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Documentation Index

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Data enrichment appends additional context — customer metadata, geographic data, and behavioral attributes — to raw events and identity profiles before they reach destinations or your analytics warehouse.
Enriched events carry more match keys, which directly raises Event Match Quality (EMQ) scores on platforms like Meta — turning a 5 into an 8 without changing your tracking setup.

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Why It Matters

A raw event captured at the edge contains the basics: URL, timestamp, IP address, user agent, and whatever identifiers the visitor volunteered. That’s enough to record that something happened, but it’s not enough for downstream systems to do their best work. Conversion APIs score events based on match key completeness. An AddToCart event with only an IP address and user agent will match poorly on Meta. The same event enriched with hashed email, phone number, city, and zip code matches at a significantly higher rate — improving both reported conversions and algorithm optimization. Enrichment also improves your own analytics. Customer lifetime value calculations become more accurate when events carry purchase history and order frequency. Segmentation becomes more granular when profiles include geographic and behavioral attributes. Every system downstream of enrichment — forwarding, attribution, reporting — benefits from richer input data.

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How It Works

Upstack Enrichment operates at the Enrich stage of the data pipeline, after identity resolution and before forwarding or warehouse storage. Enrichment draws from three sources:
  • Identity graph — Once Upstack ID resolves a visitor, Enrichment pulls all known identifiers associated with that profile (email, phone, address) and attaches them to the current event. An anonymous PageView gains match keys from a previous checkout on another device.
  • Shopify customer data — Order history, customer tags, total spend, and order count are synced from Shopify and attached to resolved profiles. These fields feed both forwarding destinations (as customer parameters) and analytics (for cohort and LTV calculations).
  • Event context — Geographic data derived from IP (city, region, country, postal code), device classification (mobile, desktop, tablet), and referrer parsing (UTM parameters, landing page) are appended to every event at processing time.
Enrichment is automatic. Once Upstack Pixel is capturing events and Upstack ID is resolving identities, every event flowing through the pipeline is enriched before it reaches any destination or warehouse table.

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Key Terms

TermDefinition
Match keyA hashed identity field (email, phone, address) used by ad platforms to link a conversion event to a user profile.
Customer metadataAttributes from Shopify (total spend, order count, customer tags) attached to a resolved identity profile.
Event contextNon-identity attributes appended at processing time: geography, device type, UTM parameters, referrer.
Profile enrichmentThe process of augmenting an identity graph node with additional data from first-party and platform sources.
EMQ (Event Match Quality)Meta’s score reflecting how well an event’s identity signals can be matched to a user — directly improved by enrichment.

Conversion API Forwarding

See how enriched events improve signal quality when forwarded to ad platforms.

Identity Resolution

Understand the identity layer that enrichment depends on.