marketing_ops · ecommerce · workflow
Dynamic Yield drives 40% email RPM increase with affinity-based personalized recommendations
The marketing team lacked access to AI-based targeting and was manually handpicking products for email recommendation widgets, making it impossible to deliver customer-centric campaigns tailored to individual user interests at scale.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Omnichannel event capture
Omnichannel events capture new and returning user activity to begin building a single view of the customer.
Tools used
Dynamic YieldUser Affinity algorithm
Outcome
Automating experience delivery with machine learning recommendation algorithms eliminated hours of manual work for the merchandising team and produced a 40% increase in revenue per thousand impressions from email campaigns.
Results
Cost replaced40%
Grounding & classification
Source type: vendor customer story
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personalizationrecommendation systememailproduct catalogmetric backedtools describedvendor confirmedworkflow describedecommerceemployee productivityrevenue increasetime savedvendor customer storyecommerce opsmarketing opsdata sync enrichment