Measurement and AI reporting
- Google Search Console vs. Bing AI Reports: What They Measure - Understand the different evidence Google and Bing expose, what their metrics can support, and what neither platform can prove about AI visibility.
- How to Measure Whether AI Engines Are Actually Citing Your Content - How to track AI citation without confusing mentions, citations, impressions and share of voice.
ICP-driven content strategy
- ICP-Driven Content Gap Analysis: A B2B SaaS Framework - A framework for scoring content gaps against your ICP instead of keyword volume alone.
- How to Run an ICP-Driven Content Gap Analysis (Step-by-Step) - A step-by-step workflow for running an ICP-driven content gap analysis, from validating the ICP to scoring and prioritizing gaps.
- Mapping Content Gaps to the B2B Buying Committee and Funnel - How to tag content gaps by buying-committee role and buying job rather than a linear funnel.
- ICP-Driven vs. Traditional Keyword Gap Analysis - How ICP-driven gap analysis differs from traditional keyword-first gap analysis, and which tools do which job.
- Measuring Content-Market Fit: Pipeline Metrics for ICP-Driven Content - How to measure whether ICP-driven content is reaching pipeline, beyond traffic metrics.
Reverse-funnel marketing
- Reverse Funnel Marketing for B2B SaaS - A method for tracing closed-won deals backward to the accounts, campaigns and content associated with them.
- Is That a Pattern or an Artefact? Reading a Backward Trace Honestly - The mechanisms that can produce or exaggerate a striking pattern in a closed-won analysis, and how to tell a finding from an artefact.
- What Your Lifecycle Stages and Attribution Fields Actually Record - An audit of what your lifecycle-stage and attribution fields actually record before a backward trace can mean anything.
- Where to Start a Backward Analysis: Closed-Won, SQL, MQL or Lead - Which rung to start a backward analysis on, and what each starting point lets you claim.
- How to Trace a Closed-Won Cohort Backward - With the Comparison Group - How to trace a closed-won cohort backward, including the comparison group of closed-lost deals.
- Working From SQLs or MQLs When Closed-Won Deals Are Too Few - What working from SQLs or MQLs costs you when closed-won deals are too few to analyze directly.
- Turning a Pipeline Pattern Into a Test You Can Actually Read - How to turn a backward-analysis pattern into a prospective test, including when randomisation supports a causal claim.
- Scaling What Worked Without Destroying the Evidence That It Did - What to preserve when scaling a working pattern so the original finding stays evaluable.
AI crawler access and JavaScript
- How AI Crawlers Access JS-Heavy SaaS Sites - What GPTBot, ClaudeBot and PerplexityBot can and can't render on JS-heavy SaaS sites, and how to fix it.
- GPTBot vs. ClaudeBot vs. PerplexityBot: How Each Crawls JS Sites - A side-by-side comparison of GPTBot, ClaudeBot and PerplexityBot's crawling behavior, request volume and JavaScript handling.
- How to Test If AI Bots Can Read Your JS Content - A log-based method for checking whether AI bots can actually read your JS-heavy site.
- SSR vs. Prerendering for AI Crawler Access: A Decision Guide - A decision framework for choosing server-side rendering, static generation or prerendering middleware to fix AI crawler access.
- Does llms.txt Actually Do Anything? The Honest Verdict - What real usage data shows about whether llms.txt actually affects AI crawler behavior.
- Major AI Crawlers and User-Triggered Fetchers: A Verified Reference - A verified reference of provider-documented user-agent strings, purposes and robots.txt behavior for AI crawlers.
- Why React & Vue SaaS Sites Go Invisible to AI Crawlers: Hydration Explained - A framework-by-framework breakdown of where React, Vue, Next.js and Nuxt sites go invisible to AI crawlers.
- The AI-Crawlable SaaS Implementation Checklist - A sequenced, pass/fail checklist for fixing AI crawler access on a JS-heavy SaaS site.
- AI Crawl Budget vs. SEO Crawl Budget: What the Data Actually Shows - What published studies show - and disagree on - about AI-crawler error rates, and why checking your own logs matters.
- Will Agentic AI Browsers Replace Crawling? - Whether agentic AI browsers change the crawling and discovery picture for JS-heavy sites.
SaaS documentation and agents
- SaaS Documentation for AI Agents: The Boundary Between Reading, Tools, and Actions - Why agent-ready documentation is two separate problems - making content readable and exposing callable actions - and what MCP and OpenAPI actually establish.
AEO and citation mechanics
- AEO Fundamentals: How to Get Cited, Not Just Ranked - What the data actually shows about whether ranking predicts AI citation, and what else affects it.
- How AI Engines Actually Choose What to Cite - The retrieval, reranking and generation mechanism behind an AI citation, and why ranking #1 doesn't guarantee it.
- How to Structure Content So AI Engines Can Quote It - What structure can and can't do for whether AI engines can quote your content.
- Q&A Formatting Without Turning Your Page Into an FAQ Dump - What the evidence does and doesn't support about Q&A formatting, TL;DRs and bullet lists as citation tactics.
- Does Structured Data Actually Help You Get Cited? - What 2026 research actually found about whether schema markup and page speed affect AI citation.
- Writing Claims AI Engines Actually Trust - What the mixed research on content trustworthiness to AI systems actually supports.
- Does Domain Authority Actually Matter for AI Citations? - What the evidence shows about how backlink metrics correlate with AI brand visibility compared to other signals.
- How to Repurpose Existing Content for AEO Without a Full Rewrite - What controlled research and Google's guidance support when updating existing content for AI citation.
- The Future of AEO: What's Documented, What's Google's Plan, and What's Still Unresolved - What's documented, what's Google's stated direction, and what's still unresolved in AEO.
Technical SEO migrations
- Technical SEO Checklist for SaaS Website Migrations - A phase-based SEO checklist for SaaS replatforms, covering planning through recovery.
- URL Inventory and Redirect Mapping for SaaS Migrations - How to build a defensible URL inventory and redirect map for a SaaS migration.
- Diagnosing and Recovering From Migration Traffic Drops - How to tell a migration defect from normal post-move fluctuation and judge how long to keep waiting.
- SaaS Migration Planning: Scope, Baselines, Owners and Risk - What to decide and record before a SaaS migration is built - scope, baselines, ownership and go/no-go criteria.
- Staging SEO QA Checklist Before Launch - How to crawl staging against production and run parity checks before launch.
- Rendering and Indexability for React, Vue and Headless Migrations - How to verify a framework migration still delivers indexable content.
- Launch-Day SEO Checklist and Rollback Plan for SaaS Migrations - The cutover sequence for a SaaS migration launch day, and rollback triggers separated from escalation triggers.
- Post-Migration SEO Monitoring: The First 30 Days - What to watch after a migration, on what cadence, and when to escalate.
SaaS pricing and structured data
- Schema for SaaS Pricing Pages: What It Establishes and What It Doesn't - What structured data does and doesn't establish for a SaaS pricing page - the hub for CoreAEX's pricing schema cluster.
- Product, SoftwareApplication, Service, Offer or AggregateOffer? Choosing Schema for SaaS Pricing - How to choose a schema type for a SaaS pricing page among Product, SoftwareApplication, Service, Offer and AggregateOffer.
- How to Mark Up Tiered, Subscription, Per-Seat and Usage-Based SaaS Pricing - How to mark up tiered, subscription, per-seat and usage-based SaaS pricing in Schema.org.
- Implementing and Validating SaaS Pricing Schema Without Data Drift - How to generate, deliver and test SaaS pricing markup from one source of truth without data drift.
- Why SaaS Prices Go Missing or Stale in Search and AI Answers - A layer-by-layer diagnostic for SaaS pricing that disappears, goes stale or comes back wrong.
- How to Measure SaaS Pricing Schema, AI Citations and Price Accuracy - A measurement framework for pricing schema and AI visibility - what each data source exposes and where visibility stops being ROI.
AI vendor shortlists
- How AI Builds B2B SaaS Vendor Shortlists - and How to Earn a Place - What's documented about how AI builds B2B SaaS vendor shortlists, and how to earn a defensible place.
- Why AI Vendor Shortlists Change Across Prompts, Buyers and Markets - How much AI-generated vendor lists move between runs, days and months, and how to tell a real change from ordinary variation.
- How to Test and Measure AI Shortlist Visibility - A protocol for measuring whether AI answers propose your SaaS product, including prompt-panel design and run counts.
- Which Sources AI Cites for B2B Software Recommendations - What published measurements of AI source composition report for B2B software recommendations specifically.
- Do Third-Party Reviews Affect AI Vendor Recommendations? - What the published evidence shows about how often review platforms are cited in AI vendor answers.
- Why Your SaaS Brand Is Missing From AI Recommendations - How to work out why your product doesn't appear in an AI answer, ordered by what each test rules out.
- Do Comparison and Alternatives Pages Get You Into AI Recommendations? - What the measurements actually cover on whether comparison and alternatives pages get you into AI recommendations.
- Does Consistent Product Information Across the Web Affect AI Recommendations? - What's documented - and what isn't - about whether consistent product information across the web affects AI recommendations.
- How to Break Down a B2B SaaS Buying Question for AI Discovery - How to break down a B2B SaaS buying question into the parts AI discovery actually evaluates.
Product accuracy and source correction
- When AI Gets Your SaaS Product Wrong: Diagnose and Correct the Source - A ten-step workflow for wrong AI answers about your product, from capture through re-test.
- How to Capture and Classify an Incorrect AI Answer About Your SaaS Product - What to record so a wrong AI answer about your product is reproducible, and how to classify the error.
- How to Correct Wrong SaaS Information on Review Sites, Directories and Listicles - What review sites, directories and listicles actually document about correcting wrong SaaS information.
- How to Fix Conflicting Product Information Across Your SaaS Website - An inventory, adjudication and ownership method for fixing conflicting product information across your own site.
- How Long Does It Take AI Answers to Reflect a Corrected SaaS Source? - What providers document - and don't - about how long AI answers take to reflect a corrected source.
- How to Report Incorrect Information to ChatGPT, Google, Perplexity and Other AI Products - What each major AI provider's reporting route is documented to do, and what it doesn't cover.
- How to Test Whether Correcting a Source Changed AI Answers - How to build a frozen prompt panel to test whether correcting a source changed AI answers.
- How to Trace the Sources Behind a Wrong AI Product Claim - How to trace the sources behind a wrong AI claim about your product, and label what's demonstrated versus inferred.
- Wrong Price, Feature or Integration: Which SaaS Source Should You Correct First? - Which SaaS source to correct first when a price, feature or integration claim is wrong.
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