The State of B2B GEO: 2026 Benchmark Report

This is the first comprehensive benchmark of B2B GEO performance built on a same-methodology audit dataset: 200+ VISIBLD GEO audits run between Q4 2025 and Q1 2026, all measured against the same 50-prompt library across 8 LLMs and scored with the same 5-pillar rubric.

Headline numbers

Composite GEO Score distribution

The full population skews left. The mode sits in the 40–50 band, with a long tail of companies stranded below 30 — typically those with legacy CMS architecture, no Wikipedia entry, no claimed G2 profile, and no schema markup beyond what Wordpress shipped by default.

• A (80–100): 2.1% of companies. Almost all have Wikipedia entries, claimed G2 profiles with 200+ reviews, and tier-1 press in the last 12 months.
• B (65–79): 7.3%. Strong on retrieval-layer signals; partial gaps in parametric authority.
• C (50–64): 31.4%. Median segment. Owned-surface basics in place; off-site graph thin.
• D (35–49): 36.8%. Largest segment. Schema incomplete, FAQ sections missing, distribution near zero.
• F (0–34): 22.4%. Functionally invisible across all 8 LLMs.

Pillar-level performance

Pillar medians reveal where the work is — and isn't — getting done.

• Technical (median 58): Most companies have basic page speed and crawlability. Schema completeness is the gap — 61% are missing FAQPage schema entirely.
• Content (median 51): Answer-first architecture is rare. The median page leads with a hero headline (promotional), not an extractable capsule.
• Entity (median 39): Cross-platform name and description consistency fails for 67% of companies. Wikidata Q-IDs exist for only 28%.
• Distribution (median 32): The category killer. 73% score below 50. G2 review velocity, Reddit presence, and press recency are the most common gaps.
• Authority (median 49): Domain authority is the most stable signal — but on its own, insufficient.

Category medians

Categories with strong Wikipedia category pages, active Reddit communities, and mature G2 directories consistently score higher.

• Developer Tools — median 62 (B-). GitHub, Stack Overflow, and Hacker News presence drive Distribution scores up.
• CRM — median 58 (C+). Mature G2 category, sustained press, named competitors with strong entity signals.
• Marketing Automation — median 55 (C). Strong Tier 4 press but uneven Wikipedia presence below the top 10 vendors.
• Cybersecurity — median 51 (C-). Strong analyst coverage; thinner Reddit and community signals.
• Customer Support SaaS — median 48 (D+). Concentration of citations on top 5 vendors; long tail invisible.
• HR Tech — median 44 (D). Capterra-heavy; Wikipedia thin below market leaders.
• Vertical SaaS — median 41 (D). Niche category pages on Wikipedia rare; review platform fragmentation.
• Legal Tech — median 38 (F+). Conservative content tone correlates with low extractability.
• Church Management — median 34 (F). Closed community, weak press surface, near-zero Wikipedia coverage.

Sample sizes per category range from 8 to 34. Categories with n<8 omitted from medians.

GEO Score and pipeline correlation

A subset of 40 audited companies opted into 6-month follow-up reporting on AI-referred demo bookings, traced via UTM parameters and self-attribution surveys. The correlation is significant:

The relationship is not linear at the extremes. Below GEO 30, the gain per 10-point lift is steeper (citation goes from "never" to "sometimes"). Between GEO 60 and 80, the gain per 10-point lift compounds further as the brand crosses the threshold from "occasional citation" to "default recommendation."

What actually moves the score

Within the 40-company follow-up cohort, the highest-leverage interventions ranked by mean GEO Score lift in 90 days:

1. FAQPage schema deployment + answer-first homepage rewrite — mean +9.2 points.
2. Claimed and populated G2 + Capterra profiles with 25+ new reviews — mean +7.8 points.
3. Wikipedia entry creation or notable-source upgrade — mean +6.4 points (when achievable; ~30% of attempts succeed).
4. Wikidata Q-ID + sameAs cross-linking — mean +4.1 points.
5. 3+ "X vs Y" comparison pages on owned domain — mean +3.7 points.
6. Founder LinkedIn weekly posting cadence — mean +2.9 points over 90 days.

Lifts are non-additive — combining all six interventions does not equal the sum. Estimated combined ceiling: +22 points from a starting score under 50.

Methodology notes

• Sample: 200+ B2B SaaS companies audited Q4 2025 – Q1 2026, ranging $1M – $400M ARR.
• Prompt library: 50 prompts per audit, calibrated to category, ICP, and 5 named competitors. Prompts spanned definitional, comparative, shortlist, and validation buyer-journey stages.
• Platforms: ChatGPT, Perplexity, Claude, Gemini, Copilot, Grok, DeepSeek, Google AI Overviews.
• Pillar weights: Technical 20%, Content 25%, Entity 15%, Distribution 25%, Authority 15%.
• Outliers: top 5% and bottom 5% per category removed for medians.
• Pipeline correlation cohort: 40 companies opted into 6-month follow-up; AI-referred bookings self-attributed and UTM-tracked.

Frequently asked questions