DataWorks
Without visibility, you're flying blind. Without correlation, you're guessing.
Questions to Ask AI About Your Marketing Data (HubSpot, GA4, Google Ads)
Questions to Ask AI About Your Marketing Data (HubSpot, GA4, Google Ads)
Measure the AI-powered B2B funnel without trusting last-click
A practical 2026 play to tag LLM traffic in GA4/GTM, report AI-driven discovery as a channel, and tie it to qualified pipeline with clear guardrails.
Claude Code + n8n for paid ads: a guardrailed daily ops loop
A practical 2026 workflow to run ICP-scored creative and daily paid monitoring with Claude Code + n8n, with guardrails, metrics, and a decision log.
Measure the AI-powered B2B funnel without breaking GA4
A practical 2026 measurement sprint to label LLM traffic in GA4/GTM and connect AI-driven discovery to qualified pipeline without over-trusting attribution.
Measure AI-driven B2B demand before the pipeline disappears
A practical 14-day sprint to measure AI-influenced B2B demand using GA4 segmentation, cleaner definitions, and recurring claim reproduction checks.
AEO in 2026: stop treating “no-click” as a traffic problem
A practical 2026 AEO play: build a governed, schema-marked product facts layer to recover AI visibility and protect pipeline as no-click search grows.
Measuring the AI-powered B2B funnel when clicks disappear
A practical 2026 framework to measure AI-driven B2B discovery, label LLM traffic in GA4, and connect directional signals to qualified pipeline.
AEO loss recovery: the measurement playbook ops can run
A practical 2026 AEO playbook for marketing ops: quantify AI-driven organic loss, set holdouts, and measure recovery with directional attribution.
The importance of creating content regularly
Why 85% of SaaS Companies Blog—and Still Miss the Strategy That Drives Pipeline If qualified pipeline is flattening and paid CAC is creeping up, “more content” won’t fix it. Regular content creation only works when it’s treated like an operating system: predictable inputs, clear ownership, and a mea