Perspectives on AI in research, research operations, and the tools that help teams move faster.
AI that programs surveys without human oversight is a liability. Here's why the testing phase — not just the build — is where human involvement matters most.
Your team programs in Decipher one week and Qualtrics the next. A platform-agnostic approach eliminates the switching tax — program the questionnaire once, deploy to any survey platform.
Most AI tools in market research come with self-published benchmarks and no independent evaluation. Here are three frameworks for actually testing them.
Not every AI use case earns its place. Here's how to spot the ones causing burnout and focus on the ones that actually make the job easier.
Research operations is becoming its own discipline, and AI is why. Here's what it covers, why it matters now, and how to get started.
The industry obsesses over AI for analysis and design. But the real time sink — translating questionnaires into programmed surveys — is the part nobody's fixing.
Survey link testing is one of the most tedious, error-prone tasks in research — and one of the most consequential. Here's why automated testing is overdue and what it looks like.
BIBD is the gold standard for MaxDiff design — but almost nobody uses it. Here's what your survey software actually does, where the gaps are, and what researchers should pay attention to.
Research teams face an impossible ask: increase throughput, cut costs, and keep quality flawless. The way out isn't working harder — it's automating the right things.
Agentic AI is everywhere in research tech marketing. Here's what it concretely means for survey workflows, how it differs from chatbots and copilots, and where human oversight still matters.
