QuQi

NAP consistency audit

Name, address and phone act as an identity fingerprint. Conflicting versions make it harder for Google to be confident which entity a citation refers to, and confidence is what keeps a listing stable. This skill finds the variants, ranks them by how much damage they do, and fixes only the ones that matter.

Get the skill file Let the agents run it
CATEGORY
Local SEO
FORMAT
nap-consistency-audit.md
STEPS
6
PRICE
Free - no account
WHEN TO REACH FOR THIS

Use when a business has moved, rebranded, changed phone numbers, or has been listed by third parties over several years and the details no longer agree across the web.

The skill file

nap-consistency-audit.md
---
name: nap-consistency-audit
description: Use when a business has moved, rebranded, changed phone numbers, or has been listed by third parties over several years and the details no longer agree across the web.
---

# NAP consistency audit

Name, address and phone act as an identity fingerprint. Conflicting versions make it harder for Google to be confident which entity a citation refers to, and confidence is what keeps a listing stable. This skill finds the variants, ranks them by how much damage they do, and fixes only the ones that matter.

## What you need first

- The single canonical NAP as it should appear everywhere
- A list of every known listing, directory and profile
- Any previous addresses or phone numbers used in the last five years

## Method

1. Define the canonical NAP once and write it down, including suite formatting and phone format, so every later fix has one target.
2. Search the exact old phone number and old address strings in quotes to surface listings you never created, which are usually the majority.
3. Classify each mismatch: wrong name, wrong address, wrong phone, or duplicate listing. Wrong phone and duplicate listings do far more harm than suite formatting differences.
4. Ignore cosmetic variance such as Street versus St or a missing full stop, which is normalised and is not worth the hours it consumes.
5. Fix in order of authority: Google Business Profile first, then the primary data aggregators and the top ten citation sources for the category, then the long tail.
6. Re-run the exact-string searches after 60 days, since aggregator-fed listings repopulate and a fix that does not stick is not a fix.

## What this produces

A prioritised mismatch register showing each incorrect listing, the type of error, its authority, and whether the correction has propagated.

## Where this goes wrong

- Chasing abbreviation and punctuation differences that are normalised anyway, while a live wrong phone number sits untouched
- Correcting downstream directories without fixing the aggregator that feeds them, so the old data returns
- Using a call tracking number on the profile and a different number everywhere else, which splits the identity

---

From the QuQi skill library - https://www.quqi.io/skills/nap-consistency-audit
Free to download · no account, no email

What you need first

  • The single canonical NAP as it should appear everywhere
  • A list of every known listing, directory and profile
  • Any previous addresses or phone numbers used in the last five years

Method

  1. 01 Define the canonical NAP once and write it down, including suite formatting and phone format, so every later fix has one target.
  2. 02 Search the exact old phone number and old address strings in quotes to surface listings you never created, which are usually the majority.
  3. 03 Classify each mismatch: wrong name, wrong address, wrong phone, or duplicate listing. Wrong phone and duplicate listings do far more harm than suite formatting differences.
  4. 04 Ignore cosmetic variance such as Street versus St or a missing full stop, which is normalised and is not worth the hours it consumes.
  5. 05 Fix in order of authority: Google Business Profile first, then the primary data aggregators and the top ten citation sources for the category, then the long tail.
  6. 06 Re-run the exact-string searches after 60 days, since aggregator-fed listings repopulate and a fix that does not stick is not a fix.

What this produces

A prioritised mismatch register showing each incorrect listing, the type of error, its authority, and whether the correction has propagated.

Where this goes wrong

  • Chasing abbreviation and punctuation differences that are normalised anyway, while a live wrong phone number sits untouched
  • Correcting downstream directories without fixing the aggregator that feeds them, so the old data returns
  • Using a call tracking number on the profile and a different number everywhere else, which splits the identity

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