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A research project in Hallway contains everything related to a specific research initiative: your research context, learning objectives, interview guide, respondent sessions, and synthesized insights.

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Before You Start

Think about what you want to learn. Good research projects start with clear questions:
  • What decisions will this research inform?
  • What do you need to understand about your users or stakeholders?
  • What assumptions do you want to validate?

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Creating a New Project

1

Navigate to Dashboard

Sign in to app.hallway.com and click New Project in the top right corner.
2

Enter Project Details

Fill in the project form with your research details.
3

Add Learning Objectives

Define what you want to learn—manually or with AI assistance.
4

Create the Project

Click Create Project to save your project in Draft status.

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Project Fields Explained

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Project Name

Give your project a clear, descriptive name that identifies the research topic. Good names help you find projects later and give respondents context. 
New Hire Onboarding Experience Research
Q4 Product Feature Validation
Enterprise User Pain Points Discovery

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Research Context

Explain what you’re researching and why. This helps the AI generate better interview questions and gives respondents context about the study. Include:
  • Background: What led to this research?
  • Goals: What decisions will this inform?
  • Scope: What aspects are you focusing on?
Minimum 20 characters required. More context leads to better interview guides.
Example:
We’re redesigning our onboarding flow for new team members. Currently, 40% of new hires don’t complete setup and exit interviews mention confusion during setup. We want to understand specifically where users get stuck and what information they need at each step to feel confident moving forward.

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Target Respondents (Optional)

Describe who should participate in interviews. This helps:
  • The AI tailor interview questions appropriately
  • You remember who to recruit
  • Ensure consistent participant criteria
Examples:
  • “SaaS product managers with 3+ years experience”
  • “First-time users who signed up in the last 30 days”
  • “Team leads in our sales organization”

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Respondent Attributes (Optional)

If your workspace has attribute categories configured, you can enable them for your project to collect demographic information from respondents.
1

Expand Respondent Attributes

Click on the Respondent Attributes section to expand it.
2

Select Categories

Check the categories you want to collect (e.g., Department, Role Level).
3

Set Requirements

Optionally mark categories as Required if respondents must provide them.
Attributes enable you to:
  • Filter sessions by demographic segments
  • See patterns across different respondent groups
  • Export reports with demographic breakdowns
Attributes are configured at the workspace level in Settings > Workspace. See Workspace Settings to set up categories.

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Adding Learning Objectives

Learning objectives are the specific things you want to learn from interviews. They guide the AI interviewer’s questions and focus.

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Manual Entry

Click Add Objective to add each learning objective. Write clear, specific statements:
  • “Understand what triggers users to seek a solution like ours”
  • “Identify the top 3 frustrations with the current checkout process”
  • “Learn how users currently solve this problem without our product”
  • “Discover what would make users recommend us to colleagues”

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Using AI Assistant

If you’re not sure how to phrase objectives, use the AI Assistant:
  1. Click AI Assistant - Generate Objectives to expand the panel
  2. Describe what you want to learn in plain English
  3. Click Generate Objectives
  4. Review the AI-generated objectives
  5. Accept, edit, or regenerate as needed
Write at least 20 characters describing your research goals. The more detail you provide, the better the generated objectives.
Example input:
“I want to understand why new team members take so long to complete onboarding. Are they confused? Too busy? Waiting for approvals? I also want to know what would make the process feel easier and what they wish they knew before starting.”
Example output:
  1. Identify the primary blockers that delay new team member onboarding completion
  2. Understand how internal approval processes impact onboarding timelines
  3. Discover what information or resources team members wish they had at the start of onboarding
  4. Learn what a smooth, efficient onboarding experience looks like from the team member perspective

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Project Status

Projects move through three statuses:
StatusDescriptionWhat You Can Do
DraftInitial state after creationEdit all settings, generate/edit guide
ActiveReady to collect responsesShare link, collect interviews, edit guide
ClosedNo longer accepting responsesView data, export insights
Closing a project stops new interviews. Make sure you’ve collected all needed responses before closing.

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After Creating Your Project

Once your project is created, you’ll need to:
  1. Generate an Interview Guide - Go to the Guide tab and click “Generate Interview Guide”
  2. Review and Edit - Check the generated guide and make any adjustments
  3. Activate - Click “Activate Project” to get your shareable interview link

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Best Practices

Focused projects generate better insights than broad, unfocused ones. You can always create additional projects for different topics.
The more context you provide, the better the AI can generate relevant interview questions. Include background, goals, and constraints.
Too many objectives dilute focus. If you have more than 7, consider splitting into multiple projects.
AI-generated guides are a starting point. Review them to ensure they match your tone, ask the right questions, and cover your objectives.

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Next Steps