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: Is a value provided for the field? If no email is present, this dimension will be marked as incomplete.

Complete

Completeness = true

A value is provided

Complete: an email address has been provided

Missing

Completeness = 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

Safe

Validity = “Valid” and

Qualification=nominative@pro

The email is nominative pro and could be pinged

Safe: the email address has a high likelihood of successful delivery and engagement

Risky

Validity = “Valid” and

Qualification in:

  • catchall@pro

  • Unknown

  • rolebased@pro

  • nominative@perso

  • catchall@perso

Depending on the qualification, the email was pinged, or does not need to be pinged.

Risky: the email address carries some level of risk of bouncing or being flagged as spam

Invalid

Validity = “Invalid” or

Qualification in:

  • Invalid

  • spamtrap@pro

Means that the email is incomplete, could not be pinged, or is a spamtrap

Invalid: the email address is invalid, undeliverable, or non-existent


Uniqueness

Question: Is the email unique in your Salesforce database? Duplicate email addresses across contacts may flag this dimension as problematic.

Unique

Uniqueness = 1

Unique: this email address is unique on your database

Missing

Uniqueness > 1

Not unique: other contact(s) have the same email address

Consistency

Question: Does the domain of the email match the related Account domain?

  • Ensures the email logically belongs to the company linked to the record.

  • ⚠️ Depends on Completeness:

    • If the email is incomplete → Consistency = False

Consistent

Domain is correct

Consistent: the email address domain is the correct one for this company

Inconsistent

Domain mismatch

Inconsistent: the email address is missing, or 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

Accuracy = “Ok”

The email is valid and matches a pattern with a high score for this account.

Accurate: the email address seems to match the current contact

Odd Format

Accuracy = “Odd Format”

The email is valid and matches a pattern with a low score for this account.

Odd Format: the format of the email address does not correspond to the standard email address format for this company

Invalid

Accuracy = “No”

The email is empty or invalid

Invalid: the email is either missing or invalid, so it cannot be accurate

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

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