Your canonical NAP (the version you treat as correct)
As it appears on other sources
Add the name, address, and phone from another listing (Google Business Profile, Yelp, Apple Maps, a directory, an old footer). Start with two and add more if you need them.
You can compare up to 4 sources at once.
How to use it
- Enter your canonical NAP at the top: the business name, full address, and phone exactly as you want them to read everywhere. This is the version every other listing gets checked against.
- Fill in at least one other source. Copy the name, address, and phone straight from a listing such as your Google Business Profile, Yelp, Apple Maps, or an old page footer. Add up to four sources in total.
- Press Check consistency. The tool normalizes both sides (lowercase, strips punctuation, collapses spaces, standardizes Street and St, Suite and Ste, and the rest, and reduces phones to digits) and compares each field.
- Read the per-source report. A green pass means every field matches after normalization. A mismatch lists exactly which field differs and shows your canonical value beside the source value so you can see the change to make.
- Use Copy report to put the full result on your clipboard for a cleanup checklist or a developer ticket. Fix each flagged listing at the source, then re-run to confirm.
Why it matters for AI search
An AI answer engine does not read your business the way a person reads a single page. It assembles an entity from many sources and decides how confident it is that those sources describe the same place. Your name, address, and phone are the anchor it leans on most, because they are concrete and easy to match. When one directory lists a suite number you dropped years ago, or an old footer carries a phone you no longer use, the engine sees two records that almost agree, and almost is where doubt enters. That doubt is how a wrong phone number ends up in a Gemini answer, or how your shop gets left out of a Perplexity recommendation that names a competitor instead.
This is Vector 2, Anchor, in Formative Digital's 12-Vector method. Vector 2 is entity disambiguation: confirming, across every source an engine reads, that you are one business with one set of details. Consistent NAP is the cheapest and most direct way to raise that confidence, and it is the foundation the rest of the work sits on, from schema to citations. The checker shows you the gap between your canonical record and each live listing. Closing that gap across dozens of directories is the kind of cleanup the Formative Forces, our orchestrated agent system, runs at volume.
The tool shows the gap. We close it across every listing.
Catching one mismatch here is quick. Auditing your name, address, and phone across Google Business Profile, Apple Maps, Bing Places, and the directories AI engines actually read, then correcting and monitoring each one, is the work. That is part of our Local SEO Ontario engagement, where NAP, schema, and local citations are aligned together so the answer engines see a single, confident entity.
Want a read on where your listings stand right now? Book a free AI visibility audit and we will show you the NAP conflicts alongside your citation rate across the major AI engines.
Frequently Asked Questions
What is NAP consistency and why does it matter?
NAP stands for Name, Address, and Phone. NAP consistency means those three details are written the same way everywhere your business appears online: your website, Google Business Profile, Yelp, Apple Maps, directories, and citations. Search engines and AI answer engines use NAP to confirm that two listings describe the same real-world entity. When the details disagree, that confidence drops, and you can lose visibility in local search and in AI recommendations.
How does this NAP checker decide whether two listings match?
It normalizes each field before comparing. Text is lowercased, punctuation is stripped, extra whitespace is collapsed, and common abbreviations are standardized so that Street and St, Avenue and Ave, Suite and Ste and Unit, Road and Rd, and similar pairs are treated as equal. Phone numbers are reduced to their digits. The tool then compares each normalized source field to your canonical record and flags any field that still differs, so a formatting difference like Dr versus Drive does not register as a real mismatch.
Does a difference in suite or unit formatting count as a mismatch?
No. The checker standardizes Suite, Ste, and Unit to a single form before comparing, along with the common street-type abbreviations. So 425 Fairview Dr, Ste 5 and 425 Fairview Drive, Suite 5 are treated as the same address. It only reports a mismatch when a meaningful difference remains after normalization, such as a different street number, a different phone digit, or a different business name.
Does NAP consistency affect how AI engines describe my business?
Yes. AI engines such as ChatGPT, Perplexity, Google Gemini, and Google AI Overviews build an internal picture of your business from many sources. Consistent NAP across those sources makes it easier for the engine to confirm it is the same entity and to repeat your details accurately. Conflicting NAP introduces doubt, which can lead to a wrong phone number, an old address, or your business being left out of an answer entirely. We track this under Vector 2, Anchor, in our 12-Vector method.
Is this NAP checker private, and does it store my data?
The comparison runs entirely in your browser. The name, address, and phone you paste are checked on your own device, and the only point at which anything is sent is if you choose to submit the short capture form to reveal the detailed per-field report, which notifies Formative Digital so we can help you align your listings. The comparison itself is real string matching, not an estimate, so the pass and mismatch results reflect exactly what you entered after normalization.