How AI Search Is Recommending Commercial Cleaning Services: Monthly Trends

Executive Summary

The commercial cleaning category is compressing from above. Jan-Pro remains the coverage leader but fell 8.8 points from 57.2% in July 2026 to 48.4% in September 2026, a significant decline over the three-month window. The leader's gap to the next brand, Stratus Building Solutions at 27.0%, now stands at 21.4 points, down from a 18.4-point gap in July 2026. This is a category where the top tier is losing ground while the bottom tier rises.

City Wide Facility Solutions is the standout riser, climbing 10.6 points from 4.6% in July 2026 to 15.2% in September 2026. That gain is significant and marks two consecutive months of upward movement, moving the brand from the bottom of the tracked set into the middle of the pack. Its raw mention presence more than tripled from 4.9% to 18.2% over the same window.

The sharpest decliner is ServiceMaster Clean, down 13.1 points from 31.3% in July 2026 to 18.2% in September 2026. That is a significant drop, driven largely by an 8.6-point single-month fall in August. Eight of the ten tracked brands recorded significant declines from baseline, making September 2026 a month of broad redistribution rather than isolated movement. The category summary is mixed, with one significant riser, eight significant decliners, and one stable brand.

Each monthly run begins with 800 prompt-surface observations (582 unique questions in September 2026, up from 532 in July 2026). Of those, 800 mentioned a tracked brand or competitor; 497 were relevant and 303 were irrelevant. The public benchmark reflects the 374 observations that survive both qualification stages, up from 348 in July 2026.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The Jul 2026 and Sep 2026 periods shown here, along with the August 2026 period reflected in the trend line, share the same platform set, company roster, and query-volume treatment, so the benchmark-level metrics below can be compared directly across the full three-month window.

Benchmark-Level Metrics

AI Recommendation Trend

The Top Tier Is Compressing While the Category Rebalances

The commercial cleaning category is undergoing a broad rebalancing, with the top tier losing recommendation share and the lower tier gaining it. Jan-Pro's 48.4% coverage still leads the field, but its 8.8-point decline from July 2026 is significant. The middle of the table tightened considerably, with Stratus Building Solutions at 27.0%, Jani-King at 24.6%, and ServiceMaster Clean at 18.2% forming a closer cluster than at baseline.

The category-level movement came from a combination of individual results: one brand rose significantly and eight declined beyond normal variation over the three-month window, while one brand held stable. This is not a quiet quarter; it is a significant redistribution of recommendation credit from the top tier toward the middle and lower tiers.

What Changed This Month

City Wide Facility Solutions

City Wide Facility Solutions is the only significant riser in the category, climbing 10.6 points from 4.6% valid recommendation coverage in July 2026 to 15.2% in September 2026. The brand has risen in each of the two consecutive months, with its largest single-month gain of 6.1 points occurring between July and August.

Its raw mention presence more than tripled from 4.9% in July 2026 to 18.2% in September 2026, a 13.3-point increase that is significant. Its top-three rate climbed from 2.3% to 9.1%, and its rank-one rate rose from 0.9% to 2.9%. The brand reached 57 valid recommendations in September, up from 16 in July.

The distinction here is that City Wide's rise spans presence, top-three placement, and rank-one position simultaneously. It is not merely being mentioned more often; it is being recommended in shortlists at a higher rate and occasionally as the top pick.

Highest-priority diagnostic: Which prompt clusters and surfaces drove the sustained coverage gains across two months, and which competitor's lost recommendation credit did City Wide capture?

ServiceMaster Clean

ServiceMaster Clean recorded the largest decline in the category over the three-month window, falling 13.1 points from 31.3% valid recommendation coverage in July 2026 to 18.2% in September 2026. The sharpest single-month drop was 8.6 points between July and August.

Its raw mention presence fell from 44.8% to 34.0%, a 10.9-point decline that is significant. Its top-three rate dropped from 17.5% to 11.0%, and its rank-one rate fell from 6.9% to 2.7%, both significant declines. The brand logged 68 valid recommendations in September, down from 109 in July.

The commercial signal is that ServiceMaster Clean lost presence and recommendation depth together, with its rank-one rate falling more than 4 points. The brand is appearing less often and, when it does appear, less frequently as the top pick.

Highest-priority diagnostic: Which prompt clusters stopped surfacing ServiceMaster Clean, and did the rank-one loss concentrate in specific geographies or service types?

Jan-Pro

Jan-Pro's 8.8-point decline from 57.2% in July 2026 to 48.4% in September 2026 is significant, ending a period of stable leadership at the top of the category. The brand's raw mention presence held relatively firm at 71.9% versus 74.1% at baseline, a non-significant change.

Its top-three rate eased from 47.1% to 41.7%, and its rank-one rate dipped from 27.0% to 25.9%, neither individually significant. The brand logged 181 valid recommendations in September, down from 199 in July.

The distinction is that Jan-Pro lost recommendation coverage while maintaining a stable presence share, meaning AI systems are mentioning the brand across roughly the same share of prompts but recommending it in fewer of those instances.

Highest-priority diagnostic: Which prompt types shifted from recommending Jan-Pro to recommending another brand, and what attributes are being associated with the alternatives?

Stratus Building Solutions

Stratus Building Solutions fell 11.8 points from 38.8% in July 2026 to 27.0% in September 2026, a significant decline that moves the brand from clear second place into a tighter cluster with Jani-King.

Its raw mention presence dropped from 47.7% to 38.0%, a 9.7-point decline that is significant. Its top-three rate fell from 28.4% to 21.4%, and its rank-one rate dropped from 9.8% to 4.5%, both significant. The brand logged 101 valid recommendations in September, down from 135 in July.

The commercial signal is that Stratus lost ground across every recommendation layer, with its rank-one rate roughly halving over the window. The brand is present less often, recommended in shortlists less often, and chosen as the top pick far less frequently.

Highest-priority diagnostic: Which competitor captured Stratus's lost rank-one recommendations, and did the decline concentrate in specific AI surfaces?

ABM Industries, Anago Cleaning Systems, Coverall, Jani-King, and Vanguard Cleaning Systems

ABM Industries fell 7.4 points from 10.3% to 2.9%, a significant decline with an additional 4.1-point drop between August and September. The brand logged 11 valid recommendations in September, down from 36 in July.

Anago Cleaning Systems declined 10.7 points from 23.8% to 13.1%, with its top-three rate falling from 12.4% to 7.0%. It logged 49 valid recommendations in September, down from 83 in July.

Coverall fell 9.4 points from 23.8% to 14.4%, with its largest single-month drop of 6.6 points occurring between July and August. It logged 54 valid recommendations in September, down from 83 in July.

Jani-King declined 7.3 points from 31.9% to 24.6%, with its rank-one rate actually improving from 4.0% to 4.8%. It logged 92 valid recommendations in September, down from 111 in July.

Vanguard Cleaning Systems fell 11.0 points from 24.1% to 13.1%, with its raw mention presence dropping from 25.9% to 15.8%. It logged 49 valid recommendations in September, down from 84 in July.

All five brands lost recommendation coverage over the window, though Jani-King's improving rank-one rate suggests it still wins top placement when recommended.

Highest-priority diagnostic: For each brand, is the decline driven by lost presence across fewer prompts or by lower recommendation rates within prompts where the brand still appears?

Buyer-Intent Interpretation

All 374 qualified observations in September 2026 fell into the brand recommendation cluster, the same pattern as July 2026 (348 of 348). The qualified benchmark set captures discovery and consideration queries, where AI systems recommend or rank providers. The public benchmark cannot yet answer pricing, value, or head-to-head comparison questions, because no qualified observations fell into those clusters this month or at baseline. Those commercial questions remain open for company-level analysis.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Small-count movements: Brands such as ISS Facility Services and ABM Industries operate on very few valid recommendations (4 and 11 in September respectively), so percentage movement for these brands carries less weight than for brands with larger counts.
• Qualified denominator: All brand-level percentages are calculated within the 374 qualified observations, not the 800 raw prompts collected.
• Directional analysis: Month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate coverage percentages sit the questions that matter for competitive position: which high-intent prompts a brand wins, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers. The benchmark surfaces the pattern; it does not explain the mechanism.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers the "why" behind the movement, so a brand can act on the opportunities the benchmark identifies.

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