Employee Experience Research & Training Build
CASE STUDY: Needs Analysis & Training Build for Customer Experience Agents
Huxley Social | Remote | 2023-2024
ABOUT THE PROJECT
Opt-outs were climbing and complaints about impersonal service were growing. I used agent interviews, opt-out data, and chat logs to find out why agents leaned on scripts, then built training around what those sources showed.
DELIVERABLES
⭐ Scenario-Based Training: Built from real missed moments in chat logs.
⭐ Practice Sessions: Small breakout groups to try new skills before live conversations.
⭐ End-of-Session Game: A real-time check to spot who needs 1-on-1 coaching.
⭐ Facilitator Guide: A roadmap managers can run with no training background.
WHAT I FOUND
Agents weren't just disengaged or undertrained - they were overwhelmed. High-volume periods were the primary driver of scripted, impersonal responses
SOP scripts were not being personalized because the agents were coping with the overwhelm. The training solution needed to address confidence under pressure, not just communication skills.
Peak hours were understaffed, meaning the behavior problem had an underlying operational causetraining alone would not fix
The top performer wasn't following a better script - she was making real-time judgment calls based on reading the customer's tone and adjusting accordingly
Agents had no safe space to practice those judgment calls before using them on live customers
WHO I WORKED WITH
Collaborated with the co-founder, team managers, clients, and a high-performing agent to align research findings with both the training design and the operational decisions that followed.
THE PROCESS
I combined agent voices with conversation data, then built and rolled out the training with the people who would use it.
Listening and Data Review: 1-on-1 interviews with agents and the top performer, plus opt-out data and chat log review, to find out why agents leaned on scripts and where opt-outs began.
Collaborative Design: Shaped the training with the co-founder, managers, and a high-performing agent, using what the data showed.
Training Build: Created SOPs, training plans, and feedback frameworks, and put the practice activities on the company LMS.
Rollout and Staffing: Agents completed the new training. Hours were adjusted and more staff were onboarded to reduce burnout and keep good employees.
RESULTS & ITERATION
After rolling out the new training, we saw:
💪 Higher Confidence: Employee survey results showed agents felt 68% more confident in handling complex conversations without escalation
📉 Fewer Opt-Outs: SMS opt-outs and complaints about impersonal service both decreased.
🤝 Structural Fix: The peak-hour finding led Huxley to hire extra support during busy periods.
🔄 Iteration: After evaluating and collecting more feedback, I connected the program to the company’s Slack using Matter bot, with spots to share feedback, give shout-outs, and earn bonus points for gift cards.
"Emily was instrumental in fostering a culture of continuous learning and growth within our organization." - Amber F., Co-founder, Huxley Social
WHAT I'D DO DIFFERENTLY
I would have gathered customer voice data directly - short exit surveys or customer interviews - rather than inferring customer experience solely from opt-out metrics and agent accounts. The agent perspective was rich, but triangulating it with actual customer feedback would have strengthened the research foundation.