- Verified by BizGlocal
Enterprise Personalization Engine With The Deepest Feature Set In Its Class
- 200+ Employees
- Founded In 2011
- New York, NY
- Serves 5+ Industries
About Dynamic Yield
Industry leader in connected fleet operations
Market Position
Eight-time Gartner Magic Quadrant Leader for Personalization Engines, also recognized as a Leader by Forrester in 2024
Innovation Focus
AI-driven decisioning, predictive targeting, generative AI product discovery through Shopping Muse, and API-first delivery
Core Strengths
Recommendations, experimentation, audience targeting and omnichannel delivery sharing one data and decisioning layer
Use Cases
Ecommerce merchandising, travel booking flows, grocery subscriptions, iGaming engagement, card issuer offers and QSR ordering.
Core Products & Solutions
Experience OS
The core platform where teams build audiences, deploy personalized web and app experiences, and manage every campaign from one workspace. Earlier module names were merged under this brand in a single operating layer.
Product Recommendations
Algorithmic recommendation strategies for home, category, product, cart and post-purchase placements. Merchandisers can add filters, pinning and business rules on top of the model output.
Experimentation and Predictive Targeting
A/B, multivariate and multi-armed bandit testing with audience-level reporting. Predictive targeting surfaces segments that respond differently to a variation so teams can personalize the winner by segment.
Shopping Muse
A generative AI shopping assistant launched in November 2023 that turns conversational, natural-language requests into product recommendations drawn from the retailer's catalog. It is aimed at fashion, home and lifestyle catalogs where shoppers describe a look or occasion rather than a SKU.
Email and Triggered Messaging Personalization
Recommendations and content blocks inserted into email at open time, plus behavior-triggered messages. This lets email teams reuse the same audiences and recommendation strategies as the website.
Experience APIs and Mobile App Personalization
Server-side and headless APIs deliver decisions to native apps, kiosks, call centers and custom front ends. A Shopify app and commerce platform partnerships such as Intershop shorten deployment for supported stacks.
Pricing Overview
Core Personalization
Mid-market ecommerce teams starting with personalization
Custom
Pricing
Custom quote, annual contract (third-party guides place entry contracts in the five-figure annual range)
- Experience OS web personalization
- Audience builder and targeting rules
- A/B and multivariate testing
- Standard recommendation strategies
- Shopify or tag-based deployment
- Standard onboarding and support
Growth Suite
Multi-channel brands personalizing web, app and email
Custom
Pricing
Custom quote, priced on traffic volume and modules
- Everything in Core Personalization
- Predictive targeting and multi-armed bandits
- Email recommendations and triggered messaging
- Mobile app personalization
- Advanced merchandising rules
- Customer success manager
Enterprise and AI
Large retailers and multi-brand, multi-market enterprises
Custom
Pricing
Custom quote, multi-year enterprise agreements common
- Everything in Growth Suite
- Shopping Muse conversational AI
- Experience APIs for headless and server-side use
- Multi-site and multi-market localization
- Professional services and strategy support
- Enterprise security and data controls
Who Is Dynamic Yield Best For?
Small Businesses
1-25 EmployeesGenerally a poor fit. Quote-only enterprise pricing and the setup effort usually exceed what a small team can recover, and self-serve tools are a better starting point.
Mid-Market Companies
26-100 EmployeesA fit for digitally mature, high-traffic ecommerce or travel brands that have enough sessions to run meaningful tests. They also need at least one person who can own the platform day to day.
Enterprise Companies
100+ EmployeesThe core segment. Multi-market retailers, grocers, travel companies and financial institutions such as Saks Fifth Avenue, Ocado, Electrolux and TUI Cruises use the full feature set across channels.
Ecommerce and Retail Brands
Any SizeBrands with large catalogs benefit most from recommendations, merchandising rules and Shopping Muse. Their revenue depends directly on product discovery and average order value.
Measurable Impact & Benefits
54.1%
Revenue Per User Lift
An iconic sports team using AI-powered predictive targeting
25%
Conversion Uplift
Winner, an iGaming operator, among targeted players
13.5%
Subscription Increase
Ocado grocery subscriptions driven by personalization
3x
Conversions
Bergzeit, an outdoor retailer, using conversational AI product discovery
9.1%
Revenue Per User Boost
Social proof messaging tactics in a published test
5
-7% Uplift In Conversion, AOV And Revenue Per Session
APMEX, an online precious metals retailer
21
Markets Localized
Electrolux localized content across 21 markets with personalization
8
-Time Gartner Leader
Named a Leader in the Gartner Magic Quadrant for Personalization Engines eight times
Dynamic Yield Real reviews
Our Rating:
4.5
- Verified Users
- Verified Users
Personalization Checklist
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Dynamic Yield’s Pros & Cons
Balanced evaluation to help you make an informed decision
Strengths
- Among the broadest feature sets in personalization: targeting, recommendations, testing, email and APIs in one engine
- Eight consecutive Gartner Magic Quadrant Leader placements for personalization engines
- Shopping Muse adds generative AI product discovery to the core platform
- Predictive targeting finds segment-level winners that basic A/B tools miss
- Experience APIs support headless, app and offline channel use cases
- Deep library of published case studies across retail, travel, grocery, iGaming and financial services
- Backed by Mastercard, which adds financial stability and access to payments data expertise
Limitations
- No published pricing, and third-party estimates place it firmly in the enterprise budget range
- Uneconomical for small businesses and low-traffic sites that cannot reach test significance
- Advanced use of APIs, custom templates and server-side delivery typically needs developer resources
- Learning curve for marketers given the number of modules, rules and reporting views
- Two ownership changes since 2019 (McDonald's, then Mastercard) make roadmap continuity a fair diligence question
- Reported results come mostly from vendor case studies rather than independent benchmarks
Our Verdict
Dynamic Yield earns its Best in Features placement because few personalization platforms cover as much ground in one engine. It combines rule-based and predictive targeting, algorithmic recommendations with merchandising controls, rigorous experimentation, email and app personalization, headless APIs and a generative AI shopping assistant. Its repeated Gartner Leader placements and case studies from brands such as Saks Fifth Avenue, Ocado and Electrolux back the claim that the features hold up at enterprise scale. That depth has a price. Every contract is custom-quoted in the enterprise range, and getting value from it takes enough traffic, clean product and behavioral data, and in-house or partner expertise to run tests and maintain recommendation logic. US mid-market and enterprise brands with large catalogs and multi-channel ambitions should put it on their shortlist. Smaller companies, or teams that mainly need simple pop-ups or basic A/B testing, will likely get better value from lighter, self-serve tools.
Resources
Resources & Documentation
Detailed materials for deeper evaluation
Experience OS Overview
Product overview of the unified personalization platform and its modules
Experience APIs
Documentation hub for server-side, headless and omnichannel personalization
Shopping Muse Product Page
How the generative AI shopping assistant works and where it fits
Gartner Magic Quadrant for Personalization Engines
Dynamic Yield's distribution of the Gartner Leader report
Case Studies Library
Customer results across retail, travel, grocery, iGaming and financial services
State of Personalization Maturity Report
Annual research report benchmarking personalization maturity across brands
Knowledge Base Release Notes
Ongoing product changes and new feature announcements
Shopify App Listing
Installation details for the Dynamic Yield by Mastercard Shopify app
What to Know
What to Know Before Buying
-
A product catalog feed and consistent event tracking are prerequisites for recommendations -
Headless, app and server-side use cases require engineering work against the Experience APIs
-
Plan for ongoing ownership by a personalization or CRO lead after launch
-
Confirm connectors for your CDP, email service provider and analytics stack during evaluation.
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Pricing typically scales with traffic, so confirm how overage and new-site additions are billed.
-
Ask whether pricing is based on sessions, page views or revenue.
-
Run the old and new tools side by side briefly to benchmark performance before cutover.
-
Negotiate traffic tiers, renewal caps and exit terms up front.
Alternatives
Compare Alternatives
See how Dynamic Yield stacks up against competitors
Optimizely leads with experimentation and content management. Dynamic Yield goes deeper on ecommerce recommendations, merchandising and AI-driven product discovery.
Detailed feature comparison, pricing analysis, and user reviews
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FAQ’s
Frequently Asked Questions
Common questions about Dynamic Yield
Dynamic Yield does not publish pricing. Every deal is a custom quote, usually an annual or multi-year contract priced on traffic volume and the modules you choose. Third-party pricing sites put it in the enterprise range, well above self-serve personalization tools.
Mastercard has owned Dynamic Yield since April 2022, when it completed the purchase from McDonald's. McDonald's had bought the company in 2019 in a deal reported at about $300 million.
Experience OS is the name for the unified platform. It brings together audience targeting, personalization, recommendations, experimentation and messaging in one workspace, with shared data and decisioning.
Shopping Muse is Dynamic Yield's generative AI shopping assistant, announced in November 2023. It turns conversational shopper requests into recommendations from the retailer's catalog, and Bergzeit reported three times more conversions with conversational AI discovery.
Yes. It supports email product recommendations and triggered messages, and it delivers personalization to native apps and other channels through its Experience APIs.
Usually not. Enterprise pricing, the need for high traffic to reach test significance, and the effort to set it up make it better suited to mid-market and enterprise brands.
A tag-based deployment with a product feed on a standard storefront can go live relatively quickly. Headless, app and multi-market rollouts that need API work and data integration take longer and need engineering resources.
Common alternatives include Adobe Target, Optimizely, Salesforce Marketing Cloud Personalization, Insider One, Nosto, Monetate and VWO. The right choice depends on your existing stack, budget and whether you need recommendations or mainly testing.