Kyle
Evans

Background

Once HealthEquity HSA members save a certain amount in their health savings accounts, they can invest the additional funds in a variety of mutual funds. As a product team, we knew from analytics that a significant number of users didn't complete investment onboarding — and we needed to fix this to grow our investment users and help members maximize the benefits of their HSA.

Process

I used both qualitative and quantitative data to create a significantly better investment onboarding experience. When I joined the role, we knew the experience was clunky and outdated, but didn't know where to focus. I started by analyzing the user flow from our existing instrumentation. I noticed a 50% drop-off at one point in the onboarding process, and another where roughly 75% of users fell out. That gave me the context to dive deeper.

I started by watching actual users go through the onboarding flow without interfering — I wanted to see the process from their point of view. After a series of user interviews, I had a clearer picture of the problems: being overwhelmed by choices, unfamiliarity with investing, and fear of committing. I worked with our UX team to design new user flows, mocked them up in Invision, and spent several days onsite with customers walking through our prototypes.

Key Insight

We were presenting users with too many choices too early. Right at the start, we asked them to pick between three investment guidance modes — Auto Pilot, GPS, or Self Driven — before they fully understood their own needs or preferences. This caused immediate drop-off and confusion.

Solution

Rather than front-loading three options, we needed to guide users through the process. This meant simplifying decisions at each step, segmenting users along the way to route them down the right path, and adjusting the pricing structure to match. I made the pitch to our investment team, sales, marketing, and stakeholders — using the quantitative data and qualitative feedback to demonstrate the need for change. We moved forward with additional testing sessions and released the first iteration, consolidating choices and removing friction.

Results

We saw an initial increase of adoption of 400% as users were able to more easily complete the onboarding flow. We also saw a 25% increase in initial investments as fewer users dropped out before getting their HSAs invested.

Background

As Western Governors University grew, it became clear that off-the-shelf technology could no longer serve its unique competency-based education model. WGU built out a product management organization — which I was among the first to join — and I had the opportunity to both help shape that org and lead one of its flagship initiatives: the Evaluation Management Application (EMA).

What We Built

EMA was three applications in one. First, an assessment creation and publishing platform for faculty to author and publish assessments to the system. Second, a fully integrated student-facing experience embedded directly into the WGU student portal — seamless and requiring no external portals or vendor logins. Third, an evaluator platform where faculty graders could receive, evaluate, and return submitted exams efficiently. With one of the largest evaluator faculty groups at WGU, maximizing their time was critical.

Start Small, Scale Fast

We began testing with just one exam, one class of 13 students, and a single evaluator. This meant doing significant manual work "behind the curtain" early on — but the lessons learned allowed us to scale dramatically over the following months as more colleges, departments, students, and evaluators came on board.

The Architectural Pivot

Early on, we chose Cassandra (a non-relational database) based on available team expertise. As we scaled, performance issues emerged around unmanaged database tombstones — and our Cassandra expert departed. Combined with an organizational push to migrate to AWS, we made the strategic decision to move to Aurora. This required a near-complete application rewrite and full data migration, pausing all feature development. I led the team through scoping, stakeholder communication, and execution. We completed the migration and move to AWS in 6 months, aligned with our conservative timeline.

Launch

The rollout was a multi-phased effort involving every department at the university. I navigated competing pressures — speed vs. change management — and worked closely across groups, adjusting timelines as needed. We hit our key goal of launching to the full university on schedule, and eventually onboarded other institutions onto the platform as well. The platform generated over $2 million in savings in the first fiscal year, reduced faculty evaluation time by 10%, and decreased student turnaround time by 30%.

The Problem

At OpenSpace, I quickly realized we needed a better way to scale decision-making and ensure that teams and product managers were empowered to act without getting slowed down by unnecessary meetings or escalations. The core issue: many decisions had long been centralized with a few executives. As the company grew, so did the product and engineering team — and we needed a way to move fast without sacrificing on core principles everyone agreed on.

The Workshop Process

I led our team through a series of structured exercises to surface where we were currently making decisions, what we actually valued based on our behavior, and where our most urgent pain points were. Once we identified the key tensions, we had an open discussion about where they most frequently appeared in our product work.

From there, I asked everyone to write out the tensions they experienced and post them on sticky notes. We grouped similar ideas, then plotted opposing ideas on continuums — forcing us to pick a side. For example: Should our product prioritize simplicity for new users, or depth for power users? We created around 16 continuums and had the team vote with dots, revealing exactly where consensus existed and where it didn't.

Crafting the Principles

I led the team in a discussion on each continuum, drawing out reasoning from anyone who voted at the extremes or where outliers appeared. I then synthesized the conversation and voting patterns into 10 clear product principles and tenets, which were reviewed with leadership to build broader buy-in before implementation.

The 10 Principles

1. We value simplicity over robustness, and prioritize new and less tech-savvy users over power users.
2. We are prescriptive — we take a stand for what's best for our product and users.
3. We value speed: move fast to beta, but confidently to full release.
4. We are building a holistic solution — one answer to many problems over many answers to many problems.
5. We build for self-service — customers should never need our help to use our product.
6. We prioritize the user and their experience over our own business needs or the purchaser.
7. We integrate broadly — building so users can move fluidly between OpenSpace and other tools in their workflow.
8. We prioritize for highest value, though not for any single customer or small group.
9. We prioritize long-term over short-term and are proactive rather than reactive.
10. We validate our assumptions — using qualitative and quantitative data to make decisions.

Outcome

These principles became a living document, revisited and refined periodically as the team experimented with them and gathered feedback. They gave the product organization a shared language for decision-making and reduced the need for escalation — freeing teams to move with speed and confidence.

Background

At Clearlink, our product organization worked closely with marketing partners to build products, test ideas, and drive better business outcomes. While we regularly ran A/B tests on copy and images, I wanted to expand that methodology to test actual user flows and experiences. This was a bigger lift — more development work, more stakeholder buy-in — but I was confident that better experience design, not just better wording, would move the needle.

The Hypothesis

We targeted an online retail site that gathered user information and funneled visitors toward either signing up online or calling to purchase. Our hypothesis: by simplifying the user flow and eliminating over two-thirds of the steps between first action and purchasing decision, we could significantly increase conversions by reducing friction and demanding less of potential customers.

Building Buy-In

We created prototypes, reviewed designs, and spent significant time preparing stakeholders at a large telecommunications partner that was resistant to change. This groundwork was essential — not just for getting approval to run the test, but for ensuring the partner would let the test run its full course without stopping early based on early (and potentially misleading) results.

Running the Test

We ran a two-week test, randomly assigning visitors to either the original experience or our redesigned flow, while tracking unique users to maintain consistent experiences for return visitors. We used the same rigor applied to our marketing A/B tests: a full testing window, appropriate confidence intervals, and a pre-set significance threshold (p = 0.05) to avoid the temptation of stopping early due to noisy early results.

Results

The results exceeded our expectations. We achieved a p-value of 0.01 — well beyond our threshold — with conversions nearly doubling on the redesigned experience versus the original. This wasn't just a win for that one site. It validated the broader case I was making internally: that investing in UX design — not just copy or aesthetics, but the entire user journey — delivers measurable, significant business value. I used this result as a proof point in conversations with other partners and internal stakeholders for years afterward.

Background

As Teem was acquired first by iOffice and then by SIQ, it was critical to establish a cohesive product vision and strategy — defining Teem's positioning within the market, against competitors, and across the portfolio of companies in the organization. I developed a comprehensive analysis and then socialized it broadly to build alignment and support.

Understanding the Market

I started with the macro context: companies and employees were gradually returning to offices in the wake of COVID-19, but the longer-term picture was a permanent mix of remote, hybrid, and in-office work. Understanding this landscape was essential for crafting a vision that was relevant both immediately and durable over time.

Understanding Our Users

Next, I focused on users — their immediate needs as they returned to offices, and their longer-term needs as work patterns continued to evolve. Teem had always been built with the employee experience first, making it notably easier and more intuitive than competitors who had started from the administrative side and were now moving toward employee-facing features. That was a key differentiator worth protecting and extending.

Competitive Landscape

I mapped Teem's history and competitive position — both against direct competitors and against adjacent solutions entering the space. While other players were expanding from admin tools into employee experience, Teem was moving in the opposite direction: from strong employee UX toward richer administrative capabilities. This created a clear positioning opportunity: the platform that was built for people first.

Vision, Positioning & Strategy

With a thorough understanding of the market, users, competitors, and company challenges, I crafted a product vision that addressed key user needs, leveraged Teem's strengths, and focused efforts on the most important experiences for the new work environment. I also defined our product positioning within the broader PE portfolio — clarifying where Teem fit and where it didn't — and developed a product strategy to guide prioritization of existing and new development.

Outcome

With a vision and strategy in place, the team was able to focus development efforts, prioritize new features correctly, and communicate a clear direction to leadership, partners, and the broader organization. It was the beginning of a much firmer and more confident direction for Teem.

Background

WGU Academy is a growing division of Western Governors University focused on helping students build academic readiness before enrolling in WGU. When I joined, the team was eager to accelerate — and part of my role was to help establish a clearer product foundation to support that growth.

Building the Foundation

Working closely with the team, we established a shared product roadmap, end-to-end strategy, and foundational product and UX processes. Aligning five product squads around OKRs and defined product areas helped sharpen focus and significantly increased delivery velocity. We also introduced monthly business reviews and KPI dashboards to keep leadership informed and decisions moving quickly.

AI Motivational Assistant

One of the early bets we made was on AI-powered student engagement. I led the launch of a pilot AI motivational assistant designed to re-engage students who had become disengaged from their coursework. The results exceeded expectations — the assistant doubled reactivation rates among disengaged students, validating the broader AI strategy for the platform.

Platform Transformation

I'm also leading a full platform transformation, replacing the Academy's legacy architecture with a modern, scalable technology stack to improve usability and support long-term growth. Alongside this, I'm building an AI-powered academic course and content creation tool projected to reduce time to market by 75%, and driving development of the Academy's first mobile application — designed to increase student engagement and reduce time to completion by 20%.

Operational Impact

Beyond product, I've driven meaningful operational improvements — reducing support ticket volume by 50% and cutting resolution time for major issues by 75% through process improvements and targeted platform enhancements. I'm also building custom-branded Academy products for partner institutions to improve student readiness, drive matriculation, and reduce cost of acquisition.

Background

As Principal Product Manager at Walmart, I directed the strategy, roadmap, and execution for the company's enterprise-wide employee feedback ecosystem — spanning 2.1 million associates across Walmart stores, Sam's Club, and corporate offices. The existing systems were fragmented, slow to deploy, and produced data that was difficult for managers to act on quickly.

Qualtrics Enterprise Rollout

I drove an enterprise RFP process that resulted in the selection and rollout of Qualtrics as the unified feedback platform — cutting survey deployment time by 40% and costs by 10%. I then led the integration of Qualtrics with Walmart's internal systems to support 10M+ annual survey responses, improving data accuracy and reducing deployment time from weeks to days.

AI-Powered Analysis

A key innovation was incorporating AI-powered analysis to automatically surface the top three and bottom three focus areas from survey results for managers, along with recommended action steps. This reduced analysis time by 50% and improved manager follow-through rates by 20% — turning raw survey data into clear, actionable priorities at scale.

Modernizing Feedback Channels

I also modernized the feedback channels used for associate concerns, ideas, and surveys — increasing associate participation rates by 15% and cutting resolution times for escalated issues by 35%. I partnered with HR, operations, and technology teams to enhance real-time reporting dashboards, enabling leadership to identify and act on emerging issues within 48 hours.

Background

The opportunity was clear: build a modern, white-labeled IRA rollover platform that financial advisors could offer to their clients under their own brand, while automating the complex compliance and operational work that traditionally made IRA rollovers slow and error-prone.

Building the Platform

I led the strategy and delivery of the platform end-to-end, integrating third-party APIs to automate account creation, identity verification, and rollover processing. This eliminated significant manual work from the process and made it possible to scale without adding operations headcount proportionally. Automation of key advisor and compliance workflows also reduced manual operations by 50% for Roth and Traditional IRA reporting.

Advisor Experience & Branding

A core differentiator was the advisor-facing experience. We built advisor branding and co-branded marketing tools that allowed advisors to present the platform under their own identity — increasing advisor engagement by 30%. Automated, compliance-approved email campaigns further improved prospect-to-client conversion by 20%.

Results

The platform scaled to 5,000 accounts and over $50M in assets in its first year — a strong validation of both the product and the market opportunity. It was recognized as a finalist for a major industry award for new retirement technology, and an overhauled sales-to-delivery process cut post-sale rework by 25%, improving both the advisor and operations experience.