What are Data Quality Dimensions for Contact Email

Learn how Delpha evaluates email fields using six data quality dimensions: completeness, validity, uniqueness, consistency, accuracy, and timeliness.

Email analysis relies on the standard Contact.Email field

Understanding Delpha’s 6 Data Quality Dimensions for Email

Delpha evaluates each field using 6 key data quality dimensions. Below is how each dimension applies to email fields, helping users interpret scores and drive cleanup efforts.

Data Quality Dimensions Explained

Completeness

Question: Do I have an email?

• If no email is present, this dimension will be marked as incomplete.

	Present	True	A value is provided.	Present: an email address has been provided.
	Missing	False	Value is blank or null.	Missing: no email address has been provided.

Validity

Question: Is the email address safe and valid?

• Delpha checks if the email can safely be used.

• ⚠️ Depends on Completeness:

  • If the email is incomplete, then:

    • Validity = Invalid

    • Qualification = Invalid

Icon	Label	D Email Validity	D Email Qualification	Logic	Explanation
	Safe	Valid	nominative@pro	This is a verified professional email assigned to a specific individual. The address was successfully pinged (reached) by the server.	Safe: The email address exists and is expected to be delivered successfully without issues.
	Risky	Valid	catchall@pro Unknown rolebased@pro nominative@perso catchall@perso	Results are inconclusive. The server may be a "catch-all" (accepting all mail) or a personal email address. A server ping may be unreliable or blocked.	Risky: The address could not be fully verified. There is a risk of a bounce or low engagement.
	Do Not Use	Invalid	Invalid spamtrap@pro	The email is malformed/incomplete, it failed the server ping, or it has been flagged as a known spam trap.	Do Not Use: This address does not exist or is dangerous. Sending to it will result in a hard bounce or damage your sender reputation.

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Uniqueness

Question: Is the email unique in your Salesforce database?

• Duplicate email addresses across contacts may flag this dimension as problematic.

	Unique	True	Uniqueness = 1	Unique: this email address is unique on your database
	Not unique	False	Uniqueness > 1	Not unique: other contact(s) have the same email address

Consistency

Question: Does the domain of the email match the company email domain?

• Validates that the contact’s email domain matches the primary domain of the linked Account record.

• ⚠️ Depends on Completeness:

  • If the email is incomplete → Consistency = False

	Consistent	True	Consistent: the email address domain is the same as the company email domain.
	Inconsistent	False	Inconsistent: the email address domain differs from the company email domain.

Accuracy

Question: Does the email match expected patterns with a high confidence score?

• Based on Delpha’s AI model and pattern matching logic.

• ⚠️ Depends on Completeness and Validity:

  • If the email is incomplete or invalid → Accuracy = No

	Accurate	Ok	The email is valid and matches the email pattern of the company.	Accurate: the email address seems to be the correct profession email of the contact
	Maybe inaccurate	Odd Format	The email is valid but doesn't matches the email pattern of the company.	Maybe: The format of the email address does not correspond to the standard email address format for this company
	Inaccurate	No	The email is empty or invalid	Inaccurate: this is not a correct email

Timeliness

Question: Is the email still active or in use?

• Measured by whether an email has been received from this address in the last 30 days.

• Helps determine if the contact data is still current.

	Up to Date	Date of last received email <= 30 days	Up to Date: you received an email from this address recently
	Outdated	Date of last received email > 30 days	Outdated: you didn't receive any email from this address in the past month