In our post on how the AI Recommendation Score is calculated, we mentioned that Brand Authority covers more than review ratings, including directory and citation consistency. It's worth pulling that thread out on its own, because NAP consistency, meaning your Name, Address and Phone number matching across every place they appear online, is one of the more boring sounding AEO levers, and one of the most commonly broken.
Why AI models care about a detail this small
AI models building confidence in a business cross reference multiple sources rather than trusting a single one. Your website says one thing, your Google Business Profile says another, an old TripAdvisor listing still has your previous address, and an industry directory has a phone number nobody has answered in two years. Individually, none of these look like a serious problem. Collectively, they read to a model as a business that might not be current, correctly located, or reliably reachable, which is precisely the kind of doubt that suppresses a confident recommendation in favour of a competitor whose details agree everywhere.
Where inconsistency creeps in
- A business that's moved or rebranded. Old addresses and previous names linger on directories nobody remembers signing up to, long after the website itself has been updated.
- Multiple phone numbers in circulation. A main line, a mobile someone used for an early listing, and a booking line can all be attributed to the same business across different sources, none of them clearly marked as primary.
- Inconsistent formatting, not just inconsistent facts. "St." versus "Street," a suite number included in one listing and dropped in another, can be enough to create ambiguity about whether two listings even refer to the same business.
- Abandoned or duplicate directory listings. Golf clubs in particular tend to accumulate old listings on regional golf directories and booking platforms that were never claimed or updated after launch.
- Google Business Profile and website disagreement. This is the single most damaging version, because GBP is one of the most heavily weighted sources AI models draw on for local trust signals.
How to actually audit it
Start with your Google Business Profile as the source of truth, since it's the listing most heavily weighted. Then search your business name directly and work through every result: your website's contact page and any location pages, TripAdvisor, Bing Places, Apple Maps, Yelp if relevant to your category, and any industry specific directories, whether that's a regional golf directory, a trade association listing, or a local chamber of commerce site. Note every discrepancy in name, address, and phone number, however minor it looks.
Fixing what you find
Claim any unclaimed listings first, since those are the ones most likely to carry outdated information nobody is actively maintaining. Update the rest to match your current, canonical details exactly, including formatting. Where a listing can't be edited or claimed, most platforms have a report or suggest an edit function, slower but still worth using rather than leaving it stale indefinitely.
Where to start
Search your own business name and see what comes back across the first two pages of results, then compare every address and phone number you find against your current, correct details. If they don't all match exactly, that's a fixable, low cost gap sitting inside your Brand Authority score right now.