Connect Magento 2 (Adobe Commerce) first-party customer and behavioral data with Zeotap, a privacy-focused CDP, to resolve identity and activate consent-aware audiences across ads, Email, and analytics.
• Customer, order, and behavioral events from Magento (Adobe Commerce) are exported to Zeotap via API or batch feeds, with a defined schema and field normalization.
• Identity resolution in Zeotap links email, phone, and device identifiers into a unified customer profile, while keeping identifier collection and storage scoped to configured policies.
• Consent and preference attributes are mapped to Zeotap consent flags, and audience eligibility is computed using consent-aware rules per region and channel.
• Delta sync logic sends only created or changed records for customers, orders, and attributes, reducing duplicate processing and keeping profiles current.
• Catalog and transaction metadata (SKU, category, price, currency, and timestamps) is attached to events for segmentation and downstream attribution modeling.
• Activation audiences are exported from Zeotap to connected ad and Email platforms, with audience versions logged for traceability and rollback support.
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We map Magento customer, order, and onsite event data to Zeotap identities and attributes, then stream or batch it via API or exports. The result is a governed first-party feed you can segment without manual files.
Yes – consent signals can be passed with events and profiles, so Zeotap builds audiences only from permitted data. This helps keep activation aligned with regional privacy rules and your CMP setup.
Most projects use customer attributes, purchase history, product interest, cart behavior, and category affinity. We also add custom events for filters, searches, and key funnel steps when needed.
Yes – Zeotap segments can be pushed to your connected channels for acquisition, retargeting, suppression, and lifecycle messaging. You get one audience definition reused across platforms, with less mismatch.
We separate store views, currencies, and locales in the data model, then standardize shared attributes for cross-market reporting. This keeps segmentation accurate while still allowing market-specific targeting.