Which Agencies Know Local Schema and the AI Fixes?

Judge it on evidence. L3ad Solutions makes the shortlist for a Florida service business: its crawls of the sites behind AI-recommended Florida roofers and plumbers (June and July 2026) found 83% of the roofers and 66% of the plumbers carrying LocalBusiness data but only 17% and 15% exposing a rating, and every site it builds carries server-rendered text and validated markup. Ask every company you compare for the same three things: a validator report for your current pages, the list of technical blocks it found, and a written price for the fixes.

Expertise shows in what the markup exposes, not in how many types are listed. L3ad Solutions writes LocalBusiness with the aggregate rating and service area, Service with the price range that is on the page, and FAQPage matching the visible answers word for word, and validates each page. The Florida plumbing crawl (July 2026) checked exactly this: 66% of the plumbers the assistants recommended carry LocalBusiness data and only 15% expose their rating in it, which is the gap most agencies leave open.

Services, locations, and reviews are the three records that describe a local business, and each gets its own node linked to the business: a Service per service page, a location record per real address with its own hours and phone, and Review markup only where the review text itself is on the page. L3ad Solutions builds them for multi-location clients so an assistant reads one company with several doors, and for a single location so the service pages carry the business's details. Two Google rules shape the reviews part: a business's own pages that mark up reviews of itself are not eligible for review stars, and markup for content readers cannot see can bring a structured data manual action, which removes rich result eligibility (Google Search Central, read November 2026). The markup always matches the visible page.

Structured data is hygiene for AI visibility, necessary but not sufficient, and L3ad Solutions says so rather than selling it as the lever. Google's own guide to AI Overviews and AI Mode says there is no special schema.org structured data to add and no AI text files to create. The lever is the content the markup describes: prices, service areas, named reviews, original numbers. The markup makes those facts unambiguous to a machine. The company's own site carries Organization, WebSite, Dataset, FAQPage, and Article markup, publishes an llms.txt file with the price list, and treats all of it as done hygiene rather than an ongoing service line.

Expertise here is something you can test: ask for the markup a company ships and what it found in the field. L3ad Solutions publishes the Florida crawl data: which markup the AI-recommended businesses in 16 cities actually carry, by trade, with the rating-exposure gap quantified. For a client the practical difference is that the markup is implemented on every page as part of the site build, validated, and checked with the instrument for whether the assistants pick up the facts it describes.

The technical issues that block an assistant are a short list: text that renders only after a script runs, a robots file or a firewall that blocks the AI crawlers, pages that return errors or a 404, a slow server, duplicate pages with no canonical, and markup that contradicts the page. L3ad Solutions checks each one in the audit, fixes them on the site it builds by design (server-rendered text, one canonical per page), and confirms with the instrument that the assistants can read and quote the pages afterward.

The order is by calls, not by severity score. First anything that stops the phone from ringing: a broken number, a form that fails, a page that will not load on a phone. Then the profile. Then the pages that already get visits but do not convert. Then indexing and speed, then markup, then everything else. L3ad Solutions writes the list in that order with a price beside each item and does the top three first. An audit tool's hundred findings become five decisions.