![]() Individual user scores are normalized, using the entire site’s traffic as a baseline. The score sums up the total interactions for each value, favoring recent interactions and high-intent interaction types by giving more weight to real-time activities, purchases, and adding to the cart. We then calculate an affinity score for each attribute value. Building a user affinity profileĪt the user level, for each type of interaction, we collect and aggregate all the product attribute values that the user interacted with. Our affinity-based audience condition provides you with the tools to build on the user’s affinity and create highly-personalized experiences based on their personal preferences.Īfter these audiences are created, they can be used for targeting and exporting the audiences to third-party platforms. Products users interact with, particularly their attributes (color, brand, style) and attribute values (red, Nike, t-shirt) teach us about their preferences.Ĭombining product attributes with interaction types, while taking into account the recency of the interaction, helps you identify user preferences overall and in real time.
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