Research Operations foundations for mid-stage product teams

Most mid-stage product teams over-invest in tooling and under-invest in the operating layer. The result is an expensive repository that nobody contributes to, and recruiting that still routes through one researcher's inbox.

Sequence the foundations

Repository taxonomy first. Recruiting pipeline second. Tooling third. In that order. The taxonomy decides what the repository can answer; the recruiting pipeline decides what evidence you can actually gather; the tooling is downstream of both.

A taxonomy your team will use

Three facets are usually enough: segment, journey stage, and evidence type. More than that and contribution rates collapse. Less than that and retrieval breaks.

Recruiting as a product

Treat your participant pipeline like a product backlog. Screeners are reusable. Incentives are budgeted. Consent is centralized. The team that gets this right runs studies in days, not weeks.

Where AI fits

AI accelerates synthesis, tagging, and screener drafting — not recruiting decisions, not consent, not analysis of decision-grade studies. Our AI-enabled Research Operations engagements wire AI into the layers where it compounds and keep it out of the layers where it misleads.