Background Checks: AI Visibility Market Discovery Index

Benchmark Summary

In October 2026, Checkr led the background checks category with valid recommendation coverage of 72.6%, up from 65.4% in July 2026. The gap to GoodHire, the second-place brand at 61.1% valid recommendation coverage, was 11.5 percentage points. Checkr was the series' significant riser, climbing 9.8 points from 62.8% in September 2026 to 72.6% in October 2026. Universal Background Screening was the series' significant decliner, falling from 1.4% in July 2026 to 0.2% in October 2026, even though its coverage held flat between September and October. Coverage movement at the top and bottom is diverging sharply.

HireRight posted the largest increase within normal month-to-month variation, rising 6.0 points from 35.1% in September 2026 to 41.1% in October 2026, its second consecutive monthly gain. The benchmark began with 800 prompt-surface observations in each month and produced 504 qualified observations after qualification.

Current Benchmark at a Glance

Qualified surface breadth is the number of canonical AI/search surface families with at least one qualified observation: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. The full breadth of six was maintained in both months. The benchmark's structural coverage is stable, with only the recommendation share shifting.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Background Checks

Research Scope and Qualification

The public benchmark is narrower than the raw collection universe by design.

Brand-level percentages use the qualified observations as the public denominator, not the raw collection. Link AI Visibility Market Discovery Methodology. Published percentages do not reflect the full raw collection.

Current Brand Standings

Questions This Section Answers

• Which background check brands lead the October 2026 recommendation standings?
• How do presence, valid recommendation coverage, and top-three rates differ across the leading brands?

This table is the primary current-month benchmark view for October 2026, sorted by valid recommendation coverage.

How to Read the Standings

• Presence rate: Share of qualified observations where the brand was mentioned at all.
• Valid recommendation coverage: Share of qualified observations where the brand received a valid recommendation.
• Top-three rate: Share of qualified observations where the brand appeared in the top three recommended positions.
• Rank-one rate: Share of qualified observations where the brand was the first recommendation.
• Net sentiment: Balance of positive over negative mentions, from minus 1 to 1.

For formulas and denominator rules, see AI Visibility Market Discovery Metric Definitions.

Recommendation Coverage Movement

Questions This Section Answers

• Which background check brands saw the largest recommendation coverage changes since July 2026?
• What separated Checkr's rise from Universal Background Screening's decline across the series?

Between September 2026 and October 2026, Checkr rose 9.8 points from 62.8% to 72.6%, and GoodHire rose 7.1 points from 54.0% to 61.1%. HireRight climbed 6.0 points from 35.1% to 41.1%, its second consecutive monthly gain. Only Checkr and HireRight moved beyond normal month-to-month variation to the upside.

Largest Increase: Checkr

Checkr's coverage moved beyond normal month-to-month variation, rising from 65.4% in July 2026 to 72.6% in October 2026, an increase of 7.2 points, with the largest single-month step coming in October 2026 when coverage rose 9.8 points from 62.8% in September 2026. Presence also rose from 96.6% in July 2026 to 98.6% in October 2026, and the top-three rate rose from 54.7% to 70.0% over the same period. The rank-one rate rose from 42.5% in July 2026 to 55.2% in October 2026. The gain was broad across the placement ladder, not confined to overall coverage.

Largest Decline: Universal Background Screening

Universal Background Screening showed the largest coverage decline across the four-month series, falling from 1.4% in July 2026 to 0.2% in October 2026, beyond normal variation. The decline was sustained rather than sharp: 1.4% in July 2026, 0.4% in August 2026, 0.2% in September 2026, and 0.2% in October 2026. Presence also receded from 2.2% in July 2026 to 0.4% in October 2026. The decline rests on a single valid recommendation and should not be over-read.

Category Leader: Checkr

Checkr held the leadership position in each month of the series, with valid recommendation coverage of 65.4% in July 2026, 60.9% in August 2026, 62.8% in September 2026, and 72.6% in October 2026. The gap to First Advantage widened from 30.6 points in July 2026 to 42.8 points in October 2026, the widest tracked gap of the series. The top-three rate rose from 54.7% in July 2026 to 70.0% in October 2026, and the rank-one rate rose from 42.5% to 55.2% over the same period.

Recommendation Placement Snapshot

Questions This Section Answers

• How do top-three and rank-one rates differ among Checkr, GoodHire, and HireRight?
• Why can similar recommendation coverage still hide very different first-position rates?

Coverage alone does not show how prominently a brand is recommended. The following table compares top-three and rank-one rates for the leading brands.

Similar coverage levels can still hide very different first-position rates. Checkr and GoodHire separated by 11.5 points in coverage in October 2026, while Checkr's rank-one rate of 55.2% was far higher than GoodHire's 10.3% rank-one rate.

Buyer-Intent Distribution

All qualified observations in both months fell into the Brand Recommendation class, where AI responses recommend specific background check providers.

The current public series cannot answer pricing or head-to-head comparison questions, because it contains no qualified observations in those classes.

Historical Measurement Record

Questions This Section Answers

• Has Checkr led the background checks category in every monthly measurement?
• Which single-month coverage movements stood out across the four-month series?

New measurements are added to the same report.

Checkr has held the coverage lead in every measurement, but not without losing ground in individual months.

Evidence and Source Layer

Questions This Section Answers

• What source and citation data is retained for each background check prompt observation?
• Does a brand's cited source presence prove it caused the AI recommendation?

The benchmark is built from prompt-level observations that retain the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment, not proof that the source caused the recommendation.

Scope Boundaries

This public benchmark does not measure:

• Market share or revenue attribution
• Attributable sales or conversions
• Every possible AI response
• Organic-search ranking positions
• Social media mention volume
• Private or sponsored channels
• Causality from a metric movement alone

No metric movement in this benchmark establishes causality on its own.

Top 10 Cited Domains

Questions This Section Answers

• Which domains were cited most often across AI platform responses in the background checks category?
• How concentrated were citations among the top 10 domains?
• Which background check brands' own domains appeared in the top cited list?

Across all AI platform responses in this measurement period, 6,154 citations were observed across 1,137 unique domains.

The ten most-cited domains account for roughly 29% of all citations despite representing a small fraction of the 1,137 unique domains observed. Two tracked brands' own domains appear in the top 10: checkr.com at rank one and goodhire.com at rank two, each cited across all six canonical AI/search surface families. The remainder of the list is dominated by third-party consumer finance and review destinations, including youtube.com, reddit.com, money.com, and nerdwallet.com, alongside general search and news sources.

About This Benchmark

The LLM Authority Index AI Visibility Market Discovery Index tracks how often and how prominently brands appear in AI-generated answers across major AI/search surfaces. Monthly measurements are benchmarked against a consistent question set to reveal changes in brand presence, recommendation coverage, and placement.

• AI Visibility Market Discovery Methodology
• AI Visibility Market Discovery Metric Definitions
• AI Visibility Market Discovery Research Standards
• Modeled AI Visibility Authority Value

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The public industry benchmark shows category-level standings. A company-level Authority Index can go deeper.

The public percentage cannot identify the prompts, competitors, or sources causing the result.

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