Storm Bowlings Website

Case Study Roadmap

Research & User Understanding

Section 1: The Question

"What are users actually coming to StormBowling.com for?"

Section 2: Research Synthesis

As responses were grouped and analyzed, larger behavioral patterns began to emerge.

Key Patterns Identified

• Education & Learning
• Product Comparison
• Understanding Ball Motion
• Guidance & Confidence
• Connection to the Sport

Section 3: The Realization

Users weren't just visiting the site to browse products — they were looking for education, guidance, comparison, and a deeper understanding of bowling equipment and the sport itself.

While users consistently expressed a desire for learning and product guidance, the website primarily functioned as a static product catalog with limited educational pathways or decision-support tools.

StormBowling.com — before redesign

A product catalog with no educational content, no learning pathways, and no tools to help users understand equipment or the sport.

Section 4: Opportunity Areas & Future State Outcomes

1. Improve Product Understanding

Users struggled to compare bowling balls and understand technical differences between products.

Proposed Direction

• Compare tool for the website
• Charts and graphs for bowling balls
• System that helps communicate products more clearly

Current Experience

The current experience lacked product guidance and decision-support systems, making product exploration overwhelming for many users.

Future State Outcome

The future-state experience focused on helping users better understand products through guided education, comparison tools, and clearer product communication.

2. Build an Educational Ecosystem

Users wanted clearer learning pathways around bowling technology, lane play, surface prep, and ball motion.

Proposed Direction

• Web pages that break down technical concepts
• Guides that offer practical advice that is actionable
• Develop an ecosystem that ties concepts and complexities together

Current Experience

The existing experience provided limited access to educational content, making it difficult for users to build a deeper understanding of bowling technology, lane play, and equipment behavior.

Future State Outcome

The future-state experience focused on creating connected learning pathways that helped users better understand bowling technology, equipment behavior, and lane play through structured educational content.

Section 5: Strategic Outcomes

Phase 1 established the strategic foundation for the broader website transformation by identifying key gaps in education, product understanding, and community engagement across the platform.

These findings directly informed the creation of:

• The development of a scalable educational ecosystem
• Expanded learning pathways and technical content
• Evolving approaches to product discovery and comparison
• More connected community and brand-focused experiences

Section 6: Early Implementations

Rather than waiting for larger initiatives to be completed, several improvements were implemented immediately based on the opportunities identified during Phase 1. These efforts focused on content visibility, product discovery, educational access, and platform engagement.

Content Visibility & What's New

Content Strategy · Platform Engagement

Reinforce recurring engagement and make fresh content easier to discover.

• Homepage "What's New" section
• New articles
• New videos
• Community content

Educational Content Expansion

Content Architecture · Learning Pathways

Create clearer learning pathways for bowlers looking to improve their understanding of equipment and the sport.

• Bowling 101
• Tutorials
• Articles
• Educational videos

Product Discovery Improvements

Product Comparison · Information Architecture

Make bowling balls easier to browse, compare, and understand.

• Ball Rack
• Reaction Graphs
• Product visibility enhancements

Platform Experience Redesigns

UX Improvements · Platform Strategy

Better align the platform experience with evolving user needs and content strategy.

• Homepage redesign
• About page redesign
• Newsroom development

Educational Ecosystem Design

Section 1: The Challenge

Research revealed that users wanted clearer educational pathways for understanding bowling technology, equipment behavior, lane conditions, and technical terminology. However, the existing platform lacked structured learning systems that supported progressive understanding.

In response, I explored the creation of a scalable educational ecosystem designed to make technical bowling concepts more accessible, interconnected, and easier to navigate.

Early exploration — mapping how users would move through educational content

Mid-fidelity flows exploring how technical concepts could be organized into connected learning pathways across the platform.

Section 2: Ecosystem Thinking

Designing Connected Learning Pathways

Rather than treating educational content as isolated articles, the goal was to create interconnected learning pathways that allowed users to progressively explore bowling technology, equipment behavior, lane play, and ball motion.

Section 3: Educational Implementations

Educational pages were intentionally cross-linked to encourage deeper exploration and support progressive learning across technical bowling concepts.

How a Ball Hooks

Core educational page covering ball motion fundamentals.

The Coverstock

Breaking down coverstock types and their effect on ball motion.

The Weightblock

How core shape influences motion shape and timing.

Surface Adjustments

Grit levels, surface prep, and how they change ball reaction.

Ball Maintenance

Cleaning, oil extraction, and long-term equipment care.

Lane Play

Reading conditions, adjusting angles, and moving with the oil.

Pin Buffer Layout System

How pin-to-PAP distance affects motion shape and transition.

Navigation & Information Architecture

Section 1: The Scaling Problem

As educational content, product systems, and community-focused experiences expanded across the platform, the existing navigation architecture became increasingly difficult to scale and navigate effectively.

Section 2: Navigation Exploration

Section 3: CMS Transition & Mega Menu Exploration

The migration to a new CMS platform created opportunities to expand the navigation architecture through scalable mega menu systems, deeper hierarchy organization, and more flexible desktop and mobile navigation patterns.

Early Navigation Direction

Early navigation concepts focused on utilizing desktop mega menus for broader content exploration while introducing landing-page systems designed to simplify mobile navigation and create more consistent cross-platform pathways.

Desktop navigation concepts focused on broader ecosystem visibility through expandable mega menu systems that surfaced products, educational content, and community pathways more directly.

Mobile Navigation Simplification

Mobile navigation concepts explored simplifying top-level pathways through landing-page systems designed to reduce nested navigation complexity and create more focused exploration flows.

Landing Page Navigation Flows

Desktop navigation concepts focused on broader ecosystem visibility through expandable mega menu systems that surfaced products, educational content, and community pathways more directly.

Implementation Challenges

As the CMS transition evolved, implementation challenges and incomplete supporting systems limited the ability to fully realize the original navigation vision. These constraints ultimately exposed additional opportunities for refinement around hierarchy clarity, content organization, and cross-platform consistency.

• Incomplete supporting systems
• Evolving CMS integration
• Scalability refinement
• Architectural reassessment

Section 4: Refined Information Architecture

As the platform ecosystem expanded, I explored new organizational structures designed to better group products, educational systems, community content, and company information into more scalable navigation pathways.

Community & Company Consolidation

• Community content was consolidated under the broader About ecosystem
• Resources and Events were restructured into dedicated sub-pathways
• Additional company-focused hierarchy was introduced through "Who We Are" and Newsroom systems

Product Ecosystem Separation

• Product navigation was separated into Bowling and Merchandise pathways
• This reduced category density while creating clearer product distinction between performance equipment and lifestyle products
• The restructuring also created opportunities to expand navigational guidance around bowling ball exploration

Educational System Integration

• The original "Explore" structure evolved into a dedicated "Learn" ecosystem
• Educational pathways were reorganized into: Equipment Basics, Setup & Performance, Technology
• This structure aligned the navigation directly with the educational architecture established in Phase 2

Section 5: Navigation Testing

To validate the revised navigation architecture, I conducted a navigation tree test using UXtweak focused on discoverability, learnability, and educational content pathways across the evolving ecosystem.

Testing Overview | Key Findings

• 53.1% directness rate across navigation tasks
• Achieved an 81.3% overall task success rate across navigation tasks
• Educational and product-learning pathways showed strong discoverability performance
• Users were generally able to predict where technical and instructional content would live within the ecosystem
• Lower directness around maintenance and technical terminology revealed opportunities for clearer labeling and category refinement

Tasks were intentionally designed to evaluate whether users could successfully navigate educational systems, technical bowling concepts, product-comparison pathways, and equipment guidance without prior knowledge of the navigation structure.

Key Learnings & Iteration

Based on testing observations, task pathways, and discoverability performance, several organizational and terminology refinements were identified within the educational navigation system.

Ball Buying Research & Decision Systems

Understanding how bowlers research equipment, compare products, build arsenals, and navigate complex purchasing decisions.

Section 1: Research Foundation

Research Focus Areas

As bowling-ball technology expanded, bowlers increasingly relied on fragmented research across YouTube videos, reviews, pro shop operators, and disconnected product information systems.

Research Framework

This document established the foundational research goals and investigative questions that guided the entire ball-buying research initiative.

The study was structured around investigating:

• purchasing behavior,
• comparison processes,
• confidence and uncertainty,
• educational gaps,
• product evaluation,
• and decision-making support systems.

Screener Survey Foundation

The initial screener survey was designed to capture broad behavioral patterns, purchasing habits, confidence levels, and research behaviors across a large range of bowlers with varying experience levels.

1. Participant Background

Questions Explored

• bowling experience
• participation level
• equipment ownership
• player engagement frequency

Purpose

Understand participant diversity, bowling experience ranges, and equipment familiarity across the respondent pool.

2. Purchase & Research Behavior

Questions Explored

• where bowlers research products,
• how they compare equipment,
• what resources influence decisions,
• and how purchasing decisions are validated.

Purpose

Identify how users navigate the bowling-ball research ecosystem and what external systems influence decision-making.

3. Motivation & Selection Criteria

Questions Explored

• purchase motivations,
• performance expectations,
• emotional drivers,
• and product-selection priorities.

Purpose

Understand the underlying factors that drive bowling-ball purchases and how users evaluate product fit.

4. Confidence & Satisfaction

Questions Explored

• confidence during product selection,
• satisfaction with previous purchases,
• and future purchase behavior.

Purpose

Identify where uncertainty, reliance on guidance, and decision-making friction emerge throughout the buying process.

Quantitative Discovery

The screener survey established a quantitative foundation for identifying recurring behavioral patterns, confidence gaps, and research tendencies across a broad range of bowlers.

1. Bowlers Are Highly Engaged

Before analyzing decision-making behaviors, I first needed to understand who these participants were and how involved they were in bowling overall.

2. Research Behavior Was Fragmented

As I analyzed how bowlers researched equipment, a more fragmented decision-making ecosystem began to emerge.

3. Performance Dominated Decision-Making

Performance consistently emerged as the dominant factor influencing purchase decisions.

4. Users Were Informed — But Still Uncertain

One of the most important contradictions emerging from the quantitative research was the gap between information access and decision confidence.

Section 2: Qualitative Deep Dive

Moving Beyond Metrics

Unlike the first survey, which focused on behavioral metrics and broad purchasing trends, this phase used open-ended storytelling prompts to understand how bowlers think through equipment decisions. The goal was to uncover the uncertainty, decision logic, emotional tensions, confidence gaps, frustrations, and mental models guiding ball selection.

Selecting Participants for Deeper Research

Participants were selected based on intersecting combinations of behaviors, demographics, purchasing habits, and experience levels in order to capture a broad range of perspectives on bowling ball buying.

Coding Qualitative Responses

As responses came in, I began coding recurring ideas, behaviors, frustrations, and decision patterns across participants.

Each response was tagged and grouped based on emerging themes related to:

• looking for "similar" balls,
• filling gaps in an arsenal,
• ball motion and lane interaction,
• relying on reviews or YouTube,
• comparing multiple options,
• pro shop recommendations,
• layouts and drilling concerns,
• trusted pro shop recommendations,
• and reactions to balls exceeding or failing expectations.

This process helped translate large volumes of qualitative feedback into structured behavioral patterns that could later be synthesized into deeper insights.

Emerging Mental Models

Bowlers repeatedly described products using conceptual archetypes rather than official manufacturer terminology.

Users were already organizing bowling balls into their own mental classification systems.

This revealed an opportunity to design navigation, filtering, and educational experiences around the language users naturally rely on when exploring products:

• Clean Symmetrical Pearl
• Continuous Solid
• Strong Asymmetrical
• Benchmark Ball
• A Transition Ball

Affinity Codes

Related behavioral codes were synthesized through affinity mapping to surface broader behavioral patterns across the dataset.

Patterns emerging

Bowlers think in lineup roles

• Supporting role dynamics
• Complementary needs
• Gaps & holes

Decision confidence is layered

• Bargaining code concerns
• Trust signals
• Anchored baselines

Expectation gaps create uncertainty

• Mismatch code concerns
• Ball didn't perform
• Confusion persists

Themes Formed

01

Building the Arsenal

Core user tension

How bowlers think about lineup roles, fit, and ball relationships

What are they trying to figure out?

"Will this meaningfully expand my lineup — or just duplicate what I already have?"

How they reason

• Benchmark ball
• Ball down
• Big hook piece
• Transition option
• "I'm looking for X"

Where they get stuck

They struggle to understand what their current arsenal is actually doing — and whether a new ball truly changes anything.

What it reveals

Bowlers think in systems, not standalone products.

02

Decision-Making & Comparison

Core user tension

How bowlers build confidence before committing to a purchase

What are they trying to figure out?

"How do I know this is the right ball?"

How they reason

• Reviews & YouTube
• Spec comparisons
• Process of elimination
• PSO validation
• Gut feel / brand trust

Where they get stuck

Too many sources, conflicting opinions, and no clear way to compare options apples-to-apples.

What it reveals

Decision confidence is built through layered trust — but the process is fragmented.

03

Uncertainty & Mismatches

Core user tension

Where expectations don't align with real-world performance

What are they trying to figure out?

"Will this actually do what I think it will?"

How they reason

• Spec shorthand ("pearl = flip")
• Marketing language
• Gut assumptions
• Layout optimism
• Expected motion formulas

Where they get stuck

The ball doesn't behave the way they expected — and they can't tell if the issue was specs, layout, or lane conditions.

What it reveals

Expectation gaps create post-purchase uncertainty and erode trust.

04

Positive Confirmation

Core user tension

Moments where bowlers feel like they got it right

What are they trying to figure out?

"Did I make the right decision?"

How they reason

• Reflecting on ball performance
• Comparing against past equipment
• Reinforced trust in specs or feel
• Emotional payoff / confidence
• Brand or ball-type loyalty

Where they get stuck

They often can't clearly explain why the ball worked — making that success difficult to replicate in future decisions.

What it reveals

Positive ball experiences become emotional trust anchors that shape future buying behavior.

05

Mental Models of Ball Motion

Core user tension

How bowlers try to predict ball motion before ever throwing it

What are they trying to figure out?

"What will this ball actually do?"

How they reason

• Visual analogy ("bigger core = bigger motion")
• Descriptive shorthand ("snappy," "strong," "smooth")
• Simplified formulas ("asym solid = early roll")
• Category assumptions
• Mental motion shortcuts

Where they get stuck

Motion language is inconsistent, specs interact in complex ways, and expectations often don't match real-world ball behavior.

What it reveals

Bowlers rely on overly simplified mental shortcuts to predict motion — but those models often break down in real use.

Section 3: Deepening the Human Story

Behavioral themes revealed broad patterns across the dataset, but interviews, personas, and journey mapping helped uncover the human stories, decision logic, and emotional friction behind those behaviors.

Going Deeper Through Interviews

Interviews were conducted to probe these themes more deeply, uncovering the reasoning, personal stories, and decision-making logic that broad survey responses alone could not fully explain.

Interview Discussion Guide

Semi-structured interviews were designed to probe the recurring themes uncovered in earlier synthesis, exploring how bowlers think, compare, trust, struggle, and imagine a better buying experience.

Interview Insights

Interviews added human depth to the themes, revealing how bowlers navigate uncertainty, build confidence, interpret motion, and rely on external guidance in real decision-making moments.

Personas Created

The interview insights exposed recurring themes around comparison behavior, trust, uncertainty, and ball motion understanding. Personas were then developed to translate those themes into concrete user archetypes that could be mapped across the full buying journey.

Persona Journeys & Experience Maps

To understand how these behavioral patterns unfold across the buying journey, each persona was mapped across moments of awareness, research, evaluation, and decision-making to surface emotional shifts, friction points, and design opportunities.

Section 4: Opportunity Areas

The personas and experience maps revealed recurring friction across the buying journey — from uncertainty around ball motion and lane conditions to comparison overload and lack of confidence in decision-making.

The following opportunity areas and "How Might We" questions were created to guide future ideation and product direction.

Section 5: Translating Research Into Clearer Ball Motion Systems

Ball Reaction Design System

This led to the development of a scalable ball reaction design system built around shared motion language, comparison logic, and reaction-based classification.

Motion Shape

Defined the overall visual shape of ball motion — from smooth, blended reactions to high-angle skid-flip motion.

This created a shared framework for discussing backend shape without relying on inconsistent buzzwords or vague comparison language.

Hook Phase Timing

Established where the ball begins reading the lane, helping bowlers differentiate between early traction, benchmark reads, and delayed backend motion.

This helped connect lane conditions and oil volume to reaction timing in a more understandable way.

Friction Response

Translated technical friction response behavior into more intuitive phrases bowlers already use in conversation — like "Smooth Off The Spot" or "Responsive To Friction."

This created a clearer bridge between technical ball motion and real-world player language.

Archetype System

Combined motion shape, hook timing, and friction response into higher-level ball archetypes that could support browsing, comparison, pairing logic, and future recommendation systems.

This created one of the first scalable reaction-based classification frameworks for organizing bowling balls by motion type instead of only technical specs.

Building Consistency Across the Catalog

As the framework was applied across the product catalog, consistent behavior relationships began emerging between shape, friction response, and timing characteristics.

Skid flip balls consistently align with faster friction responses while smoother shapes aligned with slower friction responses.

Applications Across the Ecosystem

Once the framework established a consistent language for ball motion and comparison, it became a scalable foundation for multiple tools, educational systems, and product experiences across the ecosystem.

Matchmaker

• Reaction Matching
• Arsenal-Based Logic
• Lane Context
• Recommendations

Product Pages

• Motion Metrics
• Player Fit
• Pairing Logic
• Archetypes
• Tool Tip Explanations

Filtering & Navigation

• Browse by Reaction
• Motion Categories
• Archetype Filtering
• Comparison Tools

Arsenal Builder

• Role Differentiation
• Gap Analysis
• Transition Strategy
• Benchmark Logic

Product Page Enhancements

Instead of relying purely on technical specs, product pages began incorporating reaction-based classification, player-fit guidance, pairing logic, and motion visualization systems built directly from the framework.

Matchmaker Redesign (WIP)

The original matchmaker relied heavily on technical bowler specs and generalized filtering logic, creating friction for users who didn't fully understand their game, equipment, or reaction needs.

01

Shift 1 — From Specs → Reaction Goals

Instead of requiring bowlers to understand technical specs upfront, the redesigned experience guided users toward shared reaction goals and motion archetypes using terminology grounded in real bowling language.

02

Shift 2 — Arsenal-Aware Recommendations

The recommendation logic was rebuilt around the three primary decision mindsets identified in the research: replacing an existing ball, filling a gap in an existing arsenal, and trying a different reaction shape. This allowed recommendations to become more contextual instead of purely spec-driven.

03

Shift 3 — Existing Equipment Context

To improve recommendation accuracy, the matchmaker incorporated existing equipment context into the decision process. Instead of recommending balls in isolation, the system evaluated new options relative to a user's existing arsenal — avoiding smoother, earlier, stronger, or more angular recommendations based on what they already throw.

04

Shift 4 — Deeper Educational Touchpoints

The redesign also introduced deeper educational pathways directly within the recommendation experience, allowing users to explore why specific balls were recommended and how different reaction characteristics related to their goals.

Arsenal Builder

The Arsenal Builder translated Storm's existing arsenal matrix philosophy into a more guided and understandable selection experience using the shared reaction language established through the ball reaction framework.

Guided Selection Logic

The experience used the reaction framework to control which bowling balls appeared at different stages of the matrix process.

Consistent Reaction Classification

The shared motion framework created a more consistent way to organize and categorize bowling balls across the matrix experience.

Making an Internal System More Accessible

The project helped translate an expert-driven internal framework into a more approachable and functional experience for bowlers navigating arsenal decisions.

Filtering & Navigation

The shared reaction framework also created new opportunities for browsing and comparison by allowing bowlers to navigate equipment by reaction type instead of relying only on coverstock names, release dates, or brand familiarity.

Before

After

This introduced a browsing model that is largely absent across the bowling industry, where equipment is typically organized by release date, coverstock, or manufacturer naming conventions rather than reaction behavior.

Outcome & Next Steps

The research and resulting design systems established a scalable foundation for how bowling ball motion could be described, compared, and operationalized across the ecosystem. Several systems, including the redesigned Matchmaker experience, moved into implementation and testing environments, while broader validation and organizational rollout remained ongoing.

Final Reflection

Alongside my day-to-day responsibilities of maintaining and developing the Storm website — including product launches, landing pages, educational experiences, and broader front-end platform work — I led a large-scale UX research initiative focused on understanding what bowlers were actually looking for from the digital experience.

What began as research into website expectations and bowling ball buying behavior ultimately expanded into broader systems for education, comparison, motion language, and decision support across the Storm ecosystem.

The work helped establish more scalable ways to describe ball motion, support arsenal-building decisions, and connect technical bowling concepts to more understandable user experiences.

And while many of these systems continue to evolve, the project reinforced the value of combining UX research, systems thinking, front-end development, and domain expertise into scalable product experiences and shared motion language across the ecosystem.

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