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Unlock 1:1 experiences with Affinity-based personalization

Leverage user affinity profiles to algorithmically match each person with personalized recommendations, product offers, and content.
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From complex user signals into highly-tailored experiences

As visitors interact with a brand, we detect, score, and calculate an affinity profile which can be accessed and used to serve deeply personalized 1:1 experiences.
Identify affinity and capture changes in preferences over time
Let Dynamic Yield automatically collect, analyze, and calculate affinity data on your customers’ past preferences, offline purchase history and real-time interactions with your brand. Affinity Scores are calculated for each attribute value, summing up the total engagement for each value, while favoring recent interactions and preference indicators by giving more weight to real-time activities and high-intent engagement types.
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Build and analyze affinity-specific audience segments  
Create dynamic audiences based on attributes such as category, brand affinity, price range, topic, color, and more. Breakdown any campaign report based on affinity segments, and have Dynamic Yield’s Predictive Targeting continuously analyze and identify opportunities to serve the most relevant content for each affinity audience segment.
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Recommend relevant items based on unique customer profiles
Leverage machine learning algorithms to make recommendations based on detected product or content affinities. Our Affinity-Based Recommendation Strategy uses the affinity profile of each user to retrieve a ranked list of items predicted to be most relevant to the user.
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Create hyper-relevant targeting campaigns according to affinity
With Affinity-based conditions, visitors with preferences to specific brands, colors, categories, and other attributes from the metadata can be targeted without having to build the audience manually.
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Enhance affinity profiles with predicted intent
Take affinity profiling and recommendations a step further with an advanced neural network algorithm that predicts intent before it’s shown on the page.