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[Case 02]

Reduced HR queries by 90% (40+ daily → 4) | Saved 10+ hours weekly | Same-day approvals

SaaS / Enterprise Software

Attendance Platform That Cut HR Queries by 90%

Building role-based experiences that gave employees speed and admins control

[Project Overview]

Designed an internal platform that replaced fragmented spreadsheet tracking with a centralized system, reducing HR queries by 90% and saving 10+ hours weekly.

[Problem Statement]

elRed tracked attendance via Slack and spreadsheets. HR manually processed payroll data, fielded 40+ daily queries about leave balances, and approvals took 2-3 days.

[Industry]

SaaS / Enterprise Software

[My Role]

Product Designer (UX & UI)

[Platforms]

Web

[Timeline]

3 weeks

View Case study

View Case study

[Persona]

Jhon Roberts

Marketing Manager

Age: 29

Location: New York City

Tech Proficiency: Moderate

Gender: Male

[Goal]

Quickly complete purchases without interruptions.

Access accurate product details and a seamless payment process.

Trust the platform with his payment and personal information.

[Frustrations]

Quickly complete purchases without interruptions.

Access accurate product details and a seamless payment process.

Trust the platform with his payment and personal information.

[Process]

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[01] User Research

Conducted interviews with 15 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Benchmarked against competitors to identify best practices for checkout flows.

[Outcome]

25% increase in checkout completion rates.
30% reduction in cart abandonment on mobile devices.
30% reduction in cart abandonment on mobile devices.

[Key Learnings]

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

Human-Centered Approach

Designing experiences that prioritize user needs and behaviors.

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