The Majority of Landscapers Are Invisible to AI Discovery Tools
63% of the 58,000+ landscaping contractors tracked by VerifiedNode sit in the low-score tier. That is 36,604 businesses that AI assistants, voice search tools, and LLM-powered recommendation engines are effectively skipping over.
The distribution across tiers tells a stark story:
| Score Tier | Contractor Count | Share of Total |
|---|---|---|
| High | 3,562 | 6% |
| Medium | 17,697 | 31% |
| Low | 36,604 | 63% |
Only 6% of tracked landscapers reach the high-score tier. The remaining 94% are either partially visible or invisible to the AI-driven discovery layer that is increasingly mediating how homeowners find service providers.
The visibility gap traces back to a specific technical failure: only 10% of contractors globally have JSON-LD structured data on their websites. JSON-LD is the markup format that search engines and AI platforms use to parse business details reliably. Without it, a contractor's name, service area, phone number, and specialty categories are essentially unreadable to automated systems.
The contrast with basic web presence makes this gap more striking. 89% of contractors have a website. The infrastructure exists. The structured data layer is missing.
Claimed profile status tells a similar story. Only 17% of contractors have claimed their business profiles across major platforms. Unclaimed profiles generate incomplete or conflicting signals, which AI systems resolve by deprioritizing or omitting the listing entirely.
For landscaping businesses specifically, this has direct revenue implications. AI assistants handling queries like "find a landscaper near me" or "who does lawn care in [city]" pull from structured data first. A contractor without JSON-LD and a claimed profile loses that referral before a homeowner ever makes a call. The contractor may have 200 Google reviews and a polished website, but if the machine-readable layer is absent, the visibility benefit of that reputation does not transfer to AI-powered channels.
The 89% website figure confirms this is not a resource problem. Most landscapers have the digital foundation. The specific, addressable gap is structured data adoption and profile verification: two changes that directly determine whether AI tools surface a business or skip it.
The full breakdown by state, city, and individual contractor score is available across VerifiedNode's directory pages at /landscapers/. Check your own score at /find, or review regional patterns in the State of the Market reports.
National Score Distribution: Top and Bottom Markets
Across the 65 qualified markets in the VerifiedNode rankings, the spread between leaders and laggards is not marginal. Manitoba sits at the top with an average score of 41.7. Vancouver and Dallas sit at the bottom, both at 3.9. That is a 10x gap between the highest and lowest performing markets in the dataset.
| Market | Rank | Avg Score | Total Businesses | Website % | JSON-LD % |
|---|---|---|---|---|---|
| Manitoba | 1 | 41.7 | 673 | 72% | 2% |
| Northwest Territories | 2 | 38.9 | 97 | 63% | 4% |
| Ontario | 3 | 38.5 | 11,095 | 75% | 5% |
| Alberta | 4 | 38.5 | 3,600 | 82% | 7% |
| Portland | 56 | 5.0 | 520 | — | — |
| Atlanta | 59 | 4.5 | 508 | — | — |
| Calgary | 60 | 4.2 | 628 | — | — |
| Chicago | 61 | 4.1 | 659 | — | — |
| Seattle | 62 | 4.1 | 551 | — | — |
| Denver | 63 | 4.0 | 593 | — | — |
| Dallas | 64 | 3.9 | 598 | — | — |
| Vancouver | 65 | 3.9 | 559 | — | — |
The top four markets are all Canadian provinces. The bottom ten are predominantly large US metro areas.
Market Size Does Not Explain Performance
The intuitive explanation for why smaller markets score higher is that there are fewer businesses to drag the average down. The data does not support that explanation cleanly.
Northwest Territories has 97 landscaping businesses and an average score of 38.9. Ontario has 11,095 businesses and an average score of 38.5. The difference is 0.4 points across a 114x difference in market size. Scale alone is not the driver.
Calgary has 628 businesses and an average score of 4.2. Manitoba has 673 businesses and scores 41.7. Nearly identical market sizes, 10x score difference. Something other than business count is separating these markets.
The more likely explanation is baseline adoption of visibility infrastructure: whether businesses in a given market have websites, structured data, and claimed profiles at all. Canadian provincial markets, even large ones like Ontario and Alberta, show higher website penetration and structured data adoption than the bottom-ranked metros.
Alberta leads all ranked markets with 82% website adoption and 7% JSON-LD penetration. That 7% is still well below the global average of 10%, but it is more than triple Manitoba's JSON-LD rate of 2%. Manitoba's top ranking despite low JSON-LD adoption suggests its score is driven by other visibility signals, likely review volume and profile completeness, where its average of 60 reviews per business outpaces most markets.
The Structured Data Gap Is the Central Problem
89% of contractors globally have a website. 10% have JSON-LD. That disconnect is the core issue.
A landscaping business with a website but no structured data has built a digital presence that ranks reasonably well in traditional search but transmits almost nothing useful to AI discovery systems. AI tools do not scrape websites the way crawlers do. They rely on structured, machine-readable signals: JSON-LD schema, claimed and verified profiles, consistent NAP (name, address, phone) data across platforms.
The four top-ranked markets show how far even leading regions fall short of that baseline:
| Market | JSON-LD Adoption |
|---|---|
| Manitoba | 2% |
| Northwest Territories | 4% |
| Ontario | 5% |
| Alberta | 7% |
| Global Average | 10% |
No top-ranked market reaches the global average for JSON-LD adoption. The leaders are leading by a narrow margin in a field where nearly everyone is underinvested.
The Verification Gap Compounds the Problem
Only 17% of contractors tracked by VerifiedNode have claimed their business profiles. That means 83% are operating with profiles they do not control, cannot update, and cannot optimize.
Unclaimed profiles are a compounding liability. Outdated phone numbers, incorrect service areas, and missing category tags persist because no one is logged in to correct them. AI systems encountering conflicting or incomplete signals across platforms apply a straightforward resolution: they deprioritize or omit the listing.
A contractor with 150 Google reviews and a strong website can still register as effectively invisible to AI tools if the structured data layer is absent and the profile is unclaimed. The review equity does not transfer to channels that cannot parse the underlying signals.
For regional market context and contractor-level scores, see the Alberta landscapers directory, the Ontario landscapers directory, and the full State of the Market reports. Check your individual score at /find.
Methodology
VerifiedNode computes AI visibility scores for 58,000+ landscaping contractors across 65 qualified markets. Scores incorporate website presence, JSON-LD structured data, claimed profile status, review count, rating, and cross-platform signal consistency. Data for this report was fetched on 2026-04-03. Market rankings require a minimum business count threshold to qualify. State-level data reflects provincial boundaries for Canadian markets and metro-area definitions for US cities.
Breakdown by State: Top and Bottom Markets
The pattern separating high-scoring markets from low-scoring ones is geographic, but not in the way you might expect. It is not about country, region, or climate. It is about contractor density and the digital infrastructure choices that density shapes.
Top 5 Markets
| Market | Rank | Avg Score | Total Businesses |
|---|---|---|---|
| Manitoba | 1 | 41.7 | 673 |
| Northwest Territories | 2 | 38.9 | 97 |
| Ontario | 3 | 38.5 | 11,095 |
| Alberta | 4 | 38.5 | 3,600 |
Manitoba leads all 65 qualified markets at an average score of 41.7. That number is not driven by Winnipeg. It is driven by smaller surrounding communities where competitive pressure is lower and individual businesses have stronger incentive to differentiate through digital presence.
Manitoba's top-performing cities by average score:
- Navin: 50.3 (7 businesses)
- Sunnyside: 49.9 (20 businesses)
- Niverville: 47.6 (7 businesses)
- Oakbank: 46.1 (20 businesses)
- Kleefeld: 45.6 (9 businesses)
None of these are major urban centres. Each has a small business count, which means a handful of well-optimized contractors can shift the city average meaningfully. The same pattern holds in Ontario, where the province's top-scoring cities are suburban and rural communities well outside Toronto.
Ontario's top cities by average score:
- Ariss: 58.5 (6 businesses)
- Sutton: 54.4 (5 businesses)
- Carp: 54.3 (20 businesses)
- St Jacobs: 50.6 (14 businesses)
- St Catharines: 48.9 (8 businesses)
Ontario's provincial average is 38.5 across 11,095 businesses. Its best-performing cities outperform that average by 10 to 20 points. Small-market concentration is the driver, not provincial policy or geography.
The tier distributions for these top markets reveal a consistent internal weakness. Even the leaders are mostly concentrated in the fair tier:
| Market | Excellent % | Good % | Fair % |
|---|---|---|---|
| Manitoba | 11.4% | 14.3% | 56.8% |
| Northwest Territories | 7.2% | 18.6% | 42.3% |
| Ontario | 8.2% | 13.0% | 56.3% |
Manitoba has 77 excellent-tier businesses out of 673 total. Ontario has 909 excellent-tier businesses out of 11,095. In both markets, the majority sits in fair. Leading these rankings does not mean performing well in absolute terms. It means performing less poorly than the competition.
Northwest Territories is a special case: Yellowknife is the only tracked city in the territory, with all 97 businesses concentrated in one market and an average score of 38.9. There is no small-suburb effect here. The score reflects that single mid-sized northern city, with an average rating of 4.61 and an average review count of just 11.0.
Bottom 5 Markets
| Market | Rank | Avg Score | Total Businesses |
|---|---|---|---|
| Vancouver | 65 | 3.9 | 559 |
| Dallas | 64 | 3.9 | 598 |
| Denver | 63 | 4.0 | 593 |
| Seattle | 62 | 4.1 | 551 |
| Chicago | 61 | 4.1 | 659 |
The bottom five markets share a structural profile: high contractor counts, intense competition, and average scores below 5.0. Chicago has the most businesses of any bottom-market city at 659 and scores 4.1. Dallas has 598 businesses and scores 3.9. The volume is there. The visibility infrastructure is not.
In dense urban markets, the competitive calculus works against digital investment at the individual business level. There are enough inbound leads from referrals, yard signs, and basic Google presence that structured data and profile verification feel optional. The aggregate result is a market where most contractors are undifferentiated from an AI signal standpoint, and the average score reflects that.
Vancouver and Calgary, both Canadian cities, sit at the bottom of the table alongside US metros: Vancouver at 3.9 (rank 65) and Calgary at 4.2 (rank 60). Geographic proximity to Manitoba's top-ranked contractors does not translate into score proximity.
For city-level contractor data in these markets, see the Manitoba landscapers directory, the Ontario landscapers directory, and the Alberta landscapers directory. Full regional patterns are documented in the State of the Market reports.
Methodology
VerifiedNode calculates AI visibility scores for 58,000+ landscaping contractor records across 65 qualified markets in the United States and Canada. Each contractor receives a score out of 100 points, distributed across three categories.
Scoring categories:
| Category | Points | What It Measures |
|---|---|---|
| Identity | 25 | Business name consistency, address verification, phone number accuracy across sources |
| Legitimacy | 35 | License verification, insurance status, public records cross-referencing, Google Business Profile claim status |
| Readability | 40 | Website crawlability, JSON-LD structured data presence, review count and recency, schema markup completeness |
Readability carries the highest weight because it most directly determines whether AI discovery systems can parse and surface a business. A contractor can have a valid license and a consistent address but still register as invisible if the machine-readable layer on their website is absent.
Data sources:
- Google Business Profile data (ratings, review counts, claim status, category tags)
- Public contractor license databases (cross-referenced by state and province)
- Website crawls (crawlability checks, JSON-LD detection, schema markup validation)
- Review aggregation across platforms (count, recency, consistency of NAP signals)
Sample and qualification thresholds:
The dataset covers 58,000+ contractor records. Markets must meet a minimum business count threshold to qualify for ranked comparison. 65 markets qualified for this report. State-level data uses provincial boundaries for Canadian markets and metro-area definitions for US cities. Data for this report was fetched on 2026-04-03.
Understanding the average versus median gap:
The averages in this dataset consistently sit above the medians, and that gap reflects a real structural pattern. In Manitoba, the average score is 41.7 and the median is 37.0. In Ontario, the average is 38.5 and the median is 35.0. In Northwest Territories, the average is 38.9 and the median is 33.0.
That 4 to 6 point spread means a relatively small number of high-scoring contractors are pulling the market average upward, while the majority of businesses cluster below it. The median is the more accurate representation of what a typical contractor in that market scores.
The global tier breakdown confirms this shape. Across all 58,000+ tracked records: 63% sit in the low-score tier, 31% in medium, and 6% in high. Only 17% of contractors have claimed profiles. Only 10% have JSON-LD structured data. The average flatters the field. The median and tier distribution describe it accurately.
This methodology section is intended to support citation by journalists, researchers, and contractors evaluating AI visibility benchmarks. Score data is updated on a rolling basis. Historical snapshots and full contractor-level records are available through the State of the Market reports and the VerifiedNode directory at /landscapers/.
Frequently Asked Questions
What is the average AI visibility score for landscaping contractors nationally?
The national picture skews heavily toward the low end. Across 58,000+ contractors tracked by VerifiedNode, 63% fall into the low-score tier, 31% reach medium, and only 6% achieve a high score. The scoring system runs from 0 to 100 points across three categories: Identity, Legitimacy, and Readability. Most contractors are not failing on identity or legitimacy. They are failing on readability, which is the category most directly tied to whether AI tools can parse and surface a business.
Which state or province has the best-scoring landscapers?
Manitoba ranks first among all 65 qualified markets with an average score of 41.7 across 673 tracked businesses. The next three positions are also held by Canadian provinces: Northwest Territories at 38.9, Ontario at 38.5, and Alberta at 38.5. The lowest-ranked markets, Vancouver and Dallas, both sit at 3.9. That is a 10x gap between the top and bottom of the table. Leading the rankings does not mean performing well in absolute terms: even Manitoba's majority sits in the fair tier, with only 11.4% of its businesses reaching excellent.
What percentage of landscaping contractors have a website?
89% of contractors in the VerifiedNode dataset have a website. That figure is not the problem. The problem is what those websites are missing: only 10% of contractors globally have JSON-LD structured data, and only 17% have claimed their business profiles. The infrastructure exists for nearly nine in ten businesses. The machine-readable layer built on top of that infrastructure is absent for nine in ten of the same businesses.
What is JSON-LD and why does it matter for contractors?
JSON-LD is a structured data format that tells AI systems, search engines, and voice tools exactly what a business is, where it operates, and what services it provides. Without it, that information has to be inferred from unstructured page content, and AI platforms frequently skip businesses where inference is unreliable. Only 10% of the 58,000+ contractors in this dataset have JSON-LD in place. A contractor without it can have strong reviews and a polished website and still not appear in AI-mediated referrals, because the signal those platforms rely on is absent.
How does VerifiedNode calculate contractor scores?
Each contractor receives a score out of 100 points distributed across Identity (25 points), Legitimacy (35 points), and Readability (40 points). Readability carries the highest weight because it most directly determines AI discoverability: it covers website crawlability, JSON-LD presence, schema markup completeness, and review recency. Data sources include Google Business Profile records, public license databases, website crawls, and cross-platform review aggregation. The full methodology is documented in the State of the Market reports. Check your own score at /find.