Dynamic Yield

Create experiences as unique as your customers

· for enterprise

Dynamic Yield runs algorithmic personalization across web, app, email, and ad touchpoints from a single decisioning layer, pairing product recommendations, A/B testing, and audience segmentation with a predictive engine that adapts to session behavior in real time. Owned by Mastercard and aimed at enterprise retail, QSR, and financial services teams, it suits CMOs and growth leaders running high-traffic sites who need one experimentation backbone instead of separate testing and recommendation vendors.

> pick this if

Pick this if you're an enterprise retail, QSR, or financial services team running high-traffic web and app properties that need one decisioning layer for recommendations, testing, and segmentation — with a dedicated CRO or personalization owner to run it.

> look elsewhere if

Look elsewhere if you're under ~$20M GMV, lack a dedicated experimentation owner, or want transparent self-serve pricing and fast time-to-value — Dynamic Yield is a six-figure enterprise commitment with a multi-month implementation.

> Dynamic Yield is built for

food & beverage
DTC apparel & fashion
physical retail & omnichannel
marketplaces

> what it does for ecommerce

Deploy personalized recommendations across web, app, email, and push channels
Run A/B and multivariate tests against revenue and engagement KPIs
Segment audiences using behavioral, contextual, and CRM signal inputs
Predict affinity and intent with machine learning decisioning models
Orchestrate cross-channel experiences from one centralized campaign interface

> how you'd use it

Enterprise fashion retailer, $200M–$500M GMV, 15-person growth and merchandising team
Consolidating a legacy stack of Optimizely for testing plus a separate recommendations vendor into one decisioning layer across web and iOS app, with experiments tied to category-level revenue KPIs
→ Single experimentation backbone retires two contracts, and homepage/PDP recommendation tests lift revenue-per-session in the 3–8% range once the predictive models warm up on 90 days of behavioral data
Global QSR chain, $1B+ system sales, 8-person digital product team plus agency support
Personalizing menu merchandising in the ordering app by daypart, weather, and store-level inventory, with A/B tests running per market to validate basket-builder prompts before rollout
→ Upsell prompts tuned by session context drive measurable AOV gains per market, and the team runs 40+ concurrent tests without engineering tickets for each variant
Mid-market beauty DTC on Shopify Plus, $30M–$60M GMV, 4-person CRO and lifecycle team
Running onsite recommendation strips, exit-intent offers, and email product blocks from one tool, coordinated with Klaviyo audiences and a headless storefront
→ Replaces three point solutions (recs, onsite testing, email recs), though the team needs a dedicated CRO owner to justify the six-figure floor and keep the experiment pipeline full

> Dynamic Yield use cases

> alternatives to Dynamic Yield in our index

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