How to create a Reframer study

When you create a new Reframer study, you'll be presented with the overview, which acts as a high-level summary of your study. Here you can add study objectives and any reference links you’d like to include (for example, to a prototype, discussion guide or participant register.)

This is also where you can add and view the sessions you’ve created for your study and add any relevant session information (such was demographics or background information about your participant).

From here, you can also navigate to the Tags tab, where you can create and edit any tags you intend to use during your study.

If you’re running several rounds of research for your project, we recommend creating separate studies for each round to make it easier to analyze your results.


Study name

Click on the header to give your study a name. Give it a meaningful name that’s consistent with your other project documentation and that will make sense to others working on the study.

Study details

Study objectives

This section is useful for recording study objectives, client details, projected dates, participant numbers, project owners, and so on. Use this space for information that will contribute to consistency across your study, be useful for anyone else who contributes to the study, and that will make sense over time.

Reference links

Use the reference links field to store any external links to prototypes, discussion guides, participant registers and any other external resources you want you and your team members to access.


A session is where you and your team capture observations during a user research session.

You can use Reframer sessions to collect research data from a variety of sources — user interviews, usability tests, focus groups, and even open text survey responses.

If you already know the details of your upcoming sessions, you can add new sessions as soon as you create your study. There are no limits on the numbers of sessions you can create or the amount of observations you can capture in each session.

Session name

Give your session a meaningful name that will make for easy reference for you and your team. For example, if you’re running sessions with individuals, you could include the participant number, their name and the session date (P1 -  Samuel - 15 April).

To protect participant privacy during your research, avoid using any identifiable information and use a unique participant identifier instead.

Session information

When you create a new session, you have the opportunity to add additional session information. Use this area to capture notes that will be useful to you and your team members in the future, such as the time and location of of a user testing session or the video conference URL. Session notes can be accessed from the study overview screen as well as inside the session itself.


Segments are useful for identifying demographics, personas, user types or other facts you want to capture about your sessions. They come in handy when you’re analyzing your results and identifying patterns.

For example, if you’re researching people based upon their job role and want a mix of ‘iPhone’, ‘Android’ and ‘Blackberry’ mobile device users then you’d create 2 segments called ‘Role’ and ‘Device’.

To create a segment click ‘Manage segments’ to open up the segment management modal. If you don’t already have any segment defined you’ll be prompted to provide a name for your first segment, for example ‘Device’.. Once you’re happy, click the ‘Create segment’ button and a corresponding segment will be created.

You’d then fill in your segment ‘Role’ with segment labels, such as ‘Designer’, ‘Developer’ etc. You can then also add segment labels to ‘Device’ such as ‘Android’, ‘iPhone’ and so on.

Applying your segments

Once defined, all your segment labels will appear in the ‘Segments’ section of each session. Here you can pick the label that best matches that particular session.


This area will show and allow you to manage all the tags associated with your study. Tags are used to mark observations that contain interesting or relevant information, making it easier to identify patterns in participants’ responses during analysis later on. For example, a large number of observations tagged with 'signup' and 'frustration' across multiple different sessions would indicate a potential area of concern. Read more about creating and managing your tags here.