Dynamic Yield Adds Identified Offline Purchase Data Ingestion Capability

Dynamic Yield, a marketing personalization platform provider, today released Identified Offline Purchase Data Ingestion, allowing companies to import lists of purchases done offline (e.g. in physical stores) and match these records with online identities. This new capability is available in addition to the platform's Data Loader feature, which already allows customers to onboard CRM data, personally identifiable information, content feeds, and more.

With this capability, Dynamic Yield brings offline data online to improve targeting and the quality of recommendations, providing consumers with a shopping experience that reflects their activity in-store and online.

"Today's customers are traversing digital and physical shopping experiences and expect retailers to remember their preferences and past purchase behavior no matter where the transaction occurs," said Liad Agmon, CEO of Dynamic Yield, in a statement. "Fluidity of online and offline data, therefore, is key to getting it right, and our new capability has made it possible to influence customer action on a whole other level."

Offline purchase data can be used to do the following:

• Create audiences based on offline purchases, such as shoppers who previously bought a certain number of items in-store and target them with relevant offers to capture sales online;
• Exclude products already purchased in-store from online recommendations;
• Augment the data used in recommendation algorithms (e.g. Bought Together and Popularity) by using in-store data of items that are often purchased together;
• Combine offline purchase data with online shopping behavior to create a rich profile of preferences and interests for more granular targeting;
• Target identified customers and personalize email based on offline data, such as by highlighting complementary items to those they have recently purchased in-store; and
• Export user-level data for third-party applications, such as Facebook ads, and retarget users based on their offline purchase history.