# rawmktg

> rawmktg is a blog covering B2B marketing strategy, SEO, GEO (Generative Engine Optimization), AI search visibility, and content marketing for SaaS companies.

## Published Posts

- [When Buyers Ask AI Which AEC Software to Use, Most Vendors Aren't in the Room](https://rawmktg.com/blogs/aec-ai-visibility-gap) - June 2026. Data analysis of LLM citation visibility across six AEC technology companies (Revizto, Alice Technologies, Solibri, Endra.ai, Augmenta, Vavetek) using Ahrefs data, June 2026. Six platforms tracked: Google AI Overviews, ChatGPT, Gemini, Perplexity, Microsoft Copilot, and Grok. Total citations: 375. Key findings: 4 of 6 companies have fewer than 2 total citations; Revizto leads with 310; AI Overviews and Grok account for 77% of all citations; zero companies have published llms.txt; high domain rating and organic traffic do not predict AI citation visibility. Includes platform-by-platform behavior analysis, shared factors among visible companies, and a prioritized vendor action plan (llms.txt, JSON-LD schema, trade media, X community presence, FAQ content, analyst coverage).
- [How We Run a GEO Foundation Audit](https://rawmktg.com/blogs/geo-foundation-audit) - June 2026. A repeatable five-step diagnostic for mapping brand visibility across AI engines: (1) Query Mapping with 40-50 buyer-intent prompts; (2) Multi-Model Execution across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overviews; (3) Citation Gap Scoring using Share of Voice and the Mention-Source Divide; (4) Technical Crawlability audit covering AI crawler access, client-side rendering, Core Web Vitals, and llms.txt; (5) Content Restructuring using atomic knowledge blocks and Princeton-validated operators (Statistics Addition, Quotation, Source Citation). AI-referred traffic converts at 11x organic (1.66% vs 0.15%). Only 11% of domains are cited by both ChatGPT and Perplexity. Gini coefficients: ChatGPT 0.164, Perplexity 0.244, Claude 0.288, Gemini 0.351. Fast pages (FCP <0.4s) average 6.7 citations/query vs. 2.1 for slow. Analysis of 17.2M citations across six verticals included.
- [The Topical Authority Cluster That Gets B2B Brands Into AI Shortlists](https://rawmktg.com/blogs/topical-authority-cluster-ai-shortlists) - June 2026. How generative engines weigh topical depth against breadth, and the exact hybrid cluster architecture that earns a place on LLM recommendation lists. Covers the RAG pipeline mechanics (query understanding, vector retrieval, candidate scoring, synthesis), the Princeton GEO-bench findings (+41% from statistics, +41% from expert quotes, +40% from source citations), the five citability pillars (machine-readable infrastructure, citation-first structure, named-entity density, off-site trust footprint, content freshness), an eight-question citability audit grouped by entity/citation/contextual gap type, hybrid cluster architecture with per-engine distribution tactics, llms.txt and Markdown mirror page implementation, and Share of Model (SoM) measurement via prompt-based auditing and GA4 AI-referral segmentation.
- [Why ChatGPT, Perplexity and Gemini Recommend Different Vendors (and How to Win All Three)](https://rawmktg.com/blogs/why-engines-recommend-different-vendors) - May 2026. 69% of B2B buyer journeys touch three or more AI engines, but each engine uses different ranking architecture. ChatGPT (via Bing) filters to the top 15% of indexed content by domain authority, freshness, and engagement signals; Perplexity uses real-time RAG with a five-factor scoring model (Relevance, Authority, Freshness, Corroboration, Engagement); Gemini resolves entities through Knowledge Graph before retrieving any content. Includes a prioritisation matrix mapping 12 GEO tactics across all three engines, a 60-day implementation roadmap, and a forward-looking section on agentic commerce and tool-call citation patterns.
- [Hallucination-Proofing Your Brand: The Content Architecture That Stops AI Getting You Wrong](https://rawmktg.com/blogs/hallucination-proofing-your-brand) - May 2026. The specific markup, FAQ architecture, and claim-anchoring techniques that measurably reduce AI hallucinations about your brand. Covers the Princeton GEO study findings (+41% from statistics, +40% from source citation), Schema.org @graph architecture, /llms.txt implementation, and the four-component Claim-Anchoring Framework: Answer Capsule (40-60 words), Section Autonomy (120-180 word chunks), Proof-Pairing Density Ratio (0.70 target), and Unambiguous Brand Association. Includes before-and-after content reconstruction case study and GEO monitoring platform comparison.
- [Prompt-to-Citation Tracking: How to Build a GEO Measurement Stack From Zero](https://rawmktg.com/blogs/prompt-to-citation-tracking) - May 2026. AI-sourced sessions convert at 4.4x organic, yet GA4 under-counts AI referrers by ~30% and misclassifies them into Direct/Referral buckets. A step-by-step blueprint for the complete GEO measurement stack: designing a 50-150 prompt portfolio across Money/Problem/Proof buckets, building a dual GA4 setup with custom AI Search regex, constructing the blended Looker Studio dashboard (GSC + GA4 + prompt sheet), and calculating Revenue per Citation: the metric that proves GEO ROI to the C-suite.
- [Anatomy of a High-Citation Page: Reverse-Engineering What Gets Pulled Into AI Answers](https://rawmktg.com/blogs/anatomy-of-a-high-citation-page) - May 2026. 38% of top-10 organic URLs are also AI-cited. 55% of citations come from the first 30% of a page. A deconstruction of 10 pages that consistently earn AI citations across ChatGPT, Gemini, and Perplexity: shared patterns in heading structure, paragraph density, source-linking, and answer-lead formatting.
- [Authority Seeding for AI: Building the Off-Site Signal Stack That LLMs Actually Trust](https://rawmktg.com/blogs/authority-seeding-ai-llm-trust) - May 2026. Unlinked brand mentions correlate 3x more strongly with AI citation visibility than traditional backlinks (r=0.664 vs r=0.218). A tactical playbook covering the five-gate citation gauntlet, platform-specific citation profiles for ChatGPT, Claude, Perplexity, and Google AI Overviews, vertical seeding playbooks, and a five-phase execution blueprint for building the off-site signal stack that LLMs actually trust.
- [OAI-SearchBot vs. PerplexityBot vs. Common Crawl: How AI Crawlers Actually Index Your Site](https://rawmktg.com/blogs/how-ai-crawlers-index-your-site) - May 2026. None of the three AI crawlers execute JavaScript. A technical breakdown of crawl frequency, scope, JavaScript handling, and IP verification for OAI-SearchBot, PerplexityBot, and CCBot, plus the unified robots.txt configuration that maximises citation share without leaking content to training corpora.
- [The GEO Compounding Flywheel: How to Build AI Visibility That Gets Harder to Dislodge](https://rawmktg.com/blogs/geo-compounding-flywheel) - May 2026. 73% of B2B procurement managers use ChatGPT, Claude, or Perplexity for vendor discovery. A seven-step loop (Build, Crawl, Train/Retrieve, Rate, Recommend, Validate, Re-signal) that decides who gets cited across AI platforms, the Princeton/Georgia Tech GEO research behind it, the Share of Citation metric, three B2B case studies, and a 90-day implementation blueprint.
- [Schema Markup in 2026: The Structured-Data Playbook Every B2B Brand Needs for AI Citations](https://rawmktg.com/blogs/schema-markup-ai-citations-2026) - May 2026. 53% of AI-cited pages carry valid schema markup, making cited pages nearly 3x more likely to have JSON-LD than non-cited pages. A technical breakdown of single-script @graph architecture, FAQPage, Article, SoftwareApplication, and HowTo schema types, plus a six-week implementation roadmap covering entity foundation, conversational content layer, and product and documentation schema.
- [E-E-A-T Is an AI Signal Now: How Google's Quality Framework Got Baked Into LLM Preferences](https://rawmktg.com/blogs/eeat-is-an-ai-signal-now) - May 2026. 96% of AI Overview citations go to sources Google already trusts for E-E-A-T. A technical breakdown of how RLHF, DPO, and representation engineering wired E-E-A-T into LLM preferences, the GEO Holy Trinity research findings (Quotations +41%, Statistics +31%, Cite Sources +30%), and a 90-day framework for B2B marketers to build AI citation authority.
- [The 30-Day Content Half-Life: Why Recency Is Now a Hard Ranking Signal for AI Answers](https://rawmktg.com/blogs/30-day-content-half-life-recency-ai-ranking-signal) - May 2026. Pages not updated in 90 days are 3.2x more likely to lose AI citations entirely. A technical breakdown of recency as a hard signal across ChatGPT, Perplexity, Claude, and Google AI Overviews, plus a programmatic refresh-cadence system and 90-day rollout plan.
- [India's Senior Living Sector Has an AI Problem Nobody Is Talking About](https://rawmktg.com/blogs/india-senior-living-ai-visibility-gap) - May 2026. A data-driven SEO and GEO gap analysis across Primus Senior Living, Antara Senior Care, and Ashiana Housing. The ChatGPT citation gap is 39x, the traffic gap is 7.8x, and one brand is being misclassified by AI at the moment of highest buyer intent.
- [How RAG Actually Works, And Why It's the Only GEO Lever That Moves This Quarter](https://rawmktg.com/blogs/how-rag-actually-works) - May 2026. A technical breakdown of Retrieval-Augmented Generation for B2B marketing leaders: the five-stage AI search pipeline, Princeton/Georgia Tech GEO research findings, platform-by-platform citation behaviour, and a three-phase action plan.
- [The Autonomous Retail Industry Has a Visibility Problem Nobody Is Talking About](https://rawmktg.com/blogs/autonomous-retail-ai-visibility-gap) - May 2026. How a $74 billion market is being shaped not by the best technology, but by whoever shows up first in Google and ChatGPT. Data on five autonomous retail companies including Neuroshop, AiFi, Standard AI, GetZippin, and Digit7.
- [We Analysed the SEO of 6 Leading CX SaaS Companies. The Patterns Were Identical.](https://rawmktg.com/blogs/cx-saas-seo-discoverability-analysis) - April 2026. Six findings on organic traffic gaps, technical SEO debt, content funnel inversions, backlink quality, and AI visibility across six leading B2B CX SaaS companies.
- [We Analysed 6 B2B SaaS Companies in the Container Tracking Software Space. Here Is What We Found.](https://rawmktg.com/blogs/container-tracking-saas-seo-geo-analysis) - April 2026. Seven findings on AI citation gaps, domain authority, commercial keyword coverage, carrier tracking page strategy, and referring domain quality across six container tracking SaaS companies.

## About

**Publisher:** rawmktg.
**Author:** rawmktg.
**Contact:** vinayak@rawmktg.com
**Focus:** B2B SaaS marketing, GEO, SEO, AI search, content strategy