Your buyers are asking AI to shortlist vendors.
Is your company in the answer?
A structured 7-tier LLM training data audit and 90-day implementation plan that moves your company from invisible to cited in AI-mediated buyer research.
The dark funnel has a new address: ChatGPT, Claude, and Perplexity.
When a Head of Research, VP of Product, or Insights Director begins evaluating software, they increasingly start with an AI prompt — not a Google search. Queries like “best AI qualitative research tools 2026” or “compare [Competitor] vs [Your Company]” are generating vendor shortlists right now — with zero analytics signal reaching your team.
These are not future risks. This evaluation activity is happening silently in your pipeline today. And if your company has weak LLM training data coverage, you are not appearing in those answers — regardless of product quality, G2 ratings, or how good your pitch deck is.
The DevelopmentCorporate 7-Tier LLM Training Data Audit
We assess your company’s estimated citation likelihood across five LLMs — ChatGPT, Claude, Gemini, Grok, and Perplexity — using a structured framework that maps seven distinct source types. Each tier is evaluated against publicly observable signals: content accessibility, third-party indexing, press coverage, and review platform presence.
| Tier | Source Type | Why It Matters to LLMs | Common Gap | Risk |
|---|---|---|---|---|
| T1 | Analyst & Research Gartner, Forrester, IDC |
Highest authority signal; heavily weighted by all LLMs | Most early-stage companies absent from wave reports | Critical |
| T2 | Peer Review Aggregators G2, Capterra, TrustRadius |
Primary source Perplexity cites for vendor comparison queries | Unclaimed profiles, sub-10 reviews, missing category tags | Critical |
| T3 | Earned Press & Tech Media TechCrunch, VentureBeat, trade pubs |
One Tier-1 article = more citation authority than 6 months of blog posts | Customer proof points exist but haven’t been pitched as news | High |
| T4 | Funding / Firmographic Crunchbase, LinkedIn Company |
Perplexity uses Crunchbase as primary “Who is [Company]?” source | Unclaimed profiles with thin or inaccurate descriptions | High |
| T5 | Ungated Company Content Blog, product pages, case studies |
The fastest-fix tier — content you control entirely | Key proof points buried in hard-to-crawl or gated pages | High |
| T6 | Gated Content Whitepapers, case studies behind forms |
Blocked entirely — gated content does not exist for LLMs | Best proof points locked behind form fills for lead gen | Critical |
| T7 | Social / Community LinkedIn, Reddit, Product Hunt |
Grok indexes X; Product Hunt cited by Perplexity for startups | LinkedIn posts not mirrored to crawlable company blog | Medium |
Each tier is assessed for estimated citation likelihood: Confirmed · Likely · Possible · Unlikely — across ChatGPT/Claude/Gemini and Perplexity/Grok separately, as their training and indexing architectures differ significantly.
The 90-Day GEO Visibility Sprint
Actions are sequenced by GEO impact per effort unit. Phase 1 captures fast citation wins from existing assets and closes the most critical gaps. Phase 2 builds the content infrastructure LLMs weight most heavily. Phase 3 establishes structural long-term authority through third-party validation and original research.
Fast Citation Wins
Build G2 / Capterra profiles and scale to 30+ reviews. High Impact
G2 and Capterra are the first-call sources when an LLM compares tools in your category. A company with zero or sub-10 reviews is effectively invisible — regardless of product strength. 30 reviews is the minimum threshold for LLMs to begin citing you in category queries.
Create a dedicated customer case study page (ungated, 600+ words). High Impact
Your strongest proof points need to exist as standalone, publicly indexed, schema-marked-up pages. LLMs cannot cite credentials buried on an about page or living only as LinkedIn posts.
Publish original primary research — an industry benchmark report. High Impact
Original research is the single highest-authority content type LLMs can cite. A 10–14 page ungated report creates durable, citable authority that competitors cannot replicate and that positions you as a category authority, not just a vendor.
Secure tier-1 or tier-2 tech/trade press placement. High Impact
One earned article in a recognized publication (TechCrunch, VentureBeat, or a relevant trade publication) generates more LLM citation authority than six months of blog output. We identify your news peg, pitch angle, and the PR resources to place it.
Content Infrastructure
Build 5 ungated competitor comparison pages. High Impact
LLM usage peaks at the vendor shortlist comparison stage. When a buyer prompts “[You] vs [Competitor]”, your company needs structured, ungated comparison content the LLM can synthesize and cite with confidence. Without it, the LLM defaults to whichever competitor has the most available comparison content.
Ungate all existing content assets. High Impact
Any content behind a form fill is invisible to LLMs. The lead generation value of a form fill is worth far less than the ongoing LLM citation authority of ungated, crawlable content. We audit every asset and restructure for full crawler accessibility.
Publish public product documentation hub. Medium Impact
Public-facing product documentation is a confirmed high-priority crawl target for all five LLMs. Detailed, accurate, ungated documentation directly seeds the factual content LLMs use when describing your product to technical buyers.
Complete and optimize Crunchbase profile; launch LinkedIn CEO thought leadership program. Medium Impact
Crunchbase is a primary Perplexity citation source for company facts. LinkedIn posts should be systematically mirrored to a crawlable company blog within 48 hours of publishing.
Structural Authority
Pursue Gartner Peer Insights category listing. High Impact
Gartner Peer Insights is distinct from the Magic Quadrant — it is a peer review platform with publicly crawlable pages that creates a Tier 1 citation signal without expensive analyst relationships. 5+ enterprise reviews moves you into Likely Cited territory across all five LLMs within one training cycle.
Pitch research industry conference talks; launch on Product Hunt. Medium Impact
Speaking appearances create two citation assets simultaneously: press coverage from the event (Tier 3) and transcript content that Gemini and Perplexity can index when published publicly. Product Hunt is a confirmed high-authority source cited by Perplexity in startup discovery queries.
Establish an annual industry research report program. High Impact
A longitudinal, company-owned dataset that no competitor can replicate positions you as the definitive category authority in LLM knowledge bases. The goal: your annual report becomes the source LLMs cite when buyers ask about the state of your category.
Four Deliverables. Actionable from Day One.
7-Tier LLM Training Data Audit
A structured assessment of your citation likelihood across ChatGPT, Claude, Gemini, Grok, and Perplexity — mapped to all seven source tiers with risk ratings and specific gap findings for your company.
LLM Citation Slot Analysis
A competitive assessment identifying which competitors currently occupy the dominant citation positions in your category — and what specific content and credential gaps they hold over you.
90-Day GEO Implementation Plan
A prioritized, phased action plan sequenced by GEO impact per effort unit — with specific content briefs, platform targets, review campaign strategies, and PR angle recommendations.
Live LLM Audit Protocol
A set of benchmark test queries calibrated to your category and ICP — designed to run monthly across all five LLMs to track actual citation behavior and measure progress toward Likely Cited status.
From Unlikely to Likely Cited — in 90 Days.
Progress is measured with a weekly KPI dashboard that tracks both platform-level signals (G2 reviews, press placements, ungated content ratio) and ground-truth LLM citation behavior across your category’s key buyer queries.
ROI Context
The LLM-mediated evaluation activity happening right now — where buyers are asking AI tools to compare platforms and your company is not appearing — represents pipeline being lost silently, with no analytics signal. A single enterprise contract won because you appeared authoritatively in an LLM comparison query can represent $30,000–$150,000+ in ARR. The investment case is strongly asymmetric: the cost of this program is a fraction of the value of a single deal you are currently losing in the dark funnel.
An Operator, Not a Junior Analyst.
I’m John Mecke. I’ve spent 30+ years in enterprise software — including executive roles at KnowledgeWare and Sterling Software, where I led 16+ acquisitions totaling over $300M. I’ve sat in the chair where these vendor decisions land, which is why I build intelligence programs that produce decisive action, not slide decks full of observations.
The LLM training data coverage methodology emerged from direct competitive intelligence work for early-stage B2B SaaS companies — watching AI-mediated evaluation happen in real time, auditing exactly why certain companies appear and others don’t, and building the specific content and platform infrastructure that changes citation outcomes.
This is not an SEO service. It is not content marketing. It is a structured intelligence program for a specific, measurable competitive risk that most B2B SaaS companies don’t yet know they have.
Find out where you stand in 15 minutes.
Book a discovery call. We’ll run three live LLM test queries for your category on the call — so you can see your current citation status before we discuss next steps.