Optimizing the Student Experience with ASU's Call Center
Usability Testing
Iterative UX Research
Qualitative
Interviews
My Role: UX Researcher
Team Size: 2 UX Researchers
To unlock the full potential of a AI tool, this study dives into the workflows, challenges, and needs of Call Center Specialists. Using UX research to analyze the workflows and behaviors within their daily operations with customers, I aimed to reveal key opportunities for optimization and ensure the tool’s success.
Challenge
How can we enhance this AI tool t to streamline workflows, improve access to relevant information, reduce time spent on cases, and address the challenges Call Center Specialists face during customer interactions?
My Impact
This study provided valuable insights that shaped and propelled four additional UX research studies I led for this team, enabling me to strengthen my mixed-methods research.
Overall, this resulted in measurable improvements, including:
$146,000 estimated revenue savings per year
$146,000 estimated revenue savings per year
23% increase in pre-authenticated calls
23% increase in pre-authenticated calls
16% decrease in average call time
16% decrease in average call time
Research Process
Foundational research
Conducting research to understand the Specialist's workflows and broader ecosystem by analyzing existing information, providing valuable context to guide the research plan and inform study objectives.
Interviews
40 minute moderated 1:1 observational interview sessions.
9 total | Mix of experience
Analysis and synthesis
I utilized task mapping and thematic analysis to highlight user challenges, ensuring a clear narrative of their pains and needs is crafted, leading to actionable, data-driven recommendations.
Interview question focus points
Demographic inquiries
Introduction, background, years of experience, role overview
Workflow questions
Processes, daily tasks, task flow, operational steps
Tools and resources
Support systems, resources, technology
Pain points and frustrations
Challenges, barriers, frustrations, obstacles
Opportunities and feedback
Suggestions from Specialists, growth areas, recommendations
What did we find out?
Through our research, several key findings emerged that highlight critical challenges and opportunities to optimize the Call Center Copilot.
For example, task analysis revealed areas where a 21-step process could be streamlined into just 5 steps, significantly improving efficiency for Specialists.
Key Findings
#1 User workflows
Each tool required 5+ common tasks or pages to sort through during a interaction. Many expressed frustration with DUO authentication and spam cases during their workflow.
#2 Common tools used
Peoplesoft, Salesforces, KB articles, MyASU, Slack, and Google. Lots of crossover in information sources.
#3 Lack of trust in existing tools
The previous AI tool implementation left some participants feeling it was unreliable, partly due to being labeled as a "pilot tool," which led them to double-check their information for accuracy.
#4 Opportunities for automation
Specialists mentioned many of their cases seemed like something a human did not need to do.
“You don’t need a live person to do a password reset or authentication. These types of things can be automated. It would take away monotonous and tedious work. They should be spending their time on issues that need real troubleshooting.”
Unfortunately, the mobile view of this project is a work-in-progress. Come back later!
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Recommendations
Building on the key findings, we developed a set of actionable recommendations aimed at addressing the identified challenges and maximizing the potential of the Call Center Copilot.
These chosen recommendations focus on streamlining workflows, improving usability, and enhancing overall efficiency for Specialists.
Automation
Consider having a automated message for pre-authentication using AI before to reaching a Specialist to reduce call times.
This was implemented dropping call times by 16% and increasing volume of authenticated callers by 23%.
Tool consolidation
Exploring initiative for consolidating tools to reduce areas to check for information.
Opportunity to decrease workflow steps by 76%.
Adoption and trust
Ensuring that perceived usefulness, language, and usability is considered during initial phase of tool as it may impact trust and adoption.
This is a tool that will initially change their workflow.
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