The project itself :
Project Overview
During my summer internship with the IBM.com Information Architecture & Web Strategy team, I worked across three areas of the product experience: helping customers discover the right product, creating a scalable structure for product pages, and strengthening the internal guidance used to build those experiences.
The projects were different in scope, but they connected through the same customer journey:
Need → Discovery → Understanding → Action
I worked across UX design, information architecture and content strategy, moving between detailed audits, large-scale content analysis, experience recommendations, prototypes and implementation planning.
Problem:
IBM has a large and complex product ecosystem. Customers may arrive knowing the problem they need to solve without knowing the IBM product name, taxonomy, or product family that matches it. Once they reach a product page, the information still needs to help them understand the offering and decide what to do next.
Behind those customer experiences, internal teams also need clear, usable guidance to create consistent IBM.com content.
Goal:
Create clearer paths through IBM.com product experiences while developing approaches that could work at enterprise scale.
My role:
UX Strategist & Information Architect
IBM.com Information Architecture & Web Strategy team under Global Affairs
My work combined UX design, information architecture, content strategy, and prototyping. I worked independently on my assigned projects while incorporating research, standards, technical documentation, and feedback from IA teammates and other IBM stakeholders.
Responsibilities:
Auditing product findability, content, and information quality.
Identifying patterns across large content sets
Evaluating search, filtering, and product-discovery behavior
Developing
IA and UX recommendations
Designing interactive Figma concepts
Creating content and metadata guidance
Building a scalable content-readiness framework
Evaluating product pages against source material
Developing AI-assisted drafting workflows with human review
Creating stakeholder-ready recommendations and handoff artifacts
How the work connected :
One Experience, Three Projects
Rather than treating each project as an isolated deliverable, I looked at where it fit within the larger product journey.
Discover the right product
Product Finder Audit & UX Strategy
Can customers reach a relevant product path and understand why it matches what they need?
Understand the product
Anchor Link Navigation Strategy
Once customers arrive, does the product page give them enough information to evaluate the offering and choose a next step?
Create clearer content experience
IBM.com Documentation Review
Do the teams creating those pages have guidance that is easy to find and apply?
PROJECT 1
Product Finder
Finding the friction
IBM Product Finder helps customers search and browse the product portfolio. I began by evaluating the catalog itself: whether products appeared when searched by their official names, whether the results were accurate and whether the cards and destinations gave customers enough information to move forward.
The audit eventually became a larger UX question:
How much work is the customer doing to find the right product path?
What the Audit Revealed
A strategic visualization of Amelia's path through a fragmented search experience, highlighting the friction points that necessitated a comprehensive functional overhaul.
Four Patterns
Looking across inventory quality, cards, search, and filters surfaced four recurring opportunities.
Option A
Optimized Left Rail
A product-aware customer may already know the product name or family and want to move through the catalog quickly.
For this path, I created an optimized left rail Product Finder concept that keeps the familiar experience while strengthening:
Search guidance
Filter hierarchy
Visible active selections
Result counts and feedback
Buying-option visibility
Product-card clarity
Option B
Guided Discovery
A need-aware customer may know the problem they are trying to solve without knowing IBM's product terminology.
For this path, I developed a guided discovery concept that gives customers another way into the same catalog.
Customers can begin with what they already know, such as:
Business need
Product category
Industry
Buying option
Product family
The selected path narrows the product set while remaining visible so customers can understand why they are seeing those results. Direct search and Browse all products remain available for customers who prefer the traditional catalog experience.
Prototype in action:
Guided Discovery in Action
The concept moves a customer from a broad need into a focused set of product options without requiring them to know the exact IBM product name first.
The intent was to add guidance where it helps while preserving direct browsing for customers who already know where they want to go.
The IA underneath it :
Designing the System Under the Interface
The prototype also reinforced something the audit had already shown: a better interface cannot compensate for weak information underneath it.
A strong discovery experience depends on:
Inventory Quality
Valid products, accurate mappings and useful destinations
Product Identity
Aligned names, page titles, URLs and descriptions
Structured Metadata
Information that can support search, filters, tags and recommendations
Customer language
Search and classification that account for how customers describe their needs alongside IBM terminology
Scaling Clearer Content:
Meta Card Optimizer
Product cards have very little space, but their copy has to help customers quickly understand what the product is, what it helps them do and whether it may be relevant.
I developed a metadata pattern that prioritized:
Official customer-facing product name
Concise value statement
Helpful, decision-relevant tags
During IBM's Pact AI Skills Day, I also created the Meta Card Optimizer in IBM Consulting Advantage.
The tool uses approved product information as source material to generate a concise first draft for Product Finder. The draft still requires human review for accuracy, usefulness and alignment with IBM standards before publication.
Approved product information → AI-assisted draft → Human review → Card description
The goal was to give writers a more repeatable starting point without treating AI as the source of truth.
The project schematically :
BELOW THIS IS A WORK IN PROGRESS
BELOW THIS LINE IS A WORK IN PROGRESS
Takeaways
My primary takeaway was that designing for the most uncertain user—the undecided student—creates a better experience for everyone. By moving away from institutional silos and toward a guided discovery path, I was able to transform a static list into a supportive journey that reduces cognitive load and choice paralysis.
Impact:
The redesign successfully bridged long-standing usability gaps, leading to its adoption as the university's new discovery engine. Once fully implemented, the tool will provide prospective students with a streamlined, mobile-responsive interface to compare over 100 programs through real-time faceted filtering and data-driven comparison tools.
What I learned:
I learned the critical value of a structural pivot based on usability data. My initial high-fidelity prototype followed the legacy table format, but testing revealed it was still too dense for rapid scanning. Pivoting to a card-based system improved accessibility and visual hierarchy, proving that a designer must prioritize user needs over their own initial blueprints.
Next Steps
Since successfully transitioning the project to the UCCS internal team, I have focused on reflecting on the design's potential long-term impact and identifying how these interventions could be scaled in future iterations.
Post-Handoff Design Integrity
Following the delivery of the final design system and interaction documentation, I remain interested in seeing how the internal team adapts the program card components and the Undecided Student Quiz to meet the university's technical backend requirements during the 2026 rollout.
Measuring Long-Term Conversion
If given the opportunity for a post-launch retrospective, I would focus on analyzing whether the integrated Comparison Tool and Advisor Chat effectively reduced the bounce rate for undecided students and increased the quality of initial inquiries to the admissions office.
PROJECT 1
Product Finder
Finding the friction
IBM Product Finder helps customers search and browse the product portfolio. I began by evaluating the catalog itself: whether products appeared when searched by their official names, whether the results were accurate and whether the cards and destinations gave customers enough information to move forward.
The audit eventually became a larger UX question:
How much work is the customer doing to find the right product path?