Millions of users seek help every day to troubleshoot or learn new software applications, but often struggle in locating useful answers.
My research investigates new designs for software help that leverage the expertise of the user community and make it easier for users to retrieve relevant help in the context of their software tasks. I will describe one such system, LemonAid, that introduced a novel selection-based crowdsourced contextual help approach for users to find Q&A from other users by selecting a label, widget, image, or another user interface element. I will discuss how LemonAid can work as a layer atop any web-based application and present results from lab and field evaluations that demonstrate LemonAid’s effectiveness and helpfulness. Lastly, I will describe how LemonAid went through the process of transitioning from an academic endeavor to a startup, AnswerDash, that is financed by venture capital and is helping millions of users worldwide.