Local, by design

Built for local businesses — not national brands, products, or ecommerce.

viizable answers one question: when someone nearby asks AI for a business like your client’s, does your client get named? Every factor in this index was reverse-engineered from the single phrase that decides local visibility:

“best [industry] near me”

Win that one prompt and the rest follow. Get named for “best [industry] near me” and the long tail — every service, every variation, every neighborhood around them — comes with it.

What it is

AI won’t tell you how it ranks businesses — but it can’t hide the ones it does. We reverse-engineered over 30,000 top-mentioned local businesses to identify over 150 weighted ranking factors.

AI search is an unruly beast. There’s no algorithm document, no index to buy, no rulebook anywhere — and there isn’t one coming. The AI engines are independent companies competing for market share, each pulling from different sources, on different timeframes, and reading what it finds its own way.

We knew the answer to the chaos was in the data. If no one publishes the rules, the rules are hiding in the results. So we scanned more than 30,000 local businesses that AI systems actively recommend and worked backward to the facts: what they have in common, and what AI needs to see before it will put a business on its short list.

That work produced the Viizable Ranking Factor Index — the criteria common to every major AI system, each weighted by how much it actually matters. Because the engines keep shifting, we re-weight the index on a regular cycle, so you always know which factors are gaining or losing importance, month to month.

One thing we deliberately don’t do: we don’t use AI to rank businesses. Scoring is computed from historical significance across that 30,000-business dataset — not the opinion of a chatbot. What you hand your client is concrete evidence — not conjecture, not speculation, not guesswork.

Built on evidence, not opinion

AI won’t tell you how it ranks — but it can’t hide the businesses it does

30,000+
AI-recommended businesses analyzed
~140
criteria common to every major AI engine
Re-weighted
on a regular cycle as AI shifts
0%
AI guesswork in how we score
How the factors are evaluated

Five pillars of analysis — not a simple checklist

When viizable runs a scan, it may look simple on the surface. Behind it, the engine runs over 150 distinct analyses across five critical areas that determine whether AI systems will trust and recommend a business.

Pillar 1

On-Site Congruency

Structural analysis of the site’s content, schema markup, navigation consistency, and trust signals that AI crawlers evaluate.

Pillar 2

External Data Corroboration

How the business is referenced across directories, citations, review platforms, and third-party sources that AI cross-references.

Pillar 3

Contextual API Analysis

Direct interrogation of how AI systems perceive and classify the business when processing recommendation queries.

Pillar 4

Recency Signals

Freshness of content, reviews, updates, and engagement — AI systems favor businesses that show active, current operations.

Pillar 5

Recommended Site Comparison

Benchmarking the domain against sites AI already recommends in its category and geography to identify the specific gaps.

The index

160 factors, across 13 categories

What each category measures, in order of how much AI weight it carries — with a real example of the kind of gap viizable surfaces. The full line-item checklist is part of viizable’s engine.

Reputation Signals

13 factors
Looks at how the business’s reputation reads to AI across the web — the volume, freshness, rating, and consistency of reviews, and how the business responds to them, on the platforms AI actually reads.
Example of what we’d flag

The five businesses AI recommends each carry 100+ Google reviews from the last year; this shop has 14, none in the past six months — so AI reads it as inactive and skips it.

AI Corroboration

6 factors
Checks whether independent, third-party sources back up what the business claims about itself. AI trusts a fact far more when sources it didn’t get from you agree on it.
Example of what we’d flag

The homepage says “award-winning” and “#1 rated,” but no outside source — press, an association, an awards body — confirms it, so AI treats the claim as unverified and discounts it.

Business Identity Signals

19 factors
Confirms AI can tell, without guessing, exactly who the business is — its name, what it does, where it operates, who’s behind it — and that those facts agree everywhere they appear.
Example of what we’d flag

The site title says Bob’s BBQ, the footer says Robert’s Barbeque & Grill, the license reads Robert’s Barbeque & Grill, LLC, and Yelp lists it differently again — AI can’t reconcile the mismatch into one trusted identity, so it hesitates to recommend it.

AI Visibility

18 factors
Measures whether the business actually surfaces when AI answers the prompts customers really use — across each major engine — and how prominently.
Example of what we’d flag

For “best auto repair near me,” the business is named by one engine and missing from the other four, while two competitors appear in all five — a visibility gap you watch close as the factors get fixed.

Content Quality & Expertise Signals

16 factors
Evaluates whether the site gives AI enough substance to understand and trust the business — clear, in-depth content that demonstrates real expertise, not a thin brochure.
Example of what we’d flag

The homepage is under 300 words with no service-detail pages and no FAQ, so AI has almost nothing to extract — competitors with deep service pages get quoted instead.

Local SEO & GBP Signals

10 factors
Checks the local foundation AI leans on — the Google Business Profile and the local-relevance signals that tie the business to its place and its category.
Example of what we’d flag

The Business Profile is missing its primary category and service area, and the hours there don’t match the website — small gaps that make AI unsure the listing is current.

Contact Prominence

6 factors
Confirms a customer — and AI — can find how to reach the business instantly, and that the contact details are machine-readable, not buried.
Example of what we’d flag

The phone number appears only inside a header image, with no clickable tel: link and no dedicated contact page, so AI can’t reliably extract how to reach the business.

Trust & Safety Signals

15 factors
Looks for the trust markers AI and customers expect from a legitimate local business — security, transparency, and proof it’s safe to do business with.
Example of what we’d flag

The site has no HTTPS padlock, no privacy policy, and no visible licensing or guarantee — basic trust signals every recommended competitor displays.

SEO (Technical)

25 factors
Covers the technical foundation that lets AI crawl, parse, and correctly classify the site — structured data, tags, mobile readiness, and speed.
Example of what we’d flag

The homepage is missing LocalBusiness schema and Open Graph tags and loads slowly on mobile, so AI struggles to read what the business is and where it serves.

UX & Conversion Signals

4 factors
Assesses whether a visitor who lands on the site can immediately tell what to do next — the usability and clear next-step signals of a site built to convert.
Example of what we’d flag

There’s no clear call-to-action or booking path near the top of the page, so even when AI sends a customer, the visit stalls.

Service Trust & Eligibility

8 factors
An industry-specific set of signals that only applies to certain service businesses — it carries little or no weight for most, and viizable only counts it where it actually fits the business type.
Example of what we’d flag

For contractors like plumbers, HVAC professionals, and electricians, AI looks for license, insurance, and verification cues before it trusts them — so one that never surfaces them can lose ground to competitors who do. For a restaurant or a retail shop, these signals simply don’t apply.

Social Presence Signals

6 factors
Looks at whether the business has active, consistent, linked social profiles that corroborate it’s a real, current operation.
Example of what we’d flag

The site links to a Facebook page that hasn’t posted in two years and an Instagram handle that doesn’t match the business name — inconsistencies that weaken the picture.

Additional Actions

14 factors
The offsite punch-list of verifiable anchors — the real-world links and consistency steps that prove a business’s claims to AI beyond its own website.
Example of what we’d flag

The license number is printed on the site but not linked to the state board’s record, and the press logos in the footer don’t link to the actual articles — easy fixes that turn claims into verified facts.

The published methodology

It took us about a year to distill the data into the key factors. You can get them in less than a minute.

The 2026 Local Business AI Ranking Factor Index — by J. Brent Tuttle

The full index, explained

The complete methodology behind this index is laid out in full in the companion book — how we found the businesses AI recommends, worked backward to the common signals across 100+ industries, and determined what AI actually weighs. It teaches the heavy hitters category by category, with the complete factor list as a working reference.

It isn’t a sales pitch and it isn’t a chatbot’s opinion. It’s an industry gift — straight evidence the whole field can use.

📖 Free advance copy — available now

Founded & authored by J. Brent Tuttle. viizable’s scanning technology and data resources were the means used to run the study and build the index.

See where a business stands against the index.

Drop in any local business and viizable scores it against every factor — then shows you exactly what to fix.