Marketing Resources & Insights
Current notes on measurement, multi-agent systems, and evidence-first applied AI.
Latest Insights
Practical explanations with assumptions, limitations, and decision context
8 min read
Third-Party Cookies Aren't Gone: Build Measurement That Does Not Depend on Them
Chrome retained third-party-cookie choice, while other browsers, modes, and users restrict it. Learn how first-party data, experiments, and validated estimates make measurement more resilient.
sig.ai Research
Editorial Team
Updated Jul 2026
12 min read
Multi-Agent Reinforcement Learning for Marketing: A Practical Architecture
A reference architecture for coordinating task-specific agents while keeping objectives, constraints, failure modes, and review points visible.
Yong Huang
Founder & CEO
Updated Jul 2026
10 min read
Incrementality Testing at Scale: Moving Beyond A/B Tests
How modern incrementality measurement differs from traditional A/B testing. We cover ghost ads, PSA tests, geo-experiments, and the evidence needed to make a budget decision.
sig.ai Research
Editorial Team
Updated Jul 2026
Methodology & Decision Briefs
Current source-backed material for defining a method, reviewing an AI workflow, or preparing a business handoff.
Ontology-First AI for Small Business
Our methodology paper: knowledge as ontology plus facts, insight as reasoning with provenance, action under explicit goals and constraints — and a person making every decision. The framework behind our engagements and TransferOS.
TransferOS one-pagers — the Qualification Audit, seller and broker explainers, and a sample Transition-Risk Teardown — are on the TransferOS page, and the free Key-Person Risk Scorecard scores a deal in five minutes.
Incrementality design checklist
Define the decision, intervention, causal baseline, validity checks, and uncertainty before selecting a test design.
Use when a budget decision needs causal evidence.
Review the checklistMulti-agent evaluation checklist
Separate orchestration from learning, then test shared state, rewards, conflicts, guardrails, and human review.
Use when several AI roles influence one decision.
Review the architectureKey-person dependency review
Map owner-held knowledge, decision rights, operating routines, and evidence needed for a reliable business handoff.
Use when an acquisition depends on one operator.
Explore TransferOSA focused working session around one active decision
Bring the audience, available evidence, constraints, and decision you need to improve. The session is scoped to produce a reviewable next-step brief, not a generic presentation.
Incrementality design
Baseline, method, validity, decision threshold
Attribution diagnosis
Coverage, identity assumptions, reconciliation
Applied AI review
Workflow, evaluation, controls, escalation