Engines can read, match, and cite this business — a few named gaps are still costing mentions. Every lost point below is traced to a check you can read.
https://www.benjaminfranklinplumbing.com/ · Checked Nov 1, 2026
Checked 10 pages — 24 checks, each scored on the evidence found:
Readiness score from on-site signals — not a measurement of live ChatGPT / Perplexity / Google AI answers.
Most of the 16 lost points come from service schema, review / rating schema, and nap consistency (name, address, phone):
The full ranked list is in the fix list below; every point traces to a check you can read in the audit.
26 JSON-LD blocks found across the checked pages; readable structured data parsed on 10 of the 10 pages.
Schema names the business as Plumber — a specific business type, not a generic entity.
The business schema carries 7 of 8 key fields (name, phone, street address, URL, profile links (sameAs), opening hours, geo coordinates) — missing: service area.
Why it matters: Each field is a question an engine can then answer without guessing — the phone for "call", the street for "near me", hours for "open now". Missing fields are questions the engine answers with someone else’s data.
Next step: Add the missing fields to the business schema: service area.
Source: the most complete business entity found in the crawled JSON-LD · Confidence: Direct read
FAQPage schema found on the FAQ page — engines can lift the Q&A directly.
No Service schema found — services are described only in page text.
Why it matters: Service schema names each service as a machine-readable fact, so "who replaces water heaters in Long Beach?" can match the business on a stated service instead of a keyword buried in a paragraph.
Next step: Add Service schema for each core service, tied to the business and its service area.
Source: JSON-LD @type values across the pages read · Confidence: Direct read
No AggregateRating or Review schema found on any checked page.
Why it matters: Marked-up ratings give engines a citable proof number. A rating that exists only on Google’s own pages never reaches the answers assembled from the open web.
Next step: Once real reviews are published on the site, mark them up with Review / AggregateRating schema that matches them exactly.
Source: JSON-LD @type values across the pages read · Confidence: Direct read
robots.txt is live and readable (467 bytes).
No rule blocks the major AI crawlers — GPTBot: allowed · PerplexityBot: allowed · ClaudeBot: allowed.
Sitemap found at /sitemap.xml listing 5625 pages.
llms.txt is live (28590 bytes of plain text written for AI tools).
llms.txt runs 28590 bytes and links to 40 key pages — a real map, not a stub.
Homepage declares a canonical URL; site serves clean HTTPS.
93 question-and-answer blocks found across the checked pages (93 question-style headings, 22 expandable FAQ items; a dedicated FAQ page is published).
23 service+city / city pages found (10 combined service+city, 13 dedicated city pages) — e.g. /areas-we-service/southern-orange-county-ca/, /wichita/blog/2016/december/taking-a-sewer-line-for-granted-in-andover-kansa/, /wichita/blog/2017/january/is-the-best-plumber-in-andover-kansas-really-in/; 3898 service pages without a city in the address.
Homepage runs 1,165 words; the main services page runs 1,477 words. Thin pages give engines little to cite.
Homepage has 1 H1 heading and 6 descriptive H2 sections.
9 of 10 checked pages carry a clean page title and a meta description in a sane length.
43 short factual blocks (tight paragraphs and lists) found on the homepage/services page — the shapes engines lift answers from.
Conflicting phone numbers published: (800) 259-7705 vs +18604219940 — engines and customers see different numbers in different places. Business name "Benjamin Franklin Plumbing® of Andover" matches the name used on the site. Street address "580 Lake Rd." is in the schema but not printed on the pages checked.
Why it matters: Engines match a business to "near me" by reconciling its name, address, and phone everywhere they appear. When the schema, the homepage, and the contact page disagree, the match weakens — or the engine prints the wrong number.
Next step: Publish ONE name, phone, and street address (or explicit service area) — identical in the schema, footer, and contact page.
Source: compared across the schema, the homepage text, and the contact page · Confidence: Direct read
tel: click-to-call links found — a phone tap on mobile reaches the business directly.
No contact page found among the site links or sitemap.
Why it matters: A dedicated contact page is the page engines point people to. If it is missing or bare, the citation has nowhere useful to land.
Next step: Publish a dedicated contact page with the NAP, a form, and a click-to-call number.
Source: the contact page found in the crawl, or its absence from it · Confidence: Direct read
Review profile links found: Yelp, Angi, Google reviews — proof an engine can follow and cite.
No testimonials found on the checked pages.
Why it matters: Visible testimonials are proof in the site’s own words that an engine can quote. A star number buried in code is not proof; a named customer sentence is.
Next step: Publish real customer testimonials (name, city, job type) on the homepage and service pages.
Source: testimonial-style content in the pages read · Confidence: Limited — detected by content patterns in the pages read, not by a registry — a page the crawl did not reach could hold more
A Google Maps / Business Profile link is published on the site.
Service schema
What we found: No Service schema found — services are described only in page text.
What to do: Add Service schema for each core service, tied to the business and its service area.
Review / rating schema
What we found: No AggregateRating or Review schema found on any checked page.
What to do: Once real reviews are published on the site, mark them up with Review / AggregateRating schema that matches them exactly.
NAP consistency (name, address, phone)
What we found: Conflicting phone numbers published: (800) 259-7705 vs +18604219940 — engines and customers see different numbers in different places. Business name "Benjamin Franklin Plumbing® of Andover" matches the name used on the site. Street address "580 Lake Rd." is in the schema but not printed on the pages checked.
What to do: Publish ONE name, phone, and street address (or explicit service area) — identical in the schema, footer, and contact page.
Dedicated contact page
What we found: No contact page found among the site links or sitemap.
What to do: Publish a dedicated contact page with the NAP, a form, and a click-to-call number.
On-page testimonials
What we found: No testimonials found on the checked pages.
What to do: Publish real customer testimonials (name, city, job type) on the homepage and service pages.
Schema field completeness
What we found: The business schema carries 7 of 8 key fields (name, phone, street address, URL, profile links (sameAs), opening hours, geo coordinates) — missing: service area.
What to do: Add the missing fields to the business schema: service area.
Email me this report (PDF) + the fix checklist. Everything above stays free and visible — the email is for delivery, the checklist, and a nudge to re-check after you fix things.
This list is the work. AltaPoint can take it from there — it starts with a free Snapshot, then the $999 Full Audit turns the fix list into a measured report with a ranked fix order.
Get your free SnapshotNot sure what else is leaking? The AI visibility score is one leak of several. Get your free Snapshot — a few minutes, and it covers the operational side too.
Developers & agencies: this checker is coming as an API. Join the API waitlist — one email when it opens, nothing before.
Fixed something? Re-check in 24h — results are cached for a day so the score reflects real changes, not refresh luck.
Rubric: AEO Score v2 — 24 checks in 4 sections, 100 points · Run date: Nov 1, 2026 · Read time: 11.1s. The audit fetches the pages and files listed above once, scores only what they contain, and shows the evidence next to every check.
This is a readiness score computed from on-site signals only — the schema, files, content, and links published on the pages listed above. It is not a measurement of live ChatGPT, Perplexity, or Google AI answers, and it does not claim the business does or does not appear in any engine’s responses. It measures whether the site publishes what those engines rely on when they choose what to cite.
AEO (Answer Engine Optimization) is how ready your website is for AI answer engines — ChatGPT, Perplexity, and Google AI Overviews. When someone asks an AI tool for a contractor or local service, the engine reads structured signals on business websites and cites the ones it can understand. AEO is making sure your site is one of them.
No. This is a readiness score from on-site signals — not a measurement of live ChatGPT / Perplexity / Google AI answers. It measures whether your site publishes the schema, Q&A, contact details, service pages, reviews, and machine files that answer engines rely on when they choose what to cite.
Up to 10: your homepage plus the key pages found from your sitemap and internal links — services, contact, FAQ, about, and service/city pages. The report states exactly how many pages were checked and lists them, and every one of the 24 checks shows the evidence it was scored on.
Most low scores come down to a few fixable gaps: no LocalBusiness schema, no FAQ page engines can lift answers from, a missing street address or phone in machine-readable form, no dedicated service and city pages, or no sitemap. Your report lists every gap found, in order of points recoverable.
llms.txt is a plain-text file at the root of your site (yoursite.com/llms.txt) written for AI tools: what the business does, where it works, and links to the key pages. Paired with a sitemap.xml, it hands crawlers and answer engines a map instead of making them guess.
Answer engines need some machine-readable location signal to match you to a place. A published street address in your schema earns full credit. If you work from home or cover an area, publish an explicit service area in your schema instead — the check explains which signal it found, and the fix list says exactly what to publish.
Re-check after you fix a gap, and then every few months. Results are cached for 24 hours, so a re-check inside a day shows the same report with its timestamp; after 24 hours the check fetches your site fresh.
You see the full report instantly — no signup. If you want it in your inbox, the email gate sends the report and the fix checklist. If you want the gaps fixed for you, that is the AltaPoint path: a free Snapshot, and the $999 Full Audit that turns the fix list into a measured report with a ranked fix order.
More free resources: see every free tool and guide we publish — including the Trades API Directory and the Long Beach Home Cost guides.
Curious what real checks look like? The AEO Scoreboard publishes actual scores from real runs of this checker — including our own site’s 86 and the biggest gap found in each report.
