• Managing Multiple UX Research Projects?

    Build and Manage Your Own Customer Research Panel, and Control Your Destiny

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    A Dedicated Research Panel For You

    Although professional recruiting firms can be excellent partners, it isn't always affordable or practical to use them for every research study - and there are good reasons to cultivate your own panel. Doing so takes about 2-3 hours to setup, and about 30 minutes/week to "feed and maintain."


    If you spend, on average, $150-$200 recruiting each participant in your existing research studies, this process can save you up to $2000 for every study you run.
    Down at the bottom of this post is a tool you can use to collect, manage and track your own participant pool.


    Finding participants is always one of the hardest parts of performing good research


    When we work with clients to understand an audience, we're often asked to turn around and produce results in a fairly short period of time - sometimes as little as a week.


    This is not a problem with a research engagement that's ongoing, and has reached a certain self-sustaining cadence. But starting from a standstill, and aside from the pressure of producing and vetting a good test plan and script, it's nearly impossible to recruit a good sample of participants in fewer than 3-4 weeks.


    And yet - it's hard to prove the value of research when you can't perform it well, and quickly. Many companies are still only beginning to understand the value of customer-centric research in their Digital Transformation, and for a growing UX Research department (even if you're just one person) it can be very useful to prove your value early, and often, and quickly.


    This free tool lets you manage a participant panel, including the ability to create and manage Research events and individual Research Sessions. Keeping your participants organized this way not only lets you manage your panel in just a few minutes each week, it also forms the basis of a toolset that will let you build deep-research tools that let you compare data across many studies.