintenanc
Cons
- Confirm plan limits and feature gates on the official pricing page
- Best results usually need correct setup and ongoing optimization
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