How to measure contact database quality

"High quality" means nothing unless it is measured. These are the measures that matter, how we report them, and how to check them yourself.

1. Coverage (completeness)

Percentage of rows where a field is filled in. Formula: non-empty values ÷ total rows. We compute this for every column of every pack automatically. Try it on any file with our CSV field analyzer.

2. Validity

Filled in is not the same as correct. Check format validity:

• Phone numbers parse to a valid number for the country (see phone normalisation).
• Emails match the basic pattern name@domain.tld.
• Postcodes match the national format.

3. Uniqueness

Exact duplicate rows are counted by our scanner and published per dataset. Near duplicates (same business, slightly different spelling) need normalised keys such as E.164 phone numbers or website domains.

4. Consistency

Look for mixed formats within a column (dates as 01/02/2026 and 2026-02-01, phone numbers with and without country codes). Inconsistency slows every import.

5. Accuracy

Only real-world checks can establish accuracy. Sample rows and verify them against primary sources. No seller can honestly promise 100% accuracy for business contact data, and we do not.

A quick scorecard