Connect Salesforce with mParticle to govern commerce events with identity resolution, data quality checks, and audience sync, then route trusted data across web, app, analytics, and marketing tools.
• Customer profile attributes and consent flags from Salesforce are mapped to mParticle user attributes and identity fields for unified profiles.
• Web and app commerce events are ingested into mParticle, validated against event taxonomy rules, and enriched with Salesforce identifiers where available.
• Identity resolution links known and anonymous identifiers using deterministic matching, producing a consistent user key for downstream routing.
• Data quality rules flag, block, or quarantine malformed events and unexpected attribute values, with logs available for auditing and debugging.
• Audience definitions are evaluated in mParticle and synced as segments to connected marketing and analytics destinations, with membership updates sent on change.
• Event streams are routed from mParticle to multiple endpoints in parallel, with destination-specific field mappings and filtering applied per output.
• Delta-style processing sends only updated profiles, changed audience memberships, and new events, reducing duplicate writes across systems.
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We map key Salesforce objects and identifiers into mParticle’s identity graph, then define merge rules for known and anonymous users. This keeps profiles consistent across web, app, and downstream tools.
Typical payloads include customer identifiers, lifecycle fields, order and product details, and key status changes like refunds or returns. The exact spec depends on your attribution model and audience use cases.
We align Salesforce fields and event payloads to an agreed taxonomy, then use mParticle governance rules to prevent drift. That way, teams stop “fixing reports” every time a field changes.
Yes, mParticle can build and sync audiences using resolved identities, while suppressing duplicates and stale profiles. We also validate match rates and consent rules before scaling spend.
Common checks include required-field validation, schema validation, and anomaly monitoring for volume spikes or missing events. It reduces broken funnels and misfiring conversions in downstream platforms.






