Aligning Workflows with Brokers’ Mental Models
Project Timeline:
5 months
My role:
UX Researcher, Design Strategy, Product Designer
Tools:
Figma, Notion, Miro, Adobe CC
Overview
This startup supports health insurance agents in the United States by simplifying how they communicate insurance information to their clients. The platform offers brokers and agencies a comprehensive view of the small group health insurance landscape, enabling informed decision-making. The platform itself contains an interactive dashboard that allows brokers to manage their employer clients, employee data, and health insurance plan data.
Problem Statement
Brokers faced significant challenges in the existing workflow, which was critical to completing steps required prior to quoting, such as inputting client, employee, and plan data. The interface resembled a clunky database with little guidance or context, making it confusing for both new and experienced users.
Why It Mattered
Streamlining the workflow process was crucial to:
Reduce Time on Data Entry: Allow brokers to focus on delivering value to their clients instead of struggling with the interface.
Improve Workflow Alignment: Ensure the platform supports brokers’ mental models, reducing frustration and errors.
Minimize Human Error: Simplify processes to reduce multitasking and increase data accuracy.
Enhance User Experience: Provide a smoother, more intuitive system that drives retention and reduces churn.
Research & Insights
Research Process
To address the challenges brokers faced in the existing workflow, I employed user-centric research methods to uncover their mental models and inform the design of an intuitive, task-oriented interface.
In-Depth Interviews:
Conducted interviews with brokers to understand their workflows, daily tasks, and pain points.
Explored how brokers approached steps like entering client data, assigning plans, and managing groups.
Mapped their preferred processes to uncover gaps between their expectations and the existing workflow.
Contextual Inquiry:
Observed brokers navigating the platform and completing key tasks to identify disconnects between their mental models and the interface.
Key Findings
Completion Rates: Only 45% of users successfully completed the workflow.
Clarity and Data Accessibility:
55% of users missed important date fields, leading to a lack of results being returned without explanation.
60% struggled to find core benefit details buried in overly granular plans data.
Task-Oriented Design: The workflow needed to align with brokers’ real-world processes, enabling seamless transitions between steps like data entry and quoting.
Custom Census Templates: Brokers often received employer or carrier-provided census templates that included data fields like plan details, employee information, and dependents. They expected an AMS platform to support uploading these files directly.
Design Solution
Streamlining Navigation with Clearer Pathways
Made key actions, such as assigning users or editing groups, accessible from multiple entry points to reduce unnecessary navigation.
An AI-assisted consulting platform where brokers interacted with a system that dynamically surfaced recommendations based on user input—similar to how a chatbot refines responses based on conversation flow. Using context-aware prompts, progressive disclosure, and real-time feedback loops, I created a step-by-step task flow that guided brokers seamlessly from data entry to quoting, mimicking structured chatbot interactions.
Simplifying Data Presentation
Collapsed granular details, like per-employee contributions and less significant plan information, while highlighting key stats front and center on the plans page to create a cleaner, more focused interface.
Census Workflow
Guided users to either upload a census document using the platform’s pre-designed template or manually add employees.
This structured process not only streamlined data entry but also laid the groundwork for future enhancements, enabling brokers to upload employer-provided census documents directly.
Structuring Tasks in a Logical, Intuitive Order
Added guided workflows for tasks like assigning users after purchasing seats to improve clarity and usability.
Notable Changes
Following two rounds of usability testing, I implemented key adjustments:
Navigation Improvements:
Renamed "Customer Data" to "My Groups": Aligned the terminology with brokers' language and clarified its purpose.
Added "Back to My Groups" Side Nav Link: Enabled seamless navigation from detailed views like "Employees" back to the group overview.
Data Entry Enhancements:
Custom Census Template Uploads: Initiated the design for a column mapping feature to handle employer-provided templates, reducing manual entry.
Manual Entry Simplification: Redesigned the manual input workflow to make it more intuitive and time-efficient, while prioritizing automated solutions for the future.
Contribution Data Adjustments:
Employer-Centric Data: Redesigned the contributions section to display amounts employers pay, aligning with how brokers discuss costs with clients.
Simplified Options: Removed unused contribution types from dropdown menus to focus on the most relevant options.
Employer Profile Page:
Central Hub: Created a new employer profile page that serves as an overview and action hub, offering quick access to key functions like editing data and generating quotes.
Scalability: Designed the page to scale with future features, such as proposal generation and analytics.
Expand Rows Button: Made the expand rows button more prominent to improve visibility of employee and dependent details.
Date Selector Improvements: Added a streamlined date selector to help brokers narrow their focus when viewing employer, employee, and plan data.
Challenges
Transitioning Existing Users
Many current users were accustomed to the old interface. We needed to ensure the redesigned workflow minimized disruption and provided clear guidance for both new and existing usersTemplate Field Mismatches
Employer-provided census templates often included fields not supported in the platform’s templates. Addressing this issue required planning for AI-driven column mapping solutions.Contribution Complexity
Redesigning the contributions section required balancing simplicity with the flexibility brokers needed to handle varying client requirements.
Impact
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Completion Rate
Increased task completion rate to 90%, with users successfully navigating the workflow to reach the quoting stage.
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Improved Efficiency
Enabled brokers to manage and update client data more efficiently, directly aligning with their mental models.
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Clarity
Reduced missed date field instances through prominent placement and clear prompts. Surfaced core benefit details upfront, reducing user frustration from 60% to 3%.
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Enhanced Manual Data Entry:
Redesigned the experience for manual data entry, making the process more intuitive and user-friendly.
Future Steps
AI-Driven Column Mapping: Automated census uploads by intelligently matching employer-provided templates with platform fields, minimizing manual input. Designed a system that recognized and corrected inconsistencies in health plan names using AI-driven suggestions and human validation steps, similar to how voice assistants refine and confirm user queries.
Enhanced Employer Profile Page: Expand the profile page to include analytics, proposal generation, and more comprehensive data visualizations.
Seamless Integration with Quoting: Connect the workflow flow with the quoting process to streamline transitions and enable brokers to generate quotes effortlessly.
Conclusion
This redesign tackled key challenges brokers faced in navigating and completing platform workflows. By aligning the process with brokers’ mental models, simplifying data entry, and improving access to core benefit details, we significantly enhanced the user experience. A 90% task completion rate highlights the impact, enabling brokers to efficiently input data and move seamlessly to quoting. These changes streamlined workflows and created a scalable foundation for future enhancements, including AI-driven automation and expanded employer profiles.