Free Email Validity Scoring for D365 Leads (MX Check + Simple Heuristics)

Free Email Validity Scoring for D365 Leads (MX Check + Simple Heuristics)

Inbound leads are messy. Before a rep wastes time, you want a fast signal: is this email probably real, and is it likely tied to an actual organization?

This guide shows how to build a 100% free email validity confidence check for Dynamics 365 / Dataverse Leads using Power Automate. It:

• Checks email format

• Verifies the domain can receive email (MX record lookup)

• Flags disposable domains, free email domains, and role-based inboxes

• Produces a 0 to 10 confidence score

• Updates a Lead choice field:

  • 8 to 10: Likely valid

  • 5 to 7: Risky / needs review

  • 0 to 4: Likely invalid or low quality

What this does (and doesn't do)

This approach is designed for triage, not perfect deliverability verification.

Great for catching: fake domains, typo domains, disposable emails, low-quality submissions.

Not guaranteed to detect: catch-all inboxes, spam traps, "mailbox exists" certainty.

If you need mailbox-level certainty, you'll eventually pair this with a paid validation API. But for quick qualification, this free method delivers a ton of value.

Prerequisites (Dataverse)

On the Lead table, create a Choice field:

kpi_emailvalidityconfidence (Display name: Email Validity Confidence)

Options and values (your current values):

• Likely valid = 846280000

• Risky / needs review = 846280001

• Likely invalid or low quality = 846280002

Recommended but optional for explainability:

• kpi_emailvalidityscore (Whole number)

• kpi_emailvalidityflags (Single line or multiple lines of text)

Scoring model (0 to 10)

Start at 10, then subtract:

• 6 if domain has no MX record

• 3 if domain is disposable

• 2 if domain is a free email provider

• 1 if local part is role-based (info@, sales@, etc.)

• Score = 0 if email fails basic format checks

Then map to confidence:

• 8 to 10 produces Likely valid

• 5 to 7 produces Risky / needs review

• 0 to 4 produces Likely invalid or low quality

Build the flow: "Lead - Email Validity Confidence (Free DNS)"

1) Trigger

Dataverse, When a row is added, modified or deleted

• Change type: Added

• Table: Leads

• Scope: Organization

Optional: filter to only CI form leads (if you have a "lead source" indicator).

2) Initialize variables

Create these variables:

• varScore (Integer) = 10

• varEmail (String) = Lead emailaddress1

• varDomain (String) = toLower(last(split(variables('varEmail'), '@')))

• varLocal (String) = toLower(first(split(variables('varEmail'), '@')))

• varFlags (String) = empty

3) Basic format gate

Condition expression:

and(
  contains(variables('varEmail'), '@'),
  contains(variables('varDomain'), '.'),
  greater(length(variables('varLocal')), 0),
  greater(length(variables('varDomain')), 3)
)

If No:

• Set varScore = 0

• Append Invalid format; to varFlags

• Skip to the update step

4) Free MX lookup (DNS over HTTPS)

Add an HTTP action:

GET

https://dns.google/resolve?name=@{variables('varDomain')}&type=MX

Parse the JSON response (Parse JSON action) using this schema:

{
"type":"object",
"properties":{
"Status":{"type":"integer"},
"Answer":{
"type":["array","null"],
"items":{
"type":"object",
"properties":{
"name":{"type":"string"},
"type":{"type":"integer"},
"TTL":{"type":"integer"},
"data":{"type":"string"}
},
"required":["name","type","TTL","data"]
}
}
}
}

Condition expression to check MX:

and(
  equals(body('Parse_JSON')?['Status'], 0),
  greater(length(coalesce(body('Parse_JSON')?['Answer'], createArray())), 0)
)

If No:

• varScore = max(0, sub(varScore, 6))

• Append No MX;

5) Disposable / free / role-based checks (free lists)

Add 3 Array variables.

varDisposableDomains:

[
"mailinator.com",
"guerrillamail.com",
"10minutemail.com",
"tempmail.com",
"yopmail.com",
"trashmail.com",
"getnada.com",
"dispostable.com"
]

varFreeDomains:

[
"gmail.com",
"yahoo.com",
"outlook.com",
"hotmail.com",
"icloud.com",
"aol.com",
"proton.me",
"protonmail.com",
"live.com"
]

varRoleLocals:

[
"info",
"sales",
"support",
"help",
"admin",
"contact",
"billing",
"accounts",
"hello",
"inquiries"
]

Then conditions:

Disposable?

contains(variables('varDisposableDomains'), variables('varDomain'))

If Yes: -3, flag.

Free domain?

contains(variables('varFreeDomains'), variables('varDomain'))

If Yes: -2, flag.

Role-based local?

contains(variables('varRoleLocals'), variables('varLocal'))

If Yes: -1, flag.

6) Map score to Choice field (your exact values)

• If score is at least 8, use 846280000

• Else if score is at least 5, use 846280001

• Else use 846280002

7) Update the Lead record

Dataverse, Update a row:

• kpi_emailvalidityconfidence = mapped value

Optional:

• kpi_emailvalidityscore = varScore

• kpi_emailvalidityflags = varFlags