Project background
User research reveals high expectations for support experiences, with logged-in users demanding personalized answers and quick resolutions.
Leveraging AI and user journey data, we’ve developed solutions that predict user intent and present “Quick Answers” or “Best Actions” within Help Center articles. These personalized components have achieved a 25%+ engagement rate, significantly outperforming other support navigation efforts.
In addition, I also led the efforts to establish notification framework on Google’s Help Surfaces through workshops and experimentation. With the established framework, personalized notification drove significant improvements on Task Completion .
Best Action
Traditional support experiences often lead to frustration, with lengthy and complex help center articles hindering efficient issue resolution. To address this, we developed the Best Action component. By leveraging relevant account signals, this feature intelligently guides users to the most effective solution directly within Support Surfaces, eliminating the need for tedious navigation and improving overall support satisfaction.
Quick answers
We proactively address user support needs by analyzing journey data and Help Center content to predict required information. This allows us to deliver concise, relevant answers at the top of the page, providing immediate solutions and enhancing user efficiency.
Personalized notifications
To enhance user awareness and streamline issue resolution, I developed a complete notification framework for the help center. This framework, which facilitates the categorization and prioritization of personalized notifications, resulted in a 21.5% improvement in task completion by guiding users directly to effective solutions.
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