Data reliability via server-side Data Quality
Control your server-side flows with Event Specification and Data Cleansing. Ensure perfect, enriched, and compliant data for all your destinations.
1. Business Value: Guarantee actionable and certified data
The value of your tools (Analytics, CRM, Advertising) depends directly on the quality of the data they receive. Server-side without control creates a ‘black box’; reliability allows you to open this box and guarantee the integrity of each hit.
Truth-based decisions: Eliminate analytical biases caused by poorly formatted or missing data that skew your reports.
Frictionless interoperability: Send unique, standardised data to all your partners. If a supplier changes their format, you can correct it on the server without touching the site code.
Reduction of technical debt: Data cleansing allows you to fix collection errors immediately, avoiding complex correction work on your website or application.
2. Implementation methodology
Step A: Definition of the expected schema (Event Specification)
Create the repository for your tagging plan at the server level. For each event (e.g. purchase, login, page_view), the mandatory properties and the expected data type.
Action: Configure your schemas in the Data Quality module.
Documentation: Event Specification.
Step B: Monitoring and Diagnosis (Data Quality)
The system checks each incoming event. The Data Quality report immediately identifies sources that send non-compliant or undocumented data.
Action: Monitor the health score of your server-side sources.
Documentation: Rapport Data Quality.
Step C: Real-time Correction (Data Cleansing)
If an anomaly is detected (e.g., a missing currency or an incorrect date format), do not reject the data. Use Data Cleansing to normalise it before sending.
Action: Apply transformation rules to correct, enrich, or anonymise properties on the fly.
Documentation: Data Cleansing.
Step D: Proactive Alerting
Set up critical alerts. Be notified as soon as a server-side source starts sending invalid data, allowing you to take action before your destinations (Analytics, CRM, Ads) are impacted.
3. Typical use cases
Analytics & Ads standardisation: Ensure that the purchase event sent to GA4 and Meta CAPI contains exactly the same amounts and currencies thanks to a unique server-side cleansing rule.
On-the-fly data enrichment: When a customer ID arrives at the server, retrieve additional information (segmentation, loyalty) to enrich the hit before its final distribution.
Filtering and security: Use Data Cleansing to automatically mask sensitive information (PII) detected in your server flows in order to comply with your partners' privacy policies.
Need help making your data flows more reliable?
Data Quality Server-Side transforms your data flow into a strategic and certified asset. Our experts help you build your schemas and cleansing rules for total control over your data collection. Contact our support team: [email protected]
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