Use case
ResearchOps — qualitative research infrastructure for your organisation
Research ops teams are responsible for making qualitative research repeatable, governable, and fast enough to keep up with product cycles. Fieldwork gives ops leads a single system for study templates, coverage standards, and continuous output—so research does not stall when a moderator is unavailable or a timeline compresses.
What are ResearchOps teams actually solving?
ResearchOps is not only about running interviews. It is about making sure the organisation can run research reliably at volume without quality degrading invisibly.
Common failure modes include moderator dependency, inconsistent session depth, synthesis bottlenecks, and insight that never escapes the research team’s tools. Fieldwork targets the execution and measurement layers so standards show up in what participants experience—not only in a slide deck promise.
How does Fieldwork support a research ops function?
Standardisation
Define interview structures once and reuse them across projects and researchers. Every session runs with the same topic coverage behaviour and depth calibration, which removes moderator-to-moderator variance that otherwise shows up as “some sessions feel deeper.” Teams can build a library of templates for recurring programmes—onboarding feedback, quarterly pulse studies, concept tests—without rebuilding from scratch each quarter.
Coverage governance
Topic coverage is tracked automatically for every session. Gap reports surface topics that stayed underexplored across many participants, so leads can review health without reading every transcript. Calibration visibility helps you see which study structures are working and which need tightening before the next wave.
Operational throughput
Studies can launch the same day as the brief. Sessions run continuously without a scheduling queue. Analysis begins as sessions complete, which shifts researcher time toward synthesis and stakeholder communication instead of logistics.
What does a quarterly pulse template look like at scale?
A research ops lead standardises a quarterly user pulse for an enterprise software company. Multiple researchers launch the same approved template; leadership wants confidence that every wave is comparable.
Example conversation · not live data
What changed in your workflow this quarter compared to last—especially anything that slowed you down?
Pattern note: same template, forty sessions — topic coverage on “workflow blockers” resolves in 34/40; six flagged for shallow follow-up.
Aggregated reporting shows whether the wave met coverage standards before anyone writes a narrative summary—exactly the governance layer ops teams are hired to provide.
Is Fieldwork built for teams that need to scale?
Growth and Scale plans include multiple seats. Workspace roles separate owners, researchers, and viewers. Paid plans add export controls—including CSV and raw transcript export where applicable—and configurable data retention. Enterprise adds single sign-on, service-level agreements, and annual invoicing for organisations with procurement requirements.
Frequently asked questions
What is ResearchOps and why does it matter?
ResearchOps—research operations—is the discipline of making qualitative research scalable, consistent, and governable across teams. It is the systems layer: templates, access, retention, recruitment hand-offs, and insight operations that keep research from living in one person’s notebook. Without it, quality depends on individual moderators and projects drift apart even when the organisation pretends it has a single standard.
How does Fieldwork help standardise research across a team?
Research leads define study structures—topics, interview depth settings, routing rules, and screening criteria—that become the template for a programme. Every participant session follows that structure the same way, regardless of which researcher launched it or when it runs. Automated quality checks flag sessions that look thin relative to the standard you set, so QA scales beyond spot-reading transcripts.
Can we control who has access to what in Fieldwork?
Yes. Your Fieldwork account supports role levels: owners handle billing and workspace settings, researchers create and manage studies, and viewers can read outputs without editing study configuration. That separation matters when leadership wants visibility without risking accidental changes to live fieldwork.
How do we handle participant consent and data governance at scale?
Fieldwork records consent for each interview session with timestamp, study, and locale. Retention settings are configurable at the workspace level so teams can align transcripts and participant artefacts to policy. Enterprise plans extend this with custom retention posture and dedicated support for compliance conversations.
Does Fieldwork integrate with our existing research repository?
Fieldwork exports structured data you can import into repositories like Dovetail or your internal warehouse. Webhooks on Growth-and-above SDK plans can push interview outcomes automatically, which reduces copy-paste operations when ResearchOps is trying to keep a single source of truth.
Explore: Interviews, Ambient SDK, and UX research programmes.