Get Started 🠖 planning a study
Workflows
Before you build a protocol or run an interview, it helps to plan how your study will move through the Network Canvas tools from end to end. Whichever tools you choose, the shape of a study is the same: design a protocol, collect data by running it, and export that data for analysis.
Workflows at a glance
There are three ways to run a study, depending on whether your interviews happen in person or remotely and whether your devices have an internet connection. The table below shows the tools each one uses at every phase.
| Workflow | Phase 1Design a protocol | Phase 2Collect data | Phase 3Export data |
|---|---|---|---|
| Desktop, onlineIn-person interviews on internet-connected devices. | ArchitectDesign a protocol in Architect for Interviewer (new studies); Architect Classic for Interviewer Classic. | InterviewerDeploy to each device via a cloud file service. | Cloud serviceUpload exports to the same cloud service to consolidate them. |
| Desktop, offlineThe same desktop flow when devices have no internet. | ArchitectDesign a protocol in Architect for Interviewer (new studies); Architect Classic for Interviewer Classic. | InterviewerCarry the protocol to devices on a USB drive. | USB driveMove collected data back off via USB. |
| Web-basedRemote interviews completed in the browser. | ArchitectDesign the protocol in the browser. | FrescoUpload once; participants interview in their browser. | Fresco dashboardManage centrally; export from the dashboard or pull via the Fresco API. |
For the full step-by-step walkthrough of each option — including protocol deployment, data export, and backup best practices — see the Protocol and Data Workflows tutorial.
Before you start collecting data
Planning a study is more than choosing a workflow. Two topics are worth reviewing early, because they shape how you design your protocol and handle participant data:
- GDPR Compliance Guide — how Interviewer and Fresco handle participant data and what your responsibilities are.
- IRB and Security Best Practices — how to think about data security and institutional review when working with sensitive data.