DataWorks
Without visibility, you're flying blind. Without correlation, you're guessing.
Reddit is taking your category searches: the one move that closes the gap
Reddit is outranking vendors on 957K monthly B2B searches; use a KD 21–60 “SERP wedge” experiment to win category intent and measure lift.
Marketing to mid-market RevOps leaders: the “forwardable” asset play
A practical 2026 play to reach mid-market RevOps leaders: build one “forwardable” asset for internal alignment, then distribute beyond LinkedIn.
Pain signals beat personas: a GTM experiment for 2026
A practical 2026 GTM experiment to re-rank ICP accounts by pain signals, measure qualified pipeline lift with a holdout, and avoid stalled deals.
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.