Platform XDocumentationWelcome to success

1. Data quality: the foundation of success

Data quality is the most important factor for success with Google Customer Match. A high matching rate depends directly on completeness, standardisation and compliance with consent rules.

Why is this crucial?

Google Customer Match relies on recognising users via their personal information (email, telephone number, address). If this data is incomplete or incorrectly formatted, it will be ignored by Google, drastically reducing the size of activatable audiences and campaign performance.

Best practices to apply:

1.1 Valid consent (GDPR)

  • Legal and technical obligation: Google requires that data be collected with explicit consent.

  • Recommended action: Verify that each profile sent is opt-in for targeted advertising.

  • Tip: Use a ‘granted’ field in Commanders Act to filter compliant profiles.

1.2 Profile completeness

  • Avoid profiles with only an email address: they are often ignored.

  • Recommended fields to maximise matching:

    • Email (mandatory)

    • Telephone in E.164 format (+33 6...)

    • First and last name

    • Full postal address

    • Postcode

    • Country in ISO 2-letter format (e.g. FR)

  • Why? The more complete the mapping, the more Google can cross-reference information and recognise the user.

1.3 Format standardisation

  • Email: convert to lowercase before hashing.

  • Telephone: use the international E.164 format.

  • Country: use the 2-letter ISO code (FR, ES, IT, etc.).

  • Technical tip: apply these rules before SHA-256 hashing to avoid rejections.

1.4 Cleaning and deduplication

  • Remove duplicates to avoid import errors and improve quality.

  • Enable Fuse in Commanders Act for ID reconciliation.

  • Check for null or generic values (e.g. ‘N/A’, ‘Unknown’).

To be avoided at all costs:

  • Incomplete profiles (email only).

  • Incorrect formats (e.g. telephone number without international dialling code).

  • Missing columns or unclosed quotes in CSV files.

  • Sending data without valid consent.

💡 Direct impact: A clean and complete database can increase the matching rate from 20% to over 80% (internal benchmarks), particularly on Gmail.

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