Methodology
The 19 dimensions, the report format, and how the modeled numbers are built.
This is the complete framework behind your audit score: every dimension and weight, a full example report showing the format, and the exact inputs behind the modeled competitor and revenue figures. Your own audit uses your real URL, not this example.
19 Dimensions Analyzed
Every score is specific.
Every finding is actionable.
This is Solenzo's diagnostic framework, not an official ranking-factor list. Each dimension is drawn from published guidance from Google and the AI platforms on local visibility, structured data, and content quality. The weights are our own judgement about what moves the needle first for a local service business.
Google Business Profile Completeness
Is your Google listing complete enough to win the click?
Whether your Google Business Profile has its category, hours, phone, website, and photos filled in. Google says complete, accurate profile details make a business more likely to appear in local results.
Recent Review Activity
Are reviews still coming in?
How recently your most recent Google reviews were posted, and how many you have overall. Google says review count and positive ratings can help local ranking; recent activity is a buyer-confidence and profile-maintenance signal, not a confirmed Maps-ranking factor on its own.
Reviews vs. Local Competitors
How does your review count compare to a disclosed local sample?
Your Google review count and star rating compared against a disclosed sample of local competitors for the same query, location, and time — a snapshot for competitive context, not a ranking forecast.
Mobile Load Speed
Does your site load fast on a phone?
Field or lab Core Web Vitals for your homepage on mobile — LCP, INP, and CLS against Google's published good-experience thresholds. A customer can't call, book, or submit a form they abandon before the page is usable.
Mobile Contact Path
Can a ready customer reach you without hunting?
Whether your homepage shows a tap-to-call number, contact form, or booking link visible on a mobile viewport without scrolling — a conversion-friction check, not a ranking factor.
First-Party Business Data Consistency
Do your name, address, and phone match everywhere?
Whether the business name, address, and phone on your website match your Google listing. Conflicting first-party details create customer friction and make it harder to maintain a consistent business identity — this checks your own site and profile, not a broader directory audit.
Business Identity Consistency
Is your business identity consistent everywhere someone might check it?
Whether your business name, primary service description, and location/service-area details line up across your homepage, contact page, and Organization/LocalBusiness markup. A consistent identity gives search systems clearer administrative and service details — it does not measure Google's confidence, which the audit can't inspect.
Visible Proof and Attribution
Can a visitor see who stands behind your claims?
Named authors or owners, credentials where relevant, customer evidence, case examples, and clear about/contact information. This is a people-first content-quality check, not a measurement of Google's E-E-A-T scoring.
Source Quality and Specificity
Are your claims specific and attributed enough for a reader to verify?
Named sources, dates, and attribution behind important claims — specific, checkable material rather than generic assertions. Specific, attributed content is more useful to readers and consistent with Google's guidance to create original, people-first content. It is an editorial review, not a model preference AI systems have confirmed.
Evidence Support
Do your numerical claims name a source, date, and scope?
Whether statistics and specific numbers on your site are attributed and checkable. Important numerical claims should name their source, date, and scope so a reader can verify them — this isn't a density AI systems are confirmed to prefer, it's a checkability standard.
AI Search Access & Readiness
Does your site meet the conditions Google names for its AI features?
Google says there are no special AI requirements beyond standard Search eligibility — indexed, crawlable, important content in text, internal links, and accurate structured data. This checks those conditions. It can't predict whether any specific AI answer will cite you.
CSQAF Readiness (internal)
Internal editorial checklist — not shown as a customer-facing score.
Four internal pillars (crawler fluency, extraction efficiency, entity salience, semantic integrity) used to guide content editing. Not a validated unified ranking model, so it carries no weight in the published score and isn't rendered as its own dimension card.
CSQAF: Four Pillars
The unified AIO / AEO / GEO score.
Most frameworks treat AI optimization as separate work. CSQAF unifies crawler access, content extraction, entity recognition, and semantic consistency into a single machine-readability score.
Crawler Fluency
Clean HTML that bots can parse without JS rendering, plus the robots.txt rules that decide which AI crawlers may read you. GPTBot is OpenAI’s training crawler; OAI-SearchBot is the one behind ChatGPT search results. They are separate rules and worth setting deliberately.
Extraction Efficiency
Answer-first formatting with direct 40 to 60 word answers under question-based headings.
Entity Salience
Brand, authors, and topics defined as distinct entities, not just keywords, with consistent naming across the site.
Semantic Integrity
Consistent messaging, NAP data, and schema across every page and touchpoint.
Service and Buyer-Question Coverage
Does your site answer the core questions relevant to your services?
Whether your site covers the range of questions and subtopics a buyer would expect for your stated services and local market — not a claim that Google rewards a declared "topical authority" factor.
Original, Useful Detail
Does your content add something specific, not just generic claims?
Whether your content adds first-hand expertise, specifics, and practical process — original data, named client outcomes, before/after results — versus restating common knowledge. Tied to Google's people-first content guidance, not a penalty formula.
Decision-Stage Coverage
Are you visible across awareness, evaluation, and booking?
Whether your content addresses awareness, evaluation, and booking/contact stages of the customer journey — modeled on how buyers actually decide, not a claim about a Google-preferred content structure.
Content Pathway and Internal Connections
Do related pages link to each other and toward a next action?
Whether educational content links to relevant service pages and a clear next action, rather than sitting disconnected. Related pages and descriptive internal links make it easier to connect relevant information across the site.
Applicable Structured Data
Does your structured data match what's actually on the page?
JSON-LD presence and accuracy — Organization, LocalBusiness, Service, FAQ, Review — validated against your visible content. Accurate markup helps search systems interpret key business facts and can support eligibility for enhanced Google search appearances. It is not a ranking or AI-citation guarantee.
Readable, Accessible Content Structure
Is your content organized so a visitor — or a crawler — can scan it?
Heading hierarchy, sentence and paragraph length, and whether the important content exists as real HTML text rather than only in images or scripts.
Crawlable Site Connections
Are your pages connected by real, crawlable links?
Internal link density, descriptive anchor text, and pages with no crawlable inbound link. Pages without crawlable internal links are harder to discover and less connected to the site's topical pathways — Google can still find them via sitemaps or external links, so this isn't an invisibility claim.
Titles, Headings & Canonical State
Does each page have a clear, unique title and heading?
Title tag, meta description, H1 quality, and canonical/indexability state across the site — the technical basics that let Google interpret and index each page correctly.
Actual Findings
What we find when we
look under the hood.
This is the layout and depth of the report. The site, the scores, and the figures below are an example we built to show the format, not a client's results. Yours are computed from your own URL.
IllustrativeEvery figure in the panel belowWHAT A COMPLETE LOCAL LISTING LOOKS LIKE
A drawing of the elements a complete listing has: filled-out profile, active reviews, accurate categories, and consistent NAP data across directories. The businesses, ratings, and ranking order are invented. Nobody, including us, can promise a position in the Map Pack.
How We Calculate This
The numbers are modeled.
The gaps are real.
Your results include competitive analysis and revenue estimates alongside the dimension scores. Here is exactly how each is produced.
How we identify your competitors
We analyze your site content, niche, and topical signals to surface the 3 brands dominating AI recommendations in your space. These are not peers your size. They are whoever ChatGPT, Perplexity, and Google AI Overviews have decided "owns" your topic. That is your actual competitive threat: the entity capturing AI citations that could be sending you leads.
How the Opportunity Worksheet works
We do not show a default dollar figure built from industry averages. The report includes an optional worksheet: enter your own monthly qualified inquiries, lead-to-sale rate, and first-sale value, and it computes a low/high planning scenario from exactly those numbers. Until you fill it in, no revenue estimate is shown at all — not even an illustrative one.
What the AI Visibility Impact Summary shows
The score gauge shows your overall audit result across all 19 dimensions. Competitor displacement tells you how many of the 3 identified competitors currently outrank your domain in this modeled comparison. Estimated influenced queries is a modeled monthly volume in your niche, not a measured figure. Pipeline exposure is a modeled dollar value derived from that same estimate — none of this substitutes for your own analytics.
The prompt-sample protocol behind the AI Recommendation Gap
The percentage comes from a fixed set of prompts run against a specific AI platform, for a stated location and persona, on a stated date, a fixed number of times, with a defined rule for what counts as a "mention." It is a prompt-sample mention rate for that exact test corpus — not a market-share figure, and not a guarantee about how any future prompt will answer.
All competitive and revenue figures above are industry-modeled estimates, not measured data. They are designed to give directional signal and should not replace your own revenue and traffic analysis.
Local comparison protocol
The Reviews vs. Local Competitors dimension is separate from the modeled AI-competitor analysis above — it uses real Google Places data, not an LLM estimate. We sample three visible local results for the stated service query, from a stated city/ZIP centroid, on a stated date, using a clean session. We report visible review count, rating, category, and contact-path observations. This is a snapshot of that specific sample, not a ranking forecast — local results vary by location, query wording, time, and device.