To whom it may concern:

Google is no longer the only front door. When your customer asks an ai assistant, the answer arrives — with or without your name in it. Getting named is the new visibility. Are you in the answer?

This is the work.

Nine signals across three surfaces. Correlated in real time.

Assistantswho AI names
Searchwhat customers ask
Ground truthwhat your site says

A decision list you can act on Monday morning.

Run a visibility check →
monitoringlive
query 1 of 15"best italian restaurant austin tx"
ChatGPT✓ named
Claudescanning…
Google AI✓ named
activity
--:--:--restaurant · 8 of 12 named
--:--:--correlation cycle · complete
--:--:--chatgpt · query dispatched
146 scans / hour

Getting named isn't luck. It's the correlation of every signal the assistants read: the questions asked, the pages retrieved, the entities claimed, the gaps unfilled.

01 / signals

Nine signals. One correlated view.

Everyone else watches one signal. Maybe two. Nine is where correlation lives.

Assistants
01
AI recommendations
Every query your customer might ask, run against ChatGPT, Claude, and Google AI Overviews. Who names you. Who names competitors. Who names nobody.
Proprietary scanner
02
Source retrieval
Which pages each assistant actually reads to build its answer. The source graph nobody else maps.
Scan analysis
03
Competitor entities
Which categories, licenses, credentials, and citations your competitors claim that you don't.
Entity audit
Search
04
Search Console
What queries actually drive impressions today. What ranks. What clicks. The gap between what customers ask and what your site answers.
GSC API
05
Content gaps
Questions your customers ask that your site doesn't yet answer. The prescriptive side of GSC.
Content audit
06
Technical SEO
Core Web Vitals, JavaScript rendering, sitemap health, canonical hygiene, robots access per crawler.
Site audit
Ground truth
07
Site structure
Whether crawlers can even reach what you publish. Schema validity. NAP consistency. Heading hierarchy.
Structural audit
08
Google Business Profile
Categories, photos, review response, posts, hours accuracy. The signals Google feeds back to itself.
GBP data
09
Reviews
Sentiment, volume, response cadence, and — critically — what phrases customers use that AI can re-quote.
Review analysis

Real data. Real decisions. Every page for a reason. Every fix pointed at a specific signal — no ship on hope, no fix on hunch.

02 / decisions

Every page. Every fix. For a reason.

No page ships on instinct. No fix on hunch.

01
Site rebuild
Crawler-native architecture on Astro. Server-rendered, zero-JS by default, structured for retrieval.
02
Answer pages
Every query your customers ask, given a page shaped as an answer. Retrievable by name.
03
Entity graph
Schema, categories, credentials, service areas. Claimed and structured so assistants understand what you are.
04
Evidence pages
Case studies, reviews, credentials, dated observations. What the assistants cite when they name you.
05
GBP management
Posts, review response, category and photo hygiene. Weekly cadence, tracked against the scan.
06
Technical fixes
Schema, JSON-LD, sitemap, crawler access. The blocker list that makes everything else possible.
07
Measurement
Baseline before we ship. Cadence scans after. Delta reports tied back to the signal that moved.

Every number traced back to the signal that moved it. When visibility climbs, we can tell you which piece of work drove it. When it doesn't, we can tell you that too.

03 / loop

The work compounds.

Every cycle sharpens the correlation. Nothing carries forward on hope.

01
Baseline
Where you stand now, across every signal.
→
02
Correlate
Which signals point to which decisions.
→
03
Ship
The pages, fixes, and entities that move the number.
→
04
Measure
Re-scan on cadence. Track the delta per signal.
→
05
Repeat
The next decision list is smarter than the last.

Every cycle sharpens the correlation. What worked stays. What didn't gets rewritten. Nothing carries forward on hope.

Guessing is not a strategy. Every recommendation carries the signal it came from. Every ship references the evidence that scoped it. Every case study shows the numbers that moved.

04 / proof

The numbers move.

Signal said to fix it. Fix shipped. Number moved.

Case study 01
Residential cleaning
St. George, UT · 30-day sample
0→8
of 12 ai recommendation queries

Client had never been named by ChatGPT or Claude on the twelve queries a St. George homeowner would actually ask. We rebuilt the site on a crawler-native stack, fixed review schema that was hidden inside an iframe, and shipped service-area pages the assistants could retrieve. Named on eight of the twelve within thirty days.

Signals that pointed to the fix
Source retrieval · Site structure · Reviews · Content gaps
Read the full study →

Illustrative sample. Real deltas publish as scans complete post-launch.

Publication
The AI Visibility Index

Quarterly. How ChatGPT, Claude, and Google AI Overviews recommend local businesses across the top U.S. metros. Original data. Named winners. Named losers. Published by LinksMaxing because nobody else is measuring it at this depth.

First report · Q1 2027

Be in the answer.

Every engagement starts with a real conversation. Twenty minutes, a visibility scan of your business against the assistants your customers use, and an honest read on what it would take to move the number.

Book a call →
— The LinksMaxing Manifesto · Dallas · 2026