Automating Insights Workflows

Insights work suffers when every project becomes its own custom build: new survey logic, a fresh sampling plan, another analysis workbook, another reporting template, another round of stakeholder handoffs. Without structure, speed turns into version chaos, QA risk, and a lot of hidden labor.

Instead of suffering through disjointed sequences of heroic one-offs, you can leverage platforms that treat research like a system. Workflow automation tools reduce “swivel-chair work” across the lifecycle: scoping and intake, questionnaire and discussion-guide building, sample sourcing and field monitoring, analysis and synthesis, reporting, and stakeholder delivery. Some do it through end-to-end suites and others through orchestration, but, either way, they enable you to swivel less and recline more.

The introduction of AI assistance to the workflow doesn’t replace judgment; it reduces the pressure that paralyzes good researchers within production work. Think of it as “practical acceleration,” such as:

• Drafting instruments faster
• Tagging and summarizing open-ends with traceability
• Generating first-pass narratives
• Surfacing anomalies early
• Making knowledge searchable so you don’t pay twice for the same learning

If you’ve ever felt like you are re-inventing the wheel with each project – or spinning wheels like a hamster – it’s time to get off the treadmill and see how workflow automation can help you make progress and achieve more. 

Who should attend?

• ResearchOps and enablement leaders building standardized, scalable workflows
• Insights managers responsible for effectiveness across recurring deliverables
• Agencies and research teams juggling multiple tools per study
• Product, UX, and marketing teams desiring cleaner handoffs and faster synthesis