Industry Report

Subject-Specific Tutoring Services

Providers specializing in tutoring for particular subjects such as math, science, languages, or coding with targeted curricula and instructors.

Brands tracked: 40
Brands analyzed: 40
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 305
Total responses: 1,575
Top Brand Overall?
Wyzant
86/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Khan Academy
95

Highest score on the LBA metric.

Authority Leader?
Wyzant
77

Highest score on the Authority metric.

TOM Leader?
Wyzant
100

Highest score on the TOM metric.

Wyzant is the default answer in AI responses for Subject-Specific Tutoring Services

When users ask ChatGPT, Claude, or Gemini about Subject-Specific Tutoring Services, Wyzant is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Varsity Tutors 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 40 Subject-Specific Tutoring Services brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). 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 305 shared Subject-Specific Tutoring Services 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 305 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 →