AI-powered Experience OS platform by Mastercard that creates individualized customer experiences across websites, mobile apps, email, and kiosks using real-time machine learning and behavioral analysis.
AI-powered Experience OS platform by Mastercard that delivers individualized experiences across websites, mobile apps, email, and kiosks through machine learning-driven personalization.
Dynamic Yield is an AI-powered Experience Optimization platform, acquired by Mastercard in 2022, that helps enterprise brands deliver individualized digital experiences at scale across websites, mobile apps, email, advertising, and physical kiosks. Positioned as an 'Experience OS,' the platform combines a customer data layer, a real-time decisioning engine, and a unified set of personalization, testing, and recommendation tools into a single orchestration environment used by global retailers, QSRs, financial services firms, and travel brands.
At the core of the platform is its predictive algorithms suite, which uses machine learning to analyze every visitor's behavior in real time — including browsing patterns, affinity signals, product interactions, weather, time of day, location, and historical purchase context — to determine the most relevant content, product, message, or offer to surface in any given moment. Dynamic Yield's recommendation engine supports more than a dozen pre-trained strategies (such as 'Frequently Bought Together,' 'Similar Items,' 'Trending,' 'User Affinity,' and 'Recently Viewed') and lets teams blend, weight, and stack strategies into custom recipes without writing code. Behavioral messaging, triggered overlays, social proof, dynamic banners, and AI-generated variations can all be served through the same orchestration layer.
The platform's experimentation capabilities go beyond standard A/B testing into multivariate testing, server-side testing, and AI-driven multi-armed bandit allocation that automatically shifts traffic toward winning variants. Audience Discovery uses ML to surface high-value segments that human analysts might miss, while Audience Manager allows targeting based on more than 70 built-in attributes plus any custom data piped in via the customer data layer. Generative AI features added in recent releases help merchandisers and marketers ideate copy, headlines, and creative variations directly in-platform, accelerating campaign production.
Dynamic Yield supports omnichannel orchestration through a single decisioning engine, meaning a customer's interaction on the website can immediately influence the next email they receive, the recommendations shown in the mobile app, or the upsell suggested at a self-service kiosk. Native integrations exist for Shopify, Salesforce Commerce Cloud, SAP Commerce, Adobe Commerce, BigCommerce, and most major ESPs, CDPs, and analytics platforms. As part of Mastercard, the platform also leverages anonymized commerce intelligence and is increasingly bundled with Mastercard's broader personalization and loyalty offerings.
The platform is firmly enterprise-positioned: implementations typically involve a dedicated customer success manager, solution architects, and a multi-month onboarding cycle. Pricing starts around $35,000 per year and scales significantly based on traffic volume, channels, and modules activated, putting it out of reach for SMBs but well-suited to brands that need to operationalize personalization across complex, high-traffic, multi-channel environments.
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Dynamic Yield delivers enterprise-grade AI personalization through Mastercard's Experience OS platform. Best suited for high-traffic retailers and financial services requiring sophisticated cross-channel personalization with exclusive transaction data insights.
12+ pre-trained ML recommendation strategies (Similar Items, Frequently Bought Together, User Affinity, Trending, Recently Viewed, Cart-Based, etc.) that can be blended into custom recipes with weighted logic, contextual filters, and business rules — without writing code.
A single real-time decisioning layer evaluates every visitor against active campaigns, audiences, and experiments, choosing the best variation in milliseconds across web, app, email, and kiosk channels using the same customer profile.
Native A/B, multivariate, and server-side testing with multi-armed bandit traffic allocation, holdout groups, statistical significance calculations, and segment-level performance reporting — all built into the same UI as personalization campaigns.
Audience Discovery uses ML to automatically surface high-value or underperforming segments. Audience Manager supports 70+ built-in attributes plus unlimited custom attributes via the customer data layer for precise targeting.
Built-in generative AI assists merchandisers and marketers in creating copy variations, headlines, and creative for personalization campaigns and tests, reducing time from idea to live experiment.
Pre-built and customizable triggered messages, overlays, notification bars, and social proof units that fire based on real-time behavior (exit intent, cart abandonment, scroll depth, dwell time, referral source).
Unifies first-party behavioral, transactional, and CRM data into a single profile that powers all personalization and decisioning, with native integrations into major CDPs, ESPs, analytics tools, and commerce platforms.
iOS/Android SDKs for native apps, email personalization via ESP integrations, kiosk and digital signage support, and ad targeting all share the same decisioning engine and customer profile for consistent cross-channel experiences.
From ~$35,000/year
Custom (typically $75K–$150K/year)
Custom (typically $150K+/year)
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Through late 2025 and into 2026, Dynamic Yield has continued deepening its integration with Mastercard's commerce and loyalty stack, including expanded use of anonymized commerce intelligence to inform recommendations and audience discovery. The platform has expanded its generative AI capabilities for in-platform content creation, headline variation, and campaign ideation, and added stronger AI-driven personalization for self-service kiosks and connected commerce environments. New emphasis has been placed on agentic personalization workflows — where AI agents propose, launch, and iterate on experiments with human approval — and on tighter integration with major commerce platforms including Shopify, Salesforce Commerce Cloud, and SAP Commerce.
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