Industry Report

Staffing & Agency Applicant Systems

ATS products built for staffing agencies and recruitment firms featuring rapid candidate placement workflows, bulk submittals, client portals, and billing integrations.

Brands tracked: 34
Brands analyzed: 34
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 269
Total responses: 1,365
Top Brand Overall?
Bullhorn
87/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Lever
80

Highest score on the LBA metric in this industry.

Authority Leader?
Bullhorn
98

Highest score on the Authority metric in this industry.

TOM Leader?
Bullhorn
100

Highest score on the TOM metric in this industry.

Bullhorn is the default answer in AI responses for Staffing & Agency Applicant Systems

When users ask ChatGPT, Claude, or Gemini about Staffing & Agency Applicant Systems, Bullhorn is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. JobAdder is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 34 Staffing & Agency Applicant Systems brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 269 shared Staffing & Agency Applicant Systems prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 269 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →