AudienceLabs Pixel Data Pipeline
A normalization and deduplication pipeline converting high-volume website visitor exports into CRM-ready lead records.
The workflow was built to make event and enrichment data usable by sales and campaign systems without losing source detail or creating duplicate contacts.
Primary phone and email values are selected deterministically while additional values are retained in separate fields. Formatting characters, accidental concatenation and leading-country-code variations are normalized before matching.
Personal location, company, domain, LinkedIn, age and net-worth attributes are mapped into explicit destination fields rather than passed through as an unstructured export.
UUID-based deduplication prevents repeated pixel events from becoming repeated CRM records.
Visitor exports contained repeated identities, inconsistent phone formats, multiple emails and phones in single fields, and company and skip-trace data that could not be imported safely as-is.
The pipeline deduplicates by UUID, normalizes phone numbers, selects primary values, preserves additional contacts, maps personal and company attributes, and outputs one predictable CRM-ready schema.
Outcomes without invented claims
- 01Produced a consistent CRM-ready schema from irregular visitor and enrichment exports.
- 02Prevented repeated event rows from creating duplicate lead records.
- 03Preserved additional phones and emails without contaminating the primary contact fields.
What makes this publishable
- Field mapping specification
- Normalization logic
- UUID deduplication rules
- Primary and additional contact handling
- AudienceLabs
The project turns noisy event exports into controlled identity data that downstream CRM, scoring and outreach workflows can trust.