DataWorks
B2B Marketing Data, Attribution & Analytics
Without visibility, you're flying blind. Without correlation, you're guessing.
Most marketing teams are rich in dashboards and poor in answers. DataWorks covers attribution, measurement infrastructure, and the intelligence layer that makes every other marketing investment legible.
Without visibility you are flying blind; without correlation you are guessing — this section is about replacing both with evidence.
GA4’s new AI Assistant channel: the attribution cleanup move
GA4’s new AI Assistant channel auto-classifies chatbot referrals, giving demand gen teams a clean cohort to measure conversion and pipeline influence.
Audit your martech for agent cannibalization: start with newsletters
A practical 2026 playbook to audit martech tools for agent replacement, starting with newsletters, with metrics, guardrails, and risks.
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.
Stop defending clicks: a 4-layer exec report that holds up
A practical 4-layer exec reporting stack to connect B2B SaaS marketing activity to pipeline and revenue without over-claiming attribution.
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.
RDRs are the buying-group operators revenue teams keep missing
In 2026, RDRs are shifting from lead follow-up to buying-group execution, using opportunity-member tracking and AI to drive measurable deal progression.
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.