DataWorks
Without visibility, you're flying blind. Without correlation, you're guessing.
The ultimate guide didn’t die. It got unbundled.
In 2026, ultimate guides aren’t dead—they’re less defensible; unbundle one mega-guide into a hub plus decision pages built for answer-first search.
Stop trusting AI dashboards: three silent ways numbers go wrong
A practical 2026 playbook to cut AI analytics hallucinations by forcing source-backed retrieval, governed metric definitions, and escalation guardrails.
Tech SEO audits in 2026: measure crawl speed, not rankings
A practical 2026 tech SEO audit focused on AI crawlability, server-rendered HTML, and “technical accessibility” so your brand shows up in AI answers.
Gemini dashboards in Google Ads: the real win is faster decisions
Google Ads’ Gemini Dashboards speed up reporting; this playbook shows how to turn prompt-driven insights into weekly experiments with metrics and guardrails.
Identity without oversight is a measurement bug, not a privacy debate
A practical playbook to test identity oversight with a holdout experiment, proving incremental pipeline lift while catching silent breakage and fraud risk.
Ahrefs tested schema for AI citations. Nothing moved.
Ahrefs found adding JSON-LD schema didn’t meaningfully lift AI citations, so treat schema as hygiene and test fan-out query coverage instead.
AEO prompt tracking: the missing measurement between AI visibility and pipeline
A practical 2026 playbook for AEO prompt tracking: build a buyer prompt library, log multi-engine answers, and tie citations to pipeline signals.
An “AI VP of Marketing” isn’t a VP. It’s the bottom half of four jobs
An “AI VP Marketing” won’t replace leadership, but it can remove the bottom-half work; here’s how to automate workflows with metrics and guardrails.
Claude Code for marketing research: stop hallucinations in reports
A practical Claude Code workflow for State of Marketing research that reduces hallucinations using unknown-first schemas, evidence gates, and QA checks.