90d
freshness window for top AEO citation weight
DP working heuristic from platform-tracking write-ups
2×
citation rate lift vs. pages 12+ months stale
DP working heuristic; no GEO-paper-grade study yet
3/mo
minimum substantive update cadence for trades
DP recommended baseline
2×/yr
minimum revisit per existing high-value page
DP recommended baseline
The substantive part matters more than the cadence number. A one-word change to satisfy a calendar reminder doesn't trigger the freshness signal. Google's algorithm looks at the actual content delta. Real freshness updates include:
- Pricing range adjustments backed by your actual job records
- New customer review quotes added from the last 30-60 days
- Updated photos from recent jobs in the relevant city
- Material or product changes (new shingle warranty, updated certification status)
- Code or regulation updates relevant to the topic
- New first-party data points from your own operational records
The `dateModified` field on your page's Article or LocalBusiness schema has to match the most recent substantive change. Faking it is detectable and erodes the very freshness signal you're trying to manufacture.
## The first-year content calendar
For a trades business starting from a baseline of weak existing content, the first 12 months follow a defensible rhythm. The shape below assumes the business has 4-5 core services and operates across 3-5 cities in a metro. Adjust upward for larger operations, downward for solo operators.
| Month | Publish (new) | Revise (existing) | Focus |
|---|---|---|---|
| 1 | Foundation home page rewrite | Top 3 service pages | Establish baseline disciplines on highest-traffic pages |
| 2 | 2 service-detail pages (top 2 services) | 1 existing service page | Add specific data, quotes, schema |
| 3 | 2 hyper-local pages (top 2 cities, top 1 service) | 1 service page | Begin per-city depth pattern |
| 4 | 2 guides (first guide pillar + 1 spoke) | 1 hyper-local page | Establish editorial cadence |
| 5 | 2 hyper-local pages (next 2 cities × top service) | 2 service pages | Continue local depth build |
| 6 | 2 guides (second pillar setup) | 1 hyper-local page | Mid-year content audit and review-cadence check |
| 7 | 2 guides (spokes off pillar 2) | 2 service pages | Refresh data, integrate new reviews |
| 8 | 2 hyper-local pages (services 3-4 × top cities) | 2 hyper-local pages | Continue grid coverage |
| 9 | 2 guides (industry-trend pieces, seasonal) | 1 pillar | Q3 freshness pass |
| 10 | 2 hyper-local pages (round out grid) | 2 service pages | Hit majority of (service × city) cells |
| 11 | 2 guides (audit-driven spokes filling gaps) | 1 pillar | Address weakest pages from analytics |
| 12 | 2 high-value updates instead of new pieces | 4 service pages, full refresh | Annual freshness audit and Q4 update push |
That's roughly 24 new pages and 23 substantive revisions over 12 months. The total publishing rhythm is 1 new + 1 revision per week, averaged. Some weeks will be heavier, others lighter. The constraint is that no week should pass without either a new piece or a substantive revision touching the site.
The calendar assumes the business has the editorial capacity to produce this volume in-house or through a regular contributor. If the realistic capacity is half that, halve every row and accept the slower compounding. A roofer publishing 12 substantive pieces a year still outpaces 80% of competitor sites in mid-tier US metros, where the typical pattern is 0 to 4 pieces a year.
## Common objections — and the honest answers
The pushback this content discipline gets, in the field:
**"Our customers don't read this kind of content."** They don't read all of it. They read the parts that matter to their specific question. A 2,500-word guide that's structurally extractable lets them land on the H2 that answers their question and read 200 words. The other 2,300 words exist for the next ten customers with different specific questions. Length isn't a usability problem when the structure is right.
**"We don't have time to publish 24 pieces a year."** Most of the time, that's true at first. The output ramps. Month 1 produces less than month 6. Building the editorial template (question H2 inventory, quote-collection rhythm, photo library, service-list reference) front-loads the time investment. By month 4 the per-page time drops by 40-60% because the components are reusable. The capacity constraint is real, but it eases on a predictable curve.
**"Won't this stuff get scraped and used against us by AI engines?"** AI engines extract and credit. Refusing to publish doesn't prevent the extraction; it just ensures the extracted answer comes from a competitor who did the work. The asymmetric outcome favors publishing. If your content is good and your schema is clean, you become the cited source. If you don't publish, someone else gets cited as the authority in your market.
**"Can't we just use AI to write all of this?"** No. AI-generated content without human expertise and verifiable data underperforms across every metric that matters here. AI engines preferentially cite content with E-E-A-T signals (real authors, verifiable credentials, defensible data, real customer quotes). Pure AI-generated content has none of those. Use AI as a drafting assistant for the structural template, then layer in the trade-specific expertise from your team. That works. Letting AI write the whole thing doesn't.
**"How do we measure whether this is actually working?"** Three metrics over a 90-day rolling window. GA4 referral traffic from chatgpt.com, perplexity.ai, claude.ai, and gemini.google.com. Manual prompt audits of your top 10 commercially-important queries across those engines. Google Search Console impression growth on long-tail informational queries. Move all three in the right direction and the discipline is paying off. If only one moves, your content is winning on one surface but missing on others; audit which discipline is weak.
## The trades-content scorecard
Take any existing page on your site. Rate it on each of the 10 criteria below, 0 or 1. A page scoring 8+ is competitive in your metro. A page scoring 5-7 has real gaps but can be improved page-by-page. A page scoring under 5 is unlikely to compound and should be rebuilt rather than edited.
1. **Question-format H2s** — Headings phrased as the questions a real customer would ask
2. **First-sentence answers** — The first 1-2 sentences after each H2 directly answer that H2's question
3. **Specific data with sources** — Generic adjectives ("fast," "affordable," "premium") replaced with sourced numbers
4. **Real customer quotations** — At least three verbatim quotes from real reviews, attributed and linked
5. **Schema markup** — `LocalBusiness` subtype, `Service`, `FAQPage`, and `Quotation`/`Review` schema present and validated
6. **Inline citations** — At least three outbound links to authoritative external sources within the body
7. **Hyper-local depth** — Content specific to a named city (neighborhoods, codes, storm history, local context), not metro-generic
8. **Freshness** — `dateModified` reflects a substantive update within the last 90 days
9. **HTML-first** — Critical content visible in View Source, not rendered by client-side JavaScript
10. **E-E-A-T signals** — Named author byline with credentials, team-member `Person` schema with `worksFor` and `hasCredential`
Run the scorecard on your 10 highest-traffic pages before rebuilding anything new. Most trades sites discover that 3 to 5 of those top pages score under 5, and those are the highest-leverage improvements. The [AEO fundamentals pillar](/guides/aeo-fundamentals/) covers the underlying AEO mechanics. The [schema graphs pillar](/guides/schema-graphs-for-trades/) covers the schema layer. The [local SEO essentials pillar](/guides/local-seo-essentials/) covers the local SEO foundation. The four pillars together describe the full discipline.
---
## Local SEO essentials: how service businesses win in 2026
URL: https://dynamic-promotion.com/guides/local-seo-essentials/
Summary: How Google Business Profile, real reviews, NAP consistency, and LocalBusiness schema combine to win the Map Pack for service businesses in 2026.
For most service businesses, local search is the whole pipeline. A roofer in Watson. A plumber in Denham Springs. A dentist in Baton Rouge. Almost every new customer started with a phone in their hand and a Google query that mentioned a place. The Map Pack and the AI-powered local recommendation panel sit above every other source of traffic for those businesses combined. **If you're invisible there, the rest of your marketing is downstream of a closed faucet.**
This pillar is the foundation of everything Dynamic Promotion will publish about local SEO. It walks through the three signals Google uses to rank local results, the role Google Business Profile plays at the center of every local search, the structural data work (NAP consistency, LocalBusiness schema, citations) that earns algorithmic trust, and how reviews now do double duty as a ranking signal and an AI citation signal. Spokes from this pillar go deeper into individual tactics. This pillar is the one you read first.
## What is local SEO, and why does it matter for service businesses?
Local SEO is the practice of getting your business to rank when someone searches for a service in a specific place. The "place" part is what separates it from regular organic SEO. Google detects geographic intent in two ways. First, an explicit place name in the query ("plumber in Watson"). Second, an implicit one, where Google uses the searcher's location to assume they want a nearby result ("plumber" typed into a phone in Watson returns Watson plumbers regardless of whether the query said so).
When Google detects local intent, the search results page changes shape. Above the regular organic ten blue links sits the **Map Pack** (also called the Local Pack or 3-Pack), a boxed listing of three local businesses with a map, ratings, hours, and direct call buttons. The Map Pack absorbs the majority of clicks on local queries. Ranking organically below the Map Pack still matters, but the click distribution is heavily front-loaded. Position 1 in the Map Pack outperforms position 1 in the regular organic list by a factor of several times for the same query.
The Map Pack runs on different signals than the regular organic algorithm. Your Google Business Profile is the anchor. Your reviews, your photos, your service area, your category, your NAP consistency across the web, and the proximity of the searcher to your verified address all factor in. Most of these signals don't matter for traditional organic ranking at all. That's why a national chain can outrank a local contractor on a generic search and still lose the Map Pack to the same local contractor on the location-qualified version of that search.
The business case is straightforward. Google's most-cited figure on local search, [published via Think with Google](https://www.thinkwithgoogle.com/marketing-strategies/search/local-search-mobile-marketing-statistics/), put local-intent queries at roughly 46% of all searches; the figure is a decade old now, and every signal since points the share higher, not lower. For a service-vertical business, that share is higher. Most contractors, dentists, lawyers, and trade professionals draw 70% or more of their search traffic from queries with explicit or implicit local intent. The local SEO program isn't a tactical add-on. It's the lead-generation engine.
## The three signals Google uses to rank local results
Google has published the official ranking logic for local results, and it's simpler than most algorithms in this domain. The [Google Business Profile help center documents](https://support.google.com/business/answer/7091) three signals that drive local rankings:
Relevance
how well your profile and website match the searcher's query
Driven by category, services, GBP description, and on-site content
Distance
how close your verified address is to the searcher's location
A signal Google measures, not one you can fake. Verify a real address.
Prominence
how well-established and trusted your business is online
Driven by reviews, citations, links, brand mentions, and GBP activity
**Relevance** is the most controllable of the three. Your primary GBP category, your service list, and your website content all contribute to whether Google reads your business as the right match for a query. A roofer whose primary category is "Roofing contractor" with a populated services list (roof replacement, storm damage repair, gutter installation) signals more relevance for the query "roof repair in Watson" than a competitor whose primary category is the broader "Contractor."
**Distance** is the least controllable. The searcher's location at query time anchors the calculation. The closer your verified address is to that location, the higher you tend to rank. There's no shortcut here. Multi-location businesses get to compete in multiple proximity zones, but each location needs to be a real, verifiable place where the business operates.
**Prominence** is the longest-running investment. It's a synthesis of every signal that suggests your business is established, trusted, and active. Review count and freshness, citation consistency across the web, inbound links, brand mentions in news and editorial content, and the recency of your GBP activity all roll into prominence. This is the signal that compounds over years. A business with two years of consistent prominence work outranks one with six months of work, even when relevance and distance favor the newer business.
## Google Business Profile is the single biggest local lever
Of every asset a local business can invest in, the Google Business Profile produces the highest return per hour of work. [Whitespark's Local Search Ranking Factors survey](https://whitespark.ca/local-search-ranking-factors/), conducted with input from dozens of working local SEO practitioners, has put GBP signals at the top of the Map Pack ranking weight for several survey cycles in a row.
The components of a complete GBP listing:
- **Verified address** that matches the address used everywhere else (website, schema, directories)
- **Primary category** that reflects your core service, not the broadest possible category
- **Secondary categories** for the adjacent services you also offer
- **Service list** with descriptions, prices when relevant, and matching service-area coverage
- **Hours of operation** kept current, including holiday hours configured in advance
- **Photos** refreshed at least quarterly. Exterior, team, in-progress work, and finished jobs.
- **Description** populated with your core value proposition in 750 characters or less
- **Q&A section** actively monitored, with the most common questions seeded by you with your own answers
- **Posts** published weekly to keep the listing active
- **Reviews** collected steadily and responded to within 48 hours
That list reads like busywork. It is busywork. The reason it works is that GBP scores active maintenance as a trust signal. A profile that gets touched weekly outranks an equally-rated but neglected profile in the same proximity zone. The compounding effect over six months is substantial.
The most overlooked component is the Q&A section. Most owners never look at it. Google opens the Q&A as a public forum, and any user can post a question or an answer to your listing without your involvement. Bad actors and confused customers populate it with misinformation when you're not watching. The corrective work is straightforward: seed the section yourself with the 5 to 8 questions your real customers ask most often, answer them in your own voice, and check the section weekly for new public questions.
Do this
Pick one canonical NAP. Write it down. Include every detail: business name spelling, suite numbers, abbreviations vs. spelled-out words ("St" vs "Street"), phone number format with consistent dashes or dots.
Then run a free NAP scan at Moz Local or BrightLocal. Both surface every existing listing for your business and flag inconsistencies. Fix the top 10 directories first. The long tail can wait.
The reason NAP consistency matters more in 2026 than it did in 2018 is that AI engines now use the cross-reference graph to verify entities. When an AI summarizer is deciding whether to recommend you, it pulls your `LocalBusiness` schema, then checks whether the same address shows up on Yelp, BBB, Facebook, and your state's secretary of state filings. If those records agree, the AI's confidence in citing you goes up. If they conflict, you get flagged as a low-confidence entity and skipped in favor of a competitor whose records line up.
NAP consistency is also where most agencies short-change their clients. The work is tedious, takes weeks to complete on a neglected business, and produces no immediately visible UI change on the website. It compounds invisibly. Owners who skip this step rarely connect the lack of visible ROI to the underlying inconsistency.
## LocalBusiness schema and structured data essentials
[Schema.org's `LocalBusiness`](https://schema.org/LocalBusiness) type is the structured-data root that every service business needs on their website. It tells search engines (and increasingly, AI engines) the canonical machine-readable version of your business identity. The basic shape, as JSON-LD inside a `
```
A few rules that separate strong schema from weak schema:
1. **Use the most specific subtype.** Don't write `"@type": "LocalBusiness"` when there's a more specific subtype like `RoofingContractor`, `Plumber`, `Dentist`, `HVACBusiness`, `Electrician`, or `Attorney`. [Google's local-business structured data guide](https://developers.google.com/search/docs/appearance/structured-data/local-business) lists the canonical subtypes. The specific subtype gives AI engines a tighter category signal.
2. **Populate `sameAs` with at least 4 verified URLs.** This array is how AI engines verify your entity exists. Include your verified GBP listing URL, your Facebook page, your BBB listing, your LinkedIn company page, and any industry-directory listings (Angi, HomeAdvisor for home services, Healthgrades for medical, etc.).
3. **Match the schema NAP to the GBP NAP exactly.** Every field (name, street address, suite number, phone format, postal code) has to be byte-identical to what's in your Google Business Profile. Any mismatch creates entity-disambiguation problems for AI engines.
4. **Include `geo` coordinates.** The latitude and longitude help AI engines validate the address corresponds to a real place at a real location, not a virtual office shell.
5. **Validate with [Google's Rich Results Test](https://search.google.com/test/rich-results) before deploying.** Schema errors silently downgrade your eligibility. Test every page that emits `LocalBusiness` schema, not just the home page.
For multi-location businesses, the rule is one canonical `LocalBusiness` node per real location, each with its own `@id`, each linked to a per-location page on your site (`/locations/watson/`, `/locations/baton-rouge/`, etc.). The `LocalBusiness` node on your home page should represent your primary or headquarters location.
## Reviews are now a ranking AND citation signal
Reviews have always been important to local SEO. The 2026 update is that they're also one of the most powerful AEO signals. AI engines pull verbatim review quotations into recommendation answers far more readily than other content types, because review text is short, evaluative, attributable to a real person, and easily verifiable through the source platform.
The [BrightLocal Local Consumer Review Survey](https://www.brightlocal.com/research/local-consumer-review-survey/) has tracked consumer behavior around online reviews for over a decade. The headline findings from the 2024 survey:
Avoid
Page builders that emit dozens of plugin-injected scripts (Elementor on WordPress, most Wix sites with apps installed) routinely fail Core Web Vitals on mid-range Android phones. The site loads acceptably on the owner's iPhone Pro and fails on the customer's 3-year-old budget Android, which is the device most local searches come from.
If you can't change the platform, start with image optimization (WebP, lazy loading below the fold, explicit dimensions on every image) and font subsetting. Those two changes alone usually move a failing site to passing.
## How to measure local SEO success
Local SEO has more honest measurement surface than most marketing channels because the conversion paths are short and observable. The 2026 measurement stack for any service business:
**GBP Insights.** Native reporting inside Google Business Profile. Track monthly: searches that surfaced your profile, profile views, direction requests, calls from the listing, and website clicks. The interesting derivative is the search-term report, which shows the exact queries that triggered your listing in the last 30 days. That's free competitive intelligence about how customers describe the work you do.
**Google Search Console.** Filter to "Discover and Search" performance, then look at queries with geographic terms. A "Country: United States, Region: Louisiana" filter on a Watson roofer's GSC narrows to the queries that matter. Track impression growth and click-through rate monthly.
**Rank tracking for the queries that matter.** Whitespark, BrightLocal, and Local Falcon all offer grid-based rank tracking that shows where you rank in the Map Pack from different physical points within your service area. The grid view is more useful than a single rank because it reveals the proximity gradient that drives local rankings. You might rank #1 from a query origin near your office and #6 from one across town.
**Call tracking.** Most local-business leads come by phone. Without call tracking, you can't attribute calls to specific channels. CallRail or Callsource (or a built-in option from your CRM) lets you route different phone numbers to different channels and measure call volume per channel.
**Review monitoring.** A weekly check of new reviews across GBP, Facebook, Yelp, and BBB. Respond within 48 hours. Track response rate as a KPI. Your own response cadence is the one signal you have direct control over.
**AI citation monitoring** (the new layer in 2026). Run monthly prompt audits of 5 to 10 commercially important queries across ChatGPT, Perplexity, Claude, Google AI Overviews, and Gemini. Track whether you appear, whether you're mentioned by name, and whether you're cited with a link. Free to run manually; dedicated monitoring platforms make sense only after the query list outgrows a spreadsheet.
The cadence that works for most owners is a 30-minute weekly check (reviews, GBP posts, any new questions in Q&A) plus a 90-minute monthly deep-dive (GBP Insights, GSC, rank tracking, AI citation audit). Less than that and you stop noticing trends. More than that and the time isn't paying off.
## Where to start, and in what order
Everything above reduces to a sequence: the three signals Google uses, the Google Business Profile work that anchors every local SEO program, the NAP consistency discipline, the LocalBusiness schema that builds an entity Google and AI engines can verify, the role of real reviews as both a ranking and AEO signal, the directory layer that still matters, the per-city content depth that wins service-area queries, the technical floor on mobile, and how to measure whether any of it is working.
The right order for a business starting from zero: GBP setup and verification first, NAP audit and reconciliation across the top 10 directories second, LocalBusiness schema with full `sameAs` array third, a per-service-area content build fourth, review collection rhythm and response cadence fifth, technical and Core Web Vitals work sixth, ongoing measurement and monthly adjustment seventh.
Expect 60 to 90 days before Map Pack rankings start moving on commercially important queries. Expect 4 to 6 months before citation work fully compounds. Expect AEO citation share to start showing within the first 30 to 60 days of consistent on-site work because AI engines crawl and reweight content more frequently than Google reindexes for traditional ranking.
Every site Dynamic Promotion builds for a local-business client ships with the local SEO baseline described here. GBP setup as part of onboarding. LocalBusiness schema with the full `sameAs` array. NAP audit before launch. Per-city service-area pages. Quotation schema on real review excerpts. Deeper guides on multi-location architecture, review-collection automation, service-area mapping, and Apple Business Connect will hang off this pillar as they publish.
The opportunity in 2026 is the same one it's been for several years running: most local-business sites in mid-tier US markets still ship without `LocalBusiness` schema, with inconsistent NAP across directories, with stale GBP listings, and with no per-city content depth. The early movers who do the work compound disproportionate ranking and citation share. The window is still open. It won't be in three years.
---
## Schema graphs for trades: the one-graph-per-page pattern
URL: https://dynamic-promotion.com/guides/schema-graphs-for-trades/
Summary: How to wire LocalBusiness, Service, Review, and Person schema into one @id-connected JSON-LD graph that wins Google rich results and AI citations.
Picture two roofing contractors shipping identical-looking service pages in the same zip code. Same hero photo style. Same "Get a free quote" CTA. Same five trust badges. Both get the same Google Lighthouse score. In that scenario, one keeps showing up in Perplexity recommendations and Google's AI Overviews for "roof replacement" queries while the other doesn't, and nobody on the losing team can figure out why. The difference is almost always in the JSON-LD. The first site emits one connected schema graph per page with `@id`-linked entities. The second emits five loose schema blocks that look right in isolation and tell the AI engine nothing about how the entities relate.
This pillar is the JSON-LD reference for trades businesses. It covers the structural pattern (one graph per page, not loose blocks), the subtype selection that pins your business to the right Schema.org branch, the node-by-node walkthrough of what a complete trades-business graph contains, and the validation toolchain that catches the silent errors. Code samples are real and copy-pasteable. The trade names in the examples are interchangeable. Pick the one closest to your business and substitute.
## One graph, not loose blocks — the structural mistake most trades sites make
The default WordPress + Yoast pattern, and the default for most page-builder sites, is multiple `
```
Three nodes, three `@id`s, two cross-references. The `WebSite.publisher` points to `#org` instead of repeating the `RoofingContractor` data. The `WebPage.isPartOf` points to `#website` instead of repeating the `WebSite` data. The crawler now reads this as one connected entity graph instead of three disconnected ones, and every page across the site that uses the same `#org` and `#website` `@id`s contributes to the same coherent graph.
That last point matters more than the rest of this section combined. Sitewide entities like `Organization` and `WebSite` keep the same `@id` across every page on the site. Page-specific entities like `WebPage` and `Article` include the page path in the `@id` so they're unique per URL. That convention is what lets Google and the AI engines deduplicate your business correctly across hundreds of crawled pages.
## Pick the deepest `LocalBusiness` subtype Schema.org offers for your trade
[Schema.org's `LocalBusiness`](https://schema.org/LocalBusiness) is the root type for any place-based business. Underneath it sits [`HomeAndConstructionBusiness`](https://schema.org/HomeAndConstructionBusiness), which is the branch trades businesses live on. Underneath that sit the named subtypes that match specific trades:
| Trade | Schema.org type | Inheritance chain |
|---|---|---|
| Roofing contractor | [`RoofingContractor`](https://schema.org/RoofingContractor) | LocalBusiness > HomeAndConstructionBusiness > RoofingContractor |
| Plumber | [`Plumber`](https://schema.org/Plumber) | LocalBusiness > HomeAndConstructionBusiness > Plumber |
| Electrician | [`Electrician`](https://schema.org/Electrician) | LocalBusiness > HomeAndConstructionBusiness > Electrician |
| HVAC | [`HVACBusiness`](https://schema.org/HVACBusiness) | LocalBusiness > HomeAndConstructionBusiness > HVACBusiness |
| General contractor | [`GeneralContractor`](https://schema.org/GeneralContractor) | LocalBusiness > HomeAndConstructionBusiness > GeneralContractor |
| Painter | [`HousePainter`](https://schema.org/HousePainter) | LocalBusiness > HomeAndConstructionBusiness > HousePainter |
| Moving company | [`MovingCompany`](https://schema.org/MovingCompany) | LocalBusiness > HomeAndConstructionBusiness > MovingCompany |
| Locksmith | [`Locksmith`](https://schema.org/Locksmith) | LocalBusiness > HomeAndConstructionBusiness > Locksmith |
A trade that doesn't have a named subtype (drywall, masonry, gutter specialists, foundation repair, etc.) inherits the next level up. Use `HomeAndConstructionBusiness` for those. Don't fall back further to bare `LocalBusiness`, and definitely don't use plain `Organization`. The whole point of the subtype hierarchy is the tighter topical signal it sends to crawlers.
The full `RoofingContractor` node, in production form:
```json
{
"@type": "RoofingContractor",
"@id": "https://watson-roofing.com/#org",
"name": "Watson Roofing Co.",
"image": "https://watson-roofing.com/images/logo.png",
"url": "https://watson-roofing.com",
"telephone": "+1-225-555-0100",
"address": {
"@type": "PostalAddress",
"streetAddress": "1234 Main Street",
"addressLocality": "Watson",
"addressRegion": "LA",
"postalCode": "70786",
"addressCountry": "US"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 30.5089,
"longitude": -90.9123
},
"openingHoursSpecification": [
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday","Friday"],
"opens": "07:00",
"closes": "18:00"
}
],
"areaServed": [
{ "@type": "City", "name": "Watson" },
{ "@type": "City", "name": "Baton Rouge" },
{ "@type": "City", "name": "Denham Springs" }
],
"priceRange": "$$",
"knowsAbout": [
"Asphalt shingle roof replacement",
"Metal roofing systems",
"Storm-damage insurance claims"
],
"sameAs": [
"https://g.page/r/CXXX...",
"https://www.facebook.com/watsonroofing",
"https://www.linkedin.com/company/watson-roofing",
"https://www.bbb.org/us/la/watson/profile/.../"
]
}
```
Schema.org's own description of what a `LocalBusiness` is, verbatim:
Do this
Source aggregateRating from reviews you actually collect and display on your own site, paired with visible Review or Quotation content a reader can see. Keep the numbers consistent with what a customer would find on your public profiles; if your site claims 4.9 from 132 reviews and your Google Business Profile shows something different, that mismatch is an integrity signal working against you.
Use reviewCount (the integer total) plus ratingValue (the average to one decimal). Don't fabricate. Google's spam team catches mismatched aggregates at scale, and an enforcement action removes your rich-results eligibility across the entire site, not just the one page.
Avoid
aggregateRating copied or summed from third-party platforms (Google reviews, BBB) into your own markup. Google's review-snippet guidance requires ratings to come from reviews collected by the site itself; importing platform numbers into self-markup violates it.
Counting on stars in the SERP. Self-serving review markup has been excluded from star display since 2019; treat the property as entity corroboration, not a rich-result play.
## The page-level nodes: `BreadcrumbList`, `WebPage`, `Article`
Beyond the business-level entities, every page in your graph needs page-level nodes. Three types cover most cases.
**`BreadcrumbList`** describes the navigation path to the current page. It powers the visible breadcrumb trail in Google search results. The node lists the path items in order:
```json
{
"@type": "BreadcrumbList",
"@id": "https://watson-roofing.com/services/replacement/#breadcrumbs",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://watson-roofing.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Services",
"item": "https://watson-roofing.com/services/"
},
{
"@type": "ListItem",
"position": 3,
"name": "Roof Replacement",
"item": "https://watson-roofing.com/services/replacement/"
}
]
}
```
**`WebPage`** is the wrapper for the current URL. It connects to the sitewide `WebSite` via `isPartOf` and points at the main content entity (a `Service`, `Article`, or whatever the page is primarily about) via `about` or `mainEntity`:
```json
{
"@type": "WebPage",
"@id": "https://watson-roofing.com/services/replacement/#webpage",
"url": "https://watson-roofing.com/services/replacement/",
"name": "Roof Replacement in Watson, LA",
"isPartOf": { "@id": "https://watson-roofing.com/#website" },
"about": { "@id": "https://watson-roofing.com/services/replacement/#service" },
"breadcrumb": { "@id": "https://watson-roofing.com/services/replacement/#breadcrumbs" },
"datePublished": "2026-05-28",
"dateModified": "2026-05-28"
}
```
**`Article`** (or `BlogPosting`) applies to long-form content like guides and blog posts. It carries the headline, byline, publish date, modification date, and content references:
```json
{
"@type": "Article",
"@id": "https://watson-roofing.com/blog/roof-lifespan/#article",
"headline": "How long does an asphalt roof actually last in Louisiana?",
"author": { "@id": "https://watson-roofing.com/team/mike-watson/#person" },
"publisher": { "@id": "https://watson-roofing.com/#org" },
"datePublished": "2026-05-15",
"dateModified": "2026-05-15",
"mainEntityOfPage": { "@id": "https://watson-roofing.com/blog/roof-lifespan/#webpage" }
}
```
For pages that contain a Q&A section, add [`FAQPage`](https://schema.org/FAQPage). For step-by-step how-to content, add [`HowTo`](https://schema.org/HowTo). Both are well-documented in Google Search Central, both unlock real rich-results entitlements, and both are extracted aggressively by AI engines for citation answers.