Keeping track of participants, showing them their results, and more: Why might it be useful to use query string parameters in my survey/study?🔗

Suppose that you want to run a randomized controlled trial testing an intervention that is designed to help sedentary people to build up a habit of regular aerobic exercise. You might want to have a screening survey that identifies people who currently do less than 60 minutes of aerobic exercise per week, and then you might want to randomize them and to collect further data from them at several time points (throughout and following the intervention).

How would you keep track of participants across the screening and follow-up surveys? How would you keep track of who has or hasn't clicked on your follow-up survey links? And how would you make sure you're only asking questions that are relevant to the person's intervention group and stage of data collection? In all of these situations, one answer is to use query string parameters. These are the parameters (or keys) in a URL that assign values to specified attributes (such as participantID, age, and so on).

Each of your GuidedTrack programs will have its own run link, but there are many reasons you might want to customize that run link by adding query string parameters. You can customize URL query string attributes to:

  • keep track of participants who complete both screening and follow-up surveys, or other multi-part surveys, studies, or experiments[1];
  • avoid the need to ask the same questions across multiple surveys;
  • create a unique URL for each participant to use to view their survey results (for more on this, please see the section on results programs);
  • provide a customized program experience for participants, based on the URL query string attributes you set for them; and/or...
  • keep track of which participants have completed a survey that you've emailed to them (by personalizing the link you ask them to click on in the email, capturing their unique participantID number via the URL parameters).

[1] Throughout this guide, we use the terms studies, surveys, and experiments interchangeably, but we appreciate that different users may engage with GT depending on which of these they are designing. If you are running an observational study or survey, you may not need to consult the sections on randomization, but we think you will still benefit from the other sections of this guide.