Introducing New Predictive Metrics to Analyze Store Visit Behavior

Euclid leverages proprietary machine learning and large data set to predict which customers will visit a physical location.

Online-Offline Attribution and Store Visit Retargeting

Today’s mobile-first customer provides the opportunity to identify every visitor who walks in your door, understand what drove that visit and retarget to influence a purchase.

As seen in

  • In-Store Acquisition

    Easily collect in-store identity and behavior to enhance your customer database and advertising audiences.

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  • Behavioral Targeting

    Segment audiences and personalize campaigns based on in-store behavior for better performance.

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  • Omnichannel Attribution

    Directly attribute the impact of digital efforts on an in-store visit, regardless of purchase.

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How it works

  • ​Onboarding

    Euclid ingests your data — from transaction to loyalty program — and collects unique first-party data from your physical locations.

  • Matching

    The data sets are matched and enriched by Euclid’s advanced algorithms to deliver a dynamic map of identified visitors with offline behavior.

  • ​Activation​

    Using Euclid’s open API and integrations, activate the identified visitors for retargeting and attribution through your existing marketing stack.

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Euclid's solution helps us understand our customers on a new and more meaningful level by illuminating an untapped, high-intent audience for us.

Steve Miller -VP, Marketing and Business Development
Joann Fabric and Craft Stores

With Euclid, we are able to drive value from our existing Wi-Fi by providing meaningful in-store shopper metrics in an easily consumable way. This allows us to innovate in ways we never thought possible.

Nathaniel Polky -Director of Information Technology
McLendon Hardware