AI Search Optimization (AEO/GEO) for B2B SaaS

When your buyers ask AI for the best software in your category, does your name come up?

I'm Logan — I run Clear Cited myself, and B2B SaaS teams are exactly who I built the measurement for.

Clear Cited measures exactly where the 5 AI engines — ChatGPT, Perplexity, Claude, Gemini, and Grok — plus Google's AI surfaces (AI Overviews & AI Mode), measured separately — recommend your competitors and not you — with reproducible data, not screenshots — then fixes it. The full-stack engine behind it: SEO foundation, content, and authority — measured by share-of-model. Built for B2B SaaS founders, growth leaders and marketing leaders.

Get a free teardown for your B2B SaaS company See the measured CRM leaderboard

Why Clear Cited

The five levers behind share of model

We get you recommended across the 5 AI engines — ChatGPT, Perplexity, Claude, Gemini, and Grok — plus Google's AI surfaces (AI Overviews & AI Mode), measured separately — and here is the honest system beneath it: what you are actually paying for, and the real limit on each.

Every engine and surface your buyers actually use

the AI engines your buyers use, plus Google's AI surfaces and Bing's Copilot answers — each measured separately, never summed into one score

The roster is five AI engines plus two answer surfaces — AI Overviews and Microsoft Copilot — reported separately and never summed into an engine count. The five engines are measured today. Both surfaces are positioned, not measured: an engine is one foundation-model family we query directly, a surface is a product that renders an answer, and a surface never becomes an engine by being added up. Outside the labelled separate-surface panel we name the Google surface plainly as AI Overviews, because naming it beside the engines would read as an engine claim.

A method you can reproduce

pre-registered prompt sets with published hashes, run counts and a confidence interval on every figure, and null results published on the same terms as positive ones - as standing practice, not a one-off study

Confidence intervals are reported honestly wide and named per product: presence uses a Wilson interval in both products; share-of-model uses a percentile bootstrap in the paid audit and a Wilson interval in the public Index, whose pooled denominator is clustered - so those Index intervals are narrower than a cluster-corrected estimate would give, and we say so. We never narrow a CI to look more certain than the data is.

All four tiers AI cites from

we work all four tiers AI cites from — not just the fraction of your presence you directly own

This is SCOPE — the tiers we work, not an outcome we promise. The per-tier percentages are illustrative (Yext-sourced) and the earned tier (news & forums) is best-effort, never guaranteed.

Almost none of your time

your time required is almost none — sign-off graduates to become yours by default once we've earned a track record, with continued sampling

A human approves every client deliverable until a clean track record is earned; graduation is opt-in, default-off, and reversible — client-facing and published content never reaches unattended auto (AI speed, human-approved).

A system that compounds

the system learns which of your pages get cited and compounds that signal every cycle

Honest-empty until measured — attribution shows the real citations a piece earns, with the engine, prompt and date, only once they are actually earned; no projected compounding curve.

The system compounds — see how it learns which of your pages get cited → · the four tiers of citations we work →

Why B2B SaaS brands win or lose in AI search first

Your buyers now ask AI engines for the best tool in your category; share-of-model decides whether you make the AI-generated shortlist.

Your category already has an AI shortlist — and it isn't your G2 grid or an analyst quadrant. In our measured CRM leaderboard (2026-07-01), Salesforce — the market-share incumbent — ranks third by share-of-model at 14.9%, behind HubSpot (22.3%) and Pipedrive (18.2%). Market position doesn't transfer to AI answers automatically, and AI visibility is engine-specific — you can't optimize once. We measure where ChatGPT, Perplexity, Claude, Gemini, and Grok recommend you (and don't), reproducibly, then fix it.

The categories we cover for B2B SaaS

If your product competes in any of these, your buyers are already asking AI to rank it:

analytics platformsCRM softwareproject managementcustomer support & helpdeskmarketing automationdata & ETL platformssecurity & compliance SaaSHR & payroll SaaS

And here's one of them, measured — who AI actually names in product analytics, by share of model across all five engines:

For B2B-SaaS categories like product analytics, here's who AI actually recommends — measured share-of-model across all five engines, not a screenshot.

AI Visibility Index — Product analytics platforms · share-of-modelmeasured snapshot · 2026-07-01
#ProductShare of modelShare95% CI
1Mixpanel23.2%21.4–25.1
2PostHog21.5%19.8–23.4
3Amplitude20.6%18.9–22.4
4Heap13.3%11.9–14.9
5Pendo8.9%7.7–10.2
6Google Analytics5.9%4.9–7.0
Engines
5 of 5
Prompts
10
Answers
500
Runs/engine
10
Interval
Wilson score interval, 95% (z=1.96)

One of nine DevOps + B2B-SaaS categories in our AI Visibility Index. Point-in-time; engines change. · Methodology →

Your category, measured — and a plan to win it

We publish a live AI Visibility Index leaderboard for the B2B-SaaS categories we work, and a hire-us page for each that shows your category’s measured reality next to a plan. Start with yours:

CRM software →

Who AI actually names in CRM, by share-of-model, and how we get you into the answer. See the live leaderboard.

Product analytics →

The measured product-analytics shortlist and a plan to climb it. See the live leaderboard.

What the measured B2B-SaaS leaderboards actually show

We measure B2B-SaaS categories the same way we measure everything (10 buyer prompts × 10 runs × 5 engines, snapshot 2026-07-01). Four findings that change where you'd spend a marketing dollar:

The incumbent isn't the answer

In CRM software, Salesforce ranks third by share-of-model — 14.9% (95% CI 13.5–16.5) vs Pipedrive's 18.2% (16.6–19.8) and HubSpot's 22.3% (measured 2026-07-01; those intervals don't overlap). Market share doesn't buy the AI shortlist — and challengers can take it.

The top of your category may be a tie

In product analytics, Mixpanel (23.2%), PostHog (21.5%) and Amplitude (20.6%) sit within 2.6 points of each other with overlapping 95% confidence intervals (measured 2026-07-01) — a statistical tie at the top. Ties are winnable; that's where AEO effort pays fastest.

Engines split on the same brand

Gemini names Google Analytics in 51% of product-analytics answers; ChatGPT names it in 1% (measured 2026-07-01, n=100 per engine). One brand, two realities — which is why every fix we ship is engine-by-engine, and why a single "we asked ChatGPT" screenshot audit misleads.

The battle is off your site

In our CRM measurement, 95.5% of the sources engines cited were third-party — comparison posts, review sites, communities — not the vendors' own domains (measured 2026-07-01). Your blog alone can't win this; the off-site authority work below is the point.

All figures from our AI Visibility Index, measured 2026-07-01 (10 runs per prompt per engine, 95% confidence intervals; point-in-time — engines change). Methodology →

How AI visibility works for B2B SaaS

In one line: we find the buyer prompts that decide your category, measure who each AI engine recommends for them, and get you into those answers — mostly via the third-party sources (reviews, comparisons, communities) that ~95% of AI citations come from. The differentiator: we measure share-of-model rigorously, fix the SEO foundation with real data, and produce the content + authority end-to-end — then prove it.

1. Money prompts

We build the exact questions your buyers ask AI. Real prompts from our pre-registered Index sets: "HubSpot vs Salesforce for a growing B2B SaaS company?", "Best CRM for a founder-led sales motion at a startup?", "Amplitude vs Mixpanel for a B2B SaaS product team?" — yours come from your category language and sales calls.

2. Measure every engine

Each prompt runs 10+ times across ChatGPT, Perplexity, Claude, Gemini, and Grok — median + 95% confidence interval, because a single answer is noise.

3. Your share of model

How often each engine recommends you vs. named competitors, plus the exact prompts where they win and you're invisible — and the sources the AI pulled from.

4. Fix, build & monitor

Done-for-you: we fix the SEO foundation, produce the content, and earn the off-site authority on a prioritized roadmap — AI-speed, you-approved, with every asset tuned to what actually performs in your niche (researched across YouTube, Reddit, Dev.to, Hashnode, Medium, Stack Exchange, and search) — then track weekly so your share of model climbs and stays. The full-stack service →

What's included

The outcome is share of model. Here's the engine beneath it.

AI-answer optimization

The wedge — we get you named and cited in AI answers

Our wedge
Share-of-model measurement 5 engines (ChatGPT · Perplexity · Gemini · Claude · Grok) Answer-first content & schema Engine-by-engine fixes Monthly re-measurement

SEO foundation

The ground AEO stands on

Included

Technical SEO SERP / keyword Backlinks & domain authority Core Web Vitals Internal linking Schema / structured data

Done-for-you content

We write & publish — not just brief

Published across 30+ channels — your accounts, tuned per platform

LinkedIn X Reddit YouTube Dev.to Hashnode +9 more

On your domain

Answer-first articles Comparison & benchmark pages Video + VideoObject schema

Off-site authority

Listing & review sites the models cite

Curated entity work — Boost 30+ · Growth 60+ · Authority 100+

G2 Capterra Crunchbase Product Hunt + dozens more

Digital PR — earned coverage (best-effort)

Expert commentary Reporter-query responses Data-led story pitches
AI-speed, you-approved — every asset is researched and drafted fast, and you review and approve it before it publishes.

Who this is for

B2B SaaS founders, growth leaders and marketing leaders — specifically the people who own the pipeline number:

Founder/CEOHead of MarketingHead of GrowthContent/SEO LeadProduct Marketing Manager

We don't just measure — we run the whole stack for you across a clear ladder: one-time audits (Starter $500, Full $2,500, Comprehensive $4,500) and done-for-you retainers (Growth $2,950/mo, Scale $6,500/mo, Authority $12,000/mo), plus à‑la‑carte add-ons (answer-first blog posts, a social content pack of 12 posts/mo, the separate Video pack, directory listings, and digital PR) from $400. Every asset is tuned to what actually performs in your niche — researched across YouTube, Reddit, Dev.to, Hashnode, Medium, Stack Exchange, and search — not guesswork. See pricing, add-ons & packages →

See where you stand across the AI engines — free.

Get your free teardown How the audit works

FAQ

Why does AI search visibility matter for B2B SaaS?

Your buyers now ask AI engines for the best analytics platforms; share-of-model decides whether you make the AI-generated shortlist. Buyers in B2B SaaS increasingly open ChatGPT, Perplexity or Claude and ask for the best option in a category before they ever visit a vendor site — so the engine's shortlist becomes your shortlist.

Which buyer prompts do you measure for B2B SaaS?

We build your “money prompt” set from how your buyers actually ask — real examples from our pre-registered Index prompt sets: "HubSpot vs Salesforce for a growing B2B SaaS company?", "Best CRM for a founder-led sales motion at a startup?", "Amplitude vs Mixpanel for a B2B SaaS product team?", "Most cost-effective product analytics platform for a seed-stage SaaS?" — across the categories you compete in (analytics platforms, CRM software, project management, customer support & helpdesk, marketing automation, data & ETL platforms, security & compliance SaaS, and HR & payroll SaaS).

Does market position carry over into AI answers?

Not automatically — we've measured it. In our CRM leaderboard (2026-07-01), Salesforce ranks third by share-of-model at 14.9%, behind HubSpot (22.3%) and Pipedrive (18.2%); in product analytics, the top three sit within 2.6 points with overlapping confidence intervals. AI shortlists are their own competition, and they're winnable.

Who is this for?

B2B SaaS founders, growth leaders and marketing leaders. We report to the people who own the number: Founder/CEO, Head of Marketing, Head of Growth, Content/SEO Lead, and Product Marketing Manager.

Which AI engines do you cover?

ChatGPT, Perplexity, Claude, Gemini, and Grok — each recommends a different set of tools, so we measure and fix per engine, not once.

Do you guarantee we'll get cited?

No honest provider can — AI engines change constantly. We guarantee reproducible measurement (each prompt run 10+ times per engine, median with a 95% confidence interval) and evidence-based work tied to a share-of-model target.

Most AEO optimizes only the slice of citations you own. Here's the whole map — all four tiers AI cites from, and how much of it we actually work.

Clear Cited works all four tiers

Coverage 100% · Control ~86% · Influence ~94% · Earned (best-effort)

Most AEO optimizes the ~44% you own. Clear Cited works all four tiers.

Control ~86% · influence ~94% · the last ~6% earned — worked, not guaranteed.

Source: Yext (6.8M citations), 2025-10 — a third-party citation-tier mix, not measured by our AI Visibility Index (which tracks share-of-model); illustrative of the tier split until we publish our own measured citation-source mix

Coverage is the scope of what we work — never a control or ranking guarantee. · See the full Citation Control Map →

See the monthly reporting

What the ongoing analytics reporting looks like for a B2B SaaS client.

The monthly analytics walkthrough. (1:12) · captioned film — no audio by design · illustrative data, labelled in-film

The transparency wedge

A method you can reproduce

pre-registered prompt sets with published hashes, run counts and a confidence interval on every figure, and null results published on the same terms as positive ones - as standing practice, not a one-off study

at least 10 runs per engine (12 by default), spent adaptively — more on high-variance engines, fewer on stable ones, never below a 5-run floor Every presence figure carries a Wilson 95% confidence interval. Share of model carries a percentile bootstrap 95% confidence interval in the paid audit, and a Wilson 95% confidence interval in the public AI Visibility Index — the method matched to the metric and named per product, both computed from the actual runs.

Confidence intervals are reported honestly wide and named per product: presence uses a Wilson interval in both products; share-of-model uses a percentile bootstrap in the paid audit and a Wilson interval in the public Index, whose pooled denominator is clustered - so those Index intervals are narrower than a cluster-corrected estimate would give, and we say so. We never narrow a CI to look more certain than the data is.

We publish our run counts, our uncertainty and our pre-registered prompt sets. Across the 8 providers we checked on 2026-08-02: run counts 4 of 8 verified; 4 not verified; uncertainty on published figures 2 of 8 verified; 6 not verified; the prompt set published with the results 0 of 8 verified; 8 not verified. The full comparison, with each vendor’s own wording →

That is the wedge: a number you can re-run and get back. See the full method →

Hold us to it, and hold the others to it too — the 12 questions to ask anyone selling AI visibility, each one answered here with a link.