Customer Success Lab
A Branching Simulation for Risk Recognition & Decision-Making
This project shows how I turned a workplace performance problem into a realistic, scenario-based learning experience where learners practice making decisions and see the consequences of their choices.
Skills Demonstrated
Performance gap and needs analysis
Action mapping and performance-focused design
Branching scenario design
Consequence-based learning and feedback
Designing realistic, data-driven decision practice
UX/UI design for simulated workplace environments
High-fidelity prototyping
AI-assisted custom interaction development
Rapid prototyping with HTML/CSS/JavaScript
Application of adult learning principles
Project Overview
This hypothetical training solution helps new Customer Success Associates recognize account risk while balancing customer needs with productivity.
I used ChatGPT as a simulated SME to inform the analysis and scenario development, then designed a branching simulation with realistic decisions and consequences. I used Claude Code to help develop the interactive prototype.
The Problem
The Solution
The Customer Success team was seeing an increase in preventable customer churn. When lost accounts were reviewed, their histories often showed earlier signs of trouble that had gone unaddressed.
The company wanted to understand why those opportunities were being missed and what could be done earlier.
I designed a scenario-based training module that gives new CSAs a safe place to practice the decisions they face on the job.
Learners work through realistic customer interactions and decide when to look deeper, what information matters, when to follow up, and when to escalate. Their choices affect both the customer account and the time they spend away from the customer queue.
The goal is to help new CSAs build the judgment that comes with experience, without putting real customer accounts at risk.
The Gap & Need
The analysis revealed that newer CSAs could resolve immediate customer issues but were less likely to connect those interactions to larger patterns in the account.
They needed practice recognizing when to investigate further, deciding when to follow up or escalate, and balancing account health with productivity.
This project followed a structured instructional design process, drawing on both the ADDIE framework and SAM.
The Full Process
