GDPR compliance isn't an option. It's our foundation.

A GDPR approach examines purpose, legal basis, transparency and individual rights. Professional information may still be personal data; public availability does not remove those obligations.

Establish a procedure with your data-protection lead covering access, retention, deletion, transparency and suppression lists. Review supplier contracts and possible transfers, not only the advertised hosting country. Prepare a limited test with three situations: a known profile, an incomplete profile and an ambiguous case. Record starting information, expected outcomes and fields actually obtained. This prevents judging the service from one unusually favorable record. The examples here describe a working method, not performance evidence. When information is missing, preserve that state instead of replacing it with an assumption. Assign responsibility for checking results before commercial use. Use the same criteria across all cases so differences reflect the data rather than changes in the test procedure.

This page provides educational guidance, not individualized legal advice. For an operational decision, consult official texts and your supervisory authority’s recommendations, then have a qualified person assess your situation. After testing, compare outcomes with your team’s current process. The main criterion should match the need described here: list relevance, address accuracy, match quality or transfer reliability. Choose an observable indicator using consistent scope and timing. Document exceptions instead of removing them from the assessment. Before expanding, confirm capabilities and actual terms in the application. Illustrations do not establish contractual commitments, legal guarantees or service levels. Keep personal information only when required for a defined purpose, and decide how corrections or objections will reach every system where the record is used.

Then prepare the next action: review a profile, complete a field, check an address or test an integration. Related sections help separate these steps. Careful preparation makes outcomes easier to interpret and avoids confusing the quality of an individual data point with the success of an entire campaign. For “B2B data and GDPR”, also ask which observations would confirm or challenge your initial hypothesis. This connects preparation with a verifiable decision and prevents generalizing results beyond their context. Review findings with the people involved before changing your process, and distinguish measured improvements from assumptions that still require evidence. Keep the evaluation transparent, specific and reproducible for every stakeholder involved. A documented review makes comparisons easier and preserves assumptions when requirements change. Use relevant observations rather than generic promises to support the decision.