AI search optimization for B2B SaaS

When your buyers ask AI for the best B2B SaaS, does your name come up?

Clear Cited measures exactly where ChatGPT, Perplexity, Claude, Gemini, and Google AI 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

Why B2B SaaS win or lose in AI search first

Your buyers now ask AI engines for the best analytics platforms; share-of-model decides whether you make the AI-generated shortlist.

B2B SaaS founders, growth leaders and marketing leaders are exactly who we built this for. Buyers now ask AI before they shortlist, and AI visibility is engine-specific — you can't optimize once. We measure where ChatGPT, Perplexity, Claude, Gemini, and Google AI 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

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.

1. Money prompts

We build the exact questions your buyers ask AI — prompts like "best analytics platforms for a small team", "best CRM software in 2026", "analytics platforms alternatives", "is there a cheaper alternative to the incumbent?" — from your category language and sales calls.

2. Measure every engine

Each prompt runs 10+ times across ChatGPT, Perplexity, Claude, Gemini, Copilot, and Google AI Overviews — 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, human-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 measurement5 engines (ChatGPT · Perplexity · Gemini · Claude · Google AI)Answer-first content & schemaEngine-by-engine fixesMonthly re-measurement

SEO foundation

The ground AEO stands on

Included

Technical SEOSERP / keywordBacklinks & domain authorityCore Web VitalsInternal linkingSchema / structured data

Done-for-you content

We write & publish — not just brief

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

LinkedInXRedditYouTubeDev.toHashnode+9 more

On your domain

Answer-first articlesComparison & benchmark pagesVideo + VideoObject schema

Off-site authority

Listing & review sites the models cite

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

G2CapterraCrunchbaseProduct Hunt+ dozens more

Digital PR — earned coverage (best-effort)

Expert commentaryReporter-query responsesData-led story pitches

AI-speed, human-approved — every asset is researched, drafted, and a human approves it before it ships.

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 $2,000, Comprehensive $3,500) and done-for-you retainers (Growth $1,500/mo, Scale $3,500/mo, Authority $6,500/mo), plus à‑la‑carte add-ons (blog posts, a social content pack, video, directory listings, and digital PR) from $300. 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 — prompts like "best analytics platforms for a small team", "best CRM software in 2026", "analytics platforms alternatives", "is there a cheaper alternative to the incumbent?" — 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).

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, Microsoft Copilot, and Google AI Overviews / AI Mode — 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.