How Redpoint enables standardization | Redpoint Documentation

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This page illustrates how Redpoint enables standardization.

Schema registry & enforcement: Redpoint defines canonical tables and objects, ensuring strict adherence to types, nullability, and required fields during data ingestion. This process is vital as it allows for the rejection or quarantine of non-compliant data, maintaining the integrity of the data ecosystem.
Data quality rules: Redpoint uses a reusable pattern library with standards for formats like email syntax, phone numbers in E.164 format, and ISO country codes. This library includes mechanisms for block/warn actions and automatic remediation to quickly resolve data quality issues.
Reference data services: Redpoint offers a centralized management system for lookups and code sets, which are versioned and audited for accuracy and reliability. This centralization streamlines maintaining reference data across various applications and systems.
PII classification: The platform applies column-level sensitivity flags that enable data masking and enforce role-based access controls, ensuring the careful handling of personally identifiable information (PII) in compliance with data protection regulations.

Match policies: Redpoint uses deterministic matching policies, including hashed email addresses and loyalty IDs, along with optional probabilistic features. Organizations can configure these policies to set specific thresholds and cascades for optimizing the matching process.
Survivorship: The system applies prioritized source-of-truth logic for each attribute, ensuring the most accurate and current information is maintained. For example, it prioritizes the latest non-null email from trusted sources, enhancing the reliability of customer records.
Golden Record outputs: Redpoint produces durable customer IDs and stitched attributes for analytics and activation processes. This provides organizations with a comprehensive view of their customers, enabling more effective engagement strategies.

Purpose-based consent standard: Redpoint stores consent with its purpose, channel, jurisdiction, and proof. This information is vital for decision-making and ensures compliance with legal and regulatory requirements.
Preference model: The platform uses a standardized model for channel and frequency preferences, integrated into eligibility decisions. This standardization streamlines communication strategies and improves customer satisfaction.

Canonical event taxonomy: Redpoint establishes a consistent naming convention for events, such as commerce.purchase and site.view, along with required fields like event_ts in UTC ISO-8601 format, customer_id, and source_system. This approach also allows for extensible attributes, enhancing flexibility in event tracking.
Normalization and identity binding: The system assigns Golden IDs to events, effectively managing transitions from anonymous to known identities. This capability is crucial for maintaining accurate customer profiles throughout the customer journey.
Quality checks: Redpoint implements rigorous quality checks, including handling late and duplicate events, clock-skew tolerance, and the use of idempotency keys. These measures ensure that the collected data is accurate and reliable.

Channel adapters: The platform manages file and API contracts, specifying field sets, order, types, encodings, and delimiters. Automatic pre-flight validation provides actionable error reporting to resolve discrepancies before data activation.
UTM & parameter standards: Redpoint enforces consistent naming conventions for campaign, channel, and creative parameters, essential for maintaining clean and actionable analytics. This standardization enhances decision-making and performance tracking.

Asset catalog & tagging: Redpoint maintains a comprehensive asset catalog detailing owners, sensitivity levels, lifecycle stages, jurisdictions, service level agreements (SLAs), and data lineage. This catalog is essential for effective data asset management and compliance.
Promotion gates (Dev→Test→Prod): The platform includes promotion gates that ensure schema conformance, conduct PII and consent checks, and perform regression tests on segmentation outputs. It also provides alerts for volume and variance, which are critical for operational integrity.
Audit & versioning: Redpoint uses semantic versioning for schemas and rules, maintaining a complete change log that records who made changes, what was altered, and why. This transparency is crucial for governance and accountability in data management.